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스크립트에서 "黄金近50年的走势"에 대해 찾기

RSI - colour fillThis script showcases the new (overload) feature regarding the fill() function! 🥳 2 plots could be filled before, but with just 1 colour per bar, now the colour can be a gradient type. In this example we have 2 plots - rsiPlot , which plots the rsi value - centerPlot, which plots the value 50 ('centre line') Explanation of colour fill in the zone 50-80 Default when rsi > 50 - a bottom value is set at 50 (associated with colour aqua) - and a top value is set at 80 (associated with colour red) This zone (bottom -> top value) is filled with a gradient colour (50 - aqua -> 80 - red) When rsi is towards 80, you see a red coloured zone at the rsi value, while when rsi is around 50, you'll only see the colour aqua The same principle is applied in the zone 20-50 when rsi < 50 Cheers!
Pine Script® 인디케이터
fikira의
10
RSI band with Signal alert//th/en //th สวัสดีครับท่านสมาชิก ก่อนอื่นต้องขอเกริ่นก่อนเลยว่า Indicator ตัวนี้ถูกสร้างขึ้นมาบนพื้นฐานของ RSI จริง เพียงแต่ใช้ค่า EMA27 ในการสร้าง เนื่องจากผมยังไม่สามารถเขียน RSI band ที่โยงกับราคาได้ในส่วนนี้เองได้ แต่ทั้งนี้ขอให้ท่านใจเย็น ๆ และฟังผมสักหน่อย เนื่องจากก่อนหน้านี้ผมได้สังเกตเห็นว่า EMA27 นั้นมีค่าเท่ากับ RSI14 ที่ค่า 50 พอดี ดังนั้นผมจึงเลือกที่จะสร้างมันขึ้นมาด้วย EMA27 เพราะง่ายต่อการเขียน วิธีการใช้งานมีดังต่อไปนี้ Indicator ตัวนี้ใช้งานเหมือน RSI14 วิธีการอ่านคือให้นับเส้น EMA27 เป็นค่า 50 ของ RSI14 ดังนั้นให้เราพิจารณาการซื้อขายดังต่อไปนี้ (โดยหลังจากนี้ผมจะเรียก EMA27 ที่สร้างขึ้นว่า RSI band) พิจารณาเข้าซื้อ : เมื่อราคาทะลุ RSI band ขึ้นไปและย่อตัวทำ Higher Low เหนือเส้น RSI band พิจารณาขายออก : เมื่อราคาทะลุ RSI band ลงมาและรีบาวน์ทำ Lower High ใต้เส้น RSI band # ทั้งนี้ผมได้ทำสีแท่งเทียนไว้เพื่อให้ง่ายต่อการสังเกต โดยการนำไปใช้อาจนำสีของเส้นขอบแท่งเทียนออก แล้วในส่วนของไส้แท่งเทียนให้ใช้สีที่ไม่เจาะจงราคาบวกลบอย่างสี #434651 โดยเราสามารถดู Divergence โดยการเทียบความต่างระหว่างราคาและ RSI band ได้ดังนี้ ในแนวโน้มขาลง : ให้เปรียบเทียบความต่างระหว่างราคากับ RSI band ของ Lower Low ปัจจุบันกับ Low ก่อนหน้า โดยถ้าความต่างของ Low ลดลงเรื่อย ๆ จนราคาเข้าใกล้เส้น RSI band ให้พิจารณาเข้าซื้อ ในแนวโน้มขาขึ้น : ให้เปรียบเทียบความต่างระหว่างราคากับ RSI band ของ Higher High ปัจจุบันกับ High ก่อนหน้า โดยถ้าความต่างของ High ดลงเรื่อย ๆ จนราคาเข้าใกล้เส้น RSI band ให้พิจารณาขายออก ทั้งนี้ผมได้สร้าง Signal alert ไว้เพื่อให้ง่ายต่อการสังเกต โดยสร้างมาจากเงื่อนไขดังนี้ (ห้ามทำการซื้อขายตาม Signal alert เด็ดขาด เพราะเค้าแค่บอกจุดตามเงื่อนไขที่ตั้งไว้ บางทีอาจมีสัญญาณซื้อแล้วให้ซื้อต่อโดยไม่มีสัญญาณขายเลยก็ได้) Buy : เมื่อ RSI14 ตัดขึ้นที่ค่า 50 พร้อมกับ RSI14 ตัดขึ้น Signal ที่ผมตั้งไว้ (ผมใช้ EMA7 ของ RSI14) Prepare to Sell : เมื่อ RSI14 ตัดลง Signal ในขณะที่ RSI14 นั้น มีค่ามากกว่า 70 Sell/Short Top : เมื่อ RSI14 ตัดลงที่ค่า 70 พร้อมกับ RSI14 ตัดลง Signal (จะมีขึ้นแสดงว่า Peak ในกราฟ) Buy : เมื่อ RSI14 ตัดลงที่ค่า 50 พร้อมกับ RSI14 ตัดลง Signal Prepare to Buy : เมื่อ RSI14 ตัดขึ้น Signal ในขณะที่ RSI14 นั้น มีค่าน้อยกว่า 30 TP Short/Buy Bottom : เมื่อ RSI14 ตัดขึ้นที่ค่า 30 พร้อมกับ RSI14 ตัดขึ้น Signal (จะมีขึ้นแสดงว่า Deep ในกราฟ) # สาเหตุที่ใส่ข้อความใน Signal alert เพียงแค่ตอน Sell/Short Top และ TP Short/Buy Bottom เพื่อลดโอกาสเกิดการแพนิคที่เกิดจากการสังเกตได้ โดยในสัญญาณตัวอื่นจะมีแค่เครื่องหมาย * เพียงอย่างเดียว ขอให้โชคดีครับ Firstssk //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// //en (Google Translate) Hello, Trader First of all, I have to say that this indicator is built on the basis of a real RSI, just using the EMA27 value to create it, since I still can't write an RSI band that is tied to the price in this section. But please be patient and listen to me a bit. Since I previously noticed that EMA27 is exactly equal to RSI14 at 50, so I chose to build it with EMA27 because it's easier to write. Here's how to use it: This indicator works like RSI14. The reading method is to count the EMA27 line as the 50 value of RSI14, so let's consider the following trading. (After this I will call the created EMA27 RSI band) Consider buying : When the price breaks the RSI band up and makes a Higher low above the RSI band. Consider selling : When the price breaks the RSI band down and rebounds to make a Lower high below the RSI band. # However, I have colored the candlesticks to make them easier to spot. By applying it may remove the color of the candlestick border. Then for the wick part, use a color that does not specify the price plus and minus color #434651 We can see the divergence by comparing the difference between the price and the RSI band as follows. In a downtrend : Compare the difference between the price and the RSI band of the current Lower Low and the previous Low. If the divergence of the Low continues to decrease until the price approaches the RSI band, consider buying. In an uptrend : Compare the price difference between the RSI band of the current Higher High and the previous high. If the divergence of the High continues to decrease until the price approaches the RSI band, consider selling. I have created a Signal alert for easy observation. It was created from the following conditions: (Do not trade according to Signal alert strictly because they just tell the point according to the conditions set There may be a buy signal and then buy again without a sell signal.) Buy : When RSI14 crosses above 50 with RSI14 crosses up the signal I set (I use EMA7 of RSI14). Prepare to Sell : When RSI14 crosses signal while RSI14 is greater than 70. Sell/Short Top : When RSI14 crosses down at 70 with RSI14 crosses down Signal (it will show "Peak" on the chart) Buy : When RSI14 crosses down to 50 with RSI14 crosses down signal. Prepare to Buy : When RSI14 crosses signal while RSI14 is less than 30. TP Short/Buy Bottom : When RSI14 crosses above 30 with RSI14 crosses up signal (it will show "Deep" in the chart). # The reason why I put the message in Signal alert only at Sell/Short Top and TP Short/Buy Bottom to reduce the chance of panic occurring from observation. In other signals, there will only be a * sign. Good luck. Firstssk
Pine Script® 인디케이터
Firstssk의
12
Divergence of Stocks Above MA50 v.s. US-Stock MarketEnglish: This indicator has been developed as an early warning tool to estimate the probability of correction in the US stock market. It works best in the daily chart. Function: 1.) "Index-line" The underlying stock index is converted to a scale between 0% and 100% based on its 52-week highs and lows. Where 100% is closing price at 52-week high and 0% is closing price at 52-week low. 2nd) "Stocks Above MA50". For each major stock index, there is an index that determines the percentage of stocks above its 50 moving average. For example, for the S&P 500, this is the S5FI. 3) "Divergence In an efficient market, both lines (index and number of stocks above the 50 MA) would run more or less in sync. A new high in the index would also mean a new high in the stocks trading above the 50 moving average. Often, however, a correction in the index is announced when the number of stocks trading above their 50 MA do not make a new, or even a lower, high while the underlying index marks a new high. The divergence signal measures this divergence of the indices. The higher the bar, the more pronounced the divergence. How to read the indicator? If a divergence occurs, then the stops should be tightened. As with any indicator, false signals can occur because a divergence does not automatically lead to a correction. The higher the divergence is indicated, the higher the probability. The strength of a correction cannot be predicted with the indicator. For which symbols does the indicator work? The indicator works exclusively for the following symbols: S&P500: SPX, SPY, ES1!, US500 Index above MA50: S5FI Russel2000: IWM, US2000, RTY1!, RUT, IWO Index above MA50: R2FI NASDAQ100: NDX, NAS100, NQ1!, US100, QQQ Index above MA50: NDFI NASDAQ: IXIC, ONEQ, QCN1!, NDAQ Index above MA50: NCFI NYSE: XAX, NYA Index above MA50: MMFI DowJones100: DJX, DJI, DIA, MYM1!, YM1! Index above MA50: DIFI DowJonesComp: DOW, IYY Index above MA50: DCFI Deutsch: Dieser Indikator ist als Frühwarninstrument zur Einschätzung der Korrekturwahrscheinlichkeit im US-Aktienmarkt entwickelt worden. Er funktioniert am besten im Tages-Chart. Funktion: 1.) „Index-line“ Der zugrunde liegende Aktienindex wird bezogen auf seine 52Wochen Hochs und Tiefs in eine Skala zwischen 0% und 100% umgerechnet. Dabei sind 100% Schlusskurs auf 52-Wochen Hoch und 0% Schlusskurs auf 52-Wochen Tief. 2.) „Stocks Above MA50“ Zu jedem Hauptaktienindex gibt es einen Index, der den Prozentwert der Aktien über Ihrem 50 gleitenden Durchschnitt ermittelt. Beim S&P 500 ist das z.B. der S5FI. 3.) „Divergence“ In einem effizienten Markt würden beide Linien (Index und Anzahl Aktien über dem 50 MA) mehr oder weniger synchron laufen. Ein neues Hoch im Index würde auch ein neues Hoch bei den Aktien, die über dem 50 gleitenden Durchschnitt notieren, bedeuten. Oft jedoch kündigt sich eine Korrektur im Index an, wenn die Anzahl der Aktien, die über ihrem 50 MA notieren kein neues, oder sogar ein niedrigeres Hoch machen, während der zu Grunde liegende Index ein neues Hoch markiert. Das Divergenz-Signal misst diese auseinanderlaufen der Indices. Je höher der Balken, umso stärker ist die Divergenz ausgeprägt. Wie ist der Indikator zu lesen? Wenn eine Divergenz auftritt, dann sollten die Stopps enger herangezogen werden. Es kann wie bei jedem Indikator zu Fehlsignalen kommen, da eine Divergenz nicht automatisch zu einer Korrektur führen muss. Die Wahrscheinlichkeit ist um so höher, je höher die Divergenz angezeigt wird. Die Stärke einer Korrektur kann mit dem Indikator nicht prognostiziert werden. Für welche Symbole funktioniert der Indikator? Der Indikator funktioniert ausschließlich für folgende Symbole: S&P500: SPX, SPY, ES1!, US500 Index über MA50: S5FI Russel2000: IWM, US2000, RTY1!, RUT, IWO Index über MA50: R2FI NASDAQ100: NDX, NAS100, NQ1!, US100, QQQ Index über MA50: NDFI NASDAQ: IXIC, ONEQ, QCN1!, NDAQ Index über MA50: NCFI NYSE: XAX, NYA Index über MA50: MMFI DowJones100: DJX, DJI, DIA, MYM1!, YM1! Index über MA50: DIFI DowJonesComp: DOW, IYY Index über MA50: DCFI
Pine Script® 인디케이터
Benni_R의
2
KD compare strategy (交易策略對照組)This is a base and easy trading strategy for comparing my other strategy. The strategy consider K >= 80 is strong target in the last high period, and consider K <=20 is the weak target in the last low period. In the strong target, the strategy may increase long at the first day when K < 50, until 2/3 max order limitation or strong target become to weak. In the weak target, the strategy may increase short at the first day when K > 50, until 2/3 max order limitation or strong target become to strong. there are three orders for this strategy. when the strong become to weak, it may use the remain 1/3 to save itself, and change the direction at the next k > 50 when the weak become to weak, it may use the remain 1/3 to save itself, and change the direction at the next k < 50 這是一個簡單的雙向交易策略，用來對照我其他的策略。 當 K>=80 它會認為目前是強勢股，偏多操作 當 K<=20 它會認為目前是強勢股，偏空操作 當標的為強勢股時，當第一次 K<50 會加碼多單，最多買進2/3的持股，直到轉弱 當標的為弱勢股時，當第一次 K>50 會加碼空單，最多買進2/3的持股，直到轉強 當強勢轉弱勢時，會使用剩下的1/3來拯救持股，在下次 k > 50 出清持股 當弱勢轉強勢時，會使用剩下的1/3來拯救持股，在下次 k < 50 出清持股
Pine Script™ 전략
Tonyder의
Hidden Divergence with S/R & TP// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © Gemini // @version=5 // This indicator combines Hidden RSI Divergence with Support & Resistance detection // and provides dynamic take-profit targets based on ATR. It also includes alerts. indicator("Hidden Divergence with S/R & TP", overlay=true) // === INPUTS === rsiLengthInput = input.int(14, "RSI Length", minval=1) rsiSMALengthInput = input.int(5, "RSI SMA Length", minval=1) pivotLookbackLeft = input.int(5, "Pivot Left Bars", minval=1) pivotLookbackRight = input.int(5, "Pivot Right Bars", minval=1) atrPeriodInput = input.int(14, "ATR Period", minval=1) atrMultiplierTP1 = input.float(1.5, "TP1 ATR Multiplier", minval=0.1) atrMultiplierTP2 = input.float(3.0, "TP2 ATR Multiplier", minval=0.1) atrMultiplierTP3 = input.float(5.0, "TP3 ATR Multiplier", minval=0.1) // === CALCULATIONS === // Calculate RSI and its SMA rsiValue = ta.rsi(close, rsiLengthInput) rsiSMA = ta.sma(rsiValue, rsiSMALengthInput) // Calculate Average True Range for Take Profits atrValue = ta.atr(atrPeriodInput) // Identify pivot points for Support and Resistance pivotLow = ta.pivotlow(pivotLookbackLeft, pivotLookbackRight) pivotHigh = ta.pivothigh(pivotLookbackLeft, pivotLookbackRight) // Define variables to track divergence and TP levels var bool bullishDivergence = false var bool bearishDivergence = false var float tp1Buy = na var float tp2Buy = na var float tp3Buy = na var float tp1Sell = na var float tp2Sell = na var float tp3Sell = na // Reset divergence flags at each new bar bullishDivergence := false bearishDivergence := false // === HIDDEN DIVERGENCE LOGIC === // Hidden Bullish Divergence (Higher low in price, lower low in RSI) // Price makes a higher low, while RSI makes a lower low, suggesting trend continuation. for i = 1 to 50 // Look back up to 50 bars for a confirmed pivot low if not na(pivotLow ) and close < close and rsiValue < rsiValue // Check if price is making a higher low than the pivot low, and RSI is making a lower low if low > low and rsiValue < rsiValue bullishDivergence := true break // Exit loop once divergence is found // Hidden Bearish Divergence (Lower high in price, higher high in RSI) // Price makes a lower high, while RSI makes a higher high, suggesting trend continuation. for i = 1 to 50 // Look back up to 50 bars for a confirmed pivot high if not na(pivotHigh ) and close > close and rsiValue > rsiValue // Check if price is making a lower high than the pivot high, and RSI is making a higher high if high < high and rsiValue > rsiValue bearishDivergence := true break // Exit loop once divergence is found // === SETTING TP LEVELS AND ALERTS === if bullishDivergence buySignalPrice = low - atrValue * 0.5 // Entry below the low tp1Buy := buySignalPrice + atrValue * atrMultiplierTP1 tp2Buy := buySignalPrice + atrValue * atrMultiplierTP2 tp3Buy := buySignalPrice + atrValue * atrMultiplierTP3 // Alert for buying signal alert("Hidden Bullish Divergence Detected on " + syminfo.ticker + " - Buy Signal", alert.freq_once_per_bar_close) else tp1Buy := na tp2Buy := na tp3Buy := na if bearishDivergence sellSignalPrice = high + atrValue * 0.5 // Entry above the high tp1Sell := sellSignalPrice - atrValue * atrMultiplierTP1 tp2Sell := sellSignalPrice - atrValue * atrMultiplierTP2 tp3Sell := sellSignalPrice - atrValue * atrMultiplierTP3 // Alert for selling signal alert("Hidden Bearish Divergence Detected on " + syminfo.ticker + " - Sell Signal", alert.freq_once_per_bar_close) else tp1Sell := na tp2Sell := na tp3Sell := na // === PLOTTING SIGNALS AND TAKE PROFITS === // Plotting shapes for buy/sell signals plotshape(bullishDivergence, title="Buy Signal", style=shape.triangleup, location=location.belowbar, color=color.new(color.green, 0), text="Buy", textcolor=color.black) plotshape(bearishDivergence, title="Sell Signal", style=shape.triangledown, location=location.abovebar, color=color.new(color.red, 0), text="Sell", textcolor=color.black) // Plotting take-profit lines plot(tp1Buy, "TP1 Buy", color=color.new(color.lime, 0), style=plot.style_linebr) plot(tp2Buy, "TP2 Buy", color=color.new(color.lime, 0), style=plot.style_linebr) plot(tp3Buy, "TP3 Buy", color=color.new(color.lime, 0), style=plot.style_linebr) plot(tp1Sell, "TP1 Sell", color=color.new(color.orange, 0), style=plot.style_linebr) plot(tp2Sell, "TP2 Sell", color=color.new(color.orange, 0), style=plot.style_linebr) plot(tp3Sell, "TP3 Sell", color=color.new(color.orange, 0), style=plot.style_linebr) // Plotting the RSI and its SMA on a sub-pane plot(rsiValue, "RSI", color.new(color.fuchsia, 0)) plot(rsiSMA, "RSI SMA", color.new(color.yellow, 0)) hline(50, "50 Midline", color=color.new(color.gray, 50)) // Plotting background for signals bullishColor = color.new(color.green, 90) bearishColor = color.new(color.red, 90) bgcolor(bullishDivergence ? bullishColor : na, title="Bullish Divergence Zone") bgcolor(bearishDivergence ? bearishColor : na, title="Bearish Divergence Zone") // === EXPLANATION OF CONCEPTS === // Deep Knowledge of Market from AI: // This indicator is based on a powerful, yet often misunderstood, concept: divergence. // While standard divergence signals a potential trend reversal, hidden divergence signals a // continuation of the prevailing trend. This is crucial for traders who want to capitalize // on the momentum of a move rather than trying to catch tops and bottoms. // Hidden Bullish Divergence: Occurs in an uptrend when price makes a higher low, but the // RSI makes a lower low. This suggests that while there was a brief period of weakness, the // underlying buying pressure is returning to push the trend higher. It’s a "re-energizing" // of the bullish momentum. // Hidden Bearish Divergence: Occurs in a downtrend when price makes a lower high, but the // RSI makes a higher high. This indicates that while the sellers paused, the underlying // selling pressure remains strong and is likely to continue pushing the price down. It's a // subtle signal that the bears are regaining control. // Combining Divergence with S/R: The true power of this indicator comes from its // "confluence" principle. A divergence signal alone can be noisy. By requiring it to occur // at a key support or resistance level (identified using pivot points), we are filtering // out weaker signals and only focusing on high-probability setups where the market is // likely to respect a previous area of interest. This tells us that not only is the trend // likely to continue, but it is doing so from a strategic, well-defined point on the chart. // Dynamic Take-Profit Targets: The take-profit targets are based on the Average True Range (ATR). // ATR is a measure of market volatility. Using it to set targets ensures that your profit // levels are dynamic and adapt to current market conditions. In a volatile market, your // targets will be wider, while in a calm market, they will be tighter, helping you avoid // unrealistic expectations and improving your risk management.
Pine Script® 인디케이터
shunty2731의
ORB + SMA + EMA + BUY/SELL by yuvaraj ORB (Opening Range Breakout) Meaning: ORB stands for Opening Range Breakout. It is a trading strategy where you watch the price movement for the first few minutes after the market opens (for example, 9:15 – 9:30 AM in India). You mark the high and low during this period. If price goes above the high, it signals a possible buy (long trade). If price goes below the low, it signals a possible sell (short trade). Why traders use it: First few minutes decide the market direction. Helps catch early momentum trades. Very popular for intraday traders (Nifty, BankNifty, Crude Oil, etc.). Example: Market opens at 9:15. First 5 minutes: High = 100, Low = 95. If price moves above 100 → Buy. If price moves below 95 → Sell. 📌 SMA (Simple Moving Average) Meaning: SMA stands for Simple Moving Average. It is the average closing price of a stock over a certain number of candles. Example: SMA 9 → Average price of last 9 candles. SMA 50 → Average price of last 50 candles. Why traders use it: Shows trend direction. SMA going up → Uptrend, SMA going down → Downtrend. You can use multiple SMAs (for example SMA 9 and SMA 50): If SMA 9 crosses above SMA 50 → Buy signal. If SMA 9 crosses below SMA 50 → Sell signal. 🔑 Key Difference: Feature ORB SMA Type Strategy (price breakout) Indicator (average price) Use Entry trigger for trades Identifies trend direction Works Best Intraday (first minutes) Any timeframe (intraday or swing) Plots ORB High/Low lines for the first few minutes Plots SMA 9/50/180 & EMA 20 Plots trailing stopline + Buy/Sell arrows Optional bar color / background color toggle Alert conditions for Buy/Sell ORB high/low lines SMA 9/50/180 + EMA 20 Buy/Sell arrows + trailing stopline
Pine Script® 인디케이터
yuvarajvep의
Retail Sentiment Indicator - Multi-Asset CFD & Fear/Greed IndexRetail Sentiment Indicator - Multi-Asset CFD & Fear/Greed Index Overview The Retail Sentiment Indicator provides real-time sentiment data for major financial instruments including stocks, forex, commodities, and cryptocurrencies. This indicator displays retail trader positioning and market sentiment using CFD data and fear/greed indices. Methodology and Scale Calculation This indicator operates on a **-50 to +50 scale** with zero representing perfect market equilibrium. Scale Interpretation: - **Zero (0)**: Market balance - exactly 50% of investors buying, 50% selling - **Positive values**: Majority buying pressure - Example: If 63% of investors are buying, the indicator shows +13 (63 - 50 = +13) - **Negative values**: Majority selling pressure - Example: If 92% of investors are selling, the indicator shows -42 (50 - 92 = -42) BTC Fear & Greed Index Scaling: The original `BTC FEAR&GREED` index is natively scaled from 0-100 by its creator. In our indicator, this data has been rescaled to also fit the -50 to +50 range for consistency with other sentiment data sources. This unified scaling approach allows for direct comparison across all instruments and data sources within the indicator. -Important Data Source Selection- Bitcoin (BTC) Data Sources When viewing Bitcoin charts, the indicator offers **two different data sources**: 1. **Default Auto-Mode**: `BTCUSD Retail CFD` - Retail CFD traders sentiment data (automatically loaded). 2. **Manual Selection**: `BTC FEAR&GREED` - Fear & Greed Index from website: alternative dot me **To access BTC Fear & Greed Index**: Input settings -> disable checkbox "Auto-load Sentiment Data" -> manually select "BTC FEAR&GREED" from the dropdown menu. US Stock Market Data Sources For US stocks and indices (S&P 500, NASDAQ, Dow Jones), there are **two data source options**: 1. **Default Auto-Mode**: Individual retail CFD sentiment data for each instrument 2. **Manual Selection**: `SNN FEAR&GREED` - SNN's Fear & Greed Index covering the overall US market sentiment. SNN was used as the name to avoid any potential trademark infringement. **To access SNN Fear & Greed Index**: When viewing US market charts, disable in input settings checkbox "Auto-load Sentiment Data" and manually select "SNN FEAR&GREED" from the dropdown menu. This distinction allows traders to choose between **instrument-specific retail sentiment** (auto-mode) or **broader market sentiment indices** (manual selection). Features - **Auto-Detection**: Automatically loads sentiment data based on the current chart symbol - **Manual Selection**: Choose from 40+ supported instruments when auto-detection is unavailable - **Multiple Data Sources**: Combines retail CFD sentiment with Fear & Greed indices - **Visual Zones**: Clear greed/fear zones with color-coded backgrounds - **Real-time Updates**: Live sentiment data from merged data sources Supported Instruments Major Indices - S&P 500, NASDAQ, Dow Jones 30, DAX Forex Pairs - Major pairs: EURUSD, GBPUSD, USDJPY, USDCHF, USDCAD - Cross pairs: EURJPY, GBPJPY, AUDUSD, NZDUSD, and 20+ others Commodities - Precious metals: Gold (XAUUSD), Silver (XAGUSD) - Energy: WTI Oil - Agricultural: Wheat, Coffee - Industrial: Copper Cryptocurrencies - Bitcoin (BTC) sentiment data - BTC & SNN Fear & Greed indices How to Use 1. **Auto Mode** (Default): Enable "Auto-load Sentiment Data" to automatically display sentiment for the current chart symbol 2. **Manual Mode**: Disable auto-load and select from the dropdown menu for specific instruments 3. **Interpretation**: - Values above 0 (green) indicate retail greed/bullish sentiment - Values below 0 (red) indicate retail fear/bearish sentiment - Fear & Greed indices use 0-100 scale (50 is neutral) Data Sources This indicator uses curated sentiment data from retail CFD providers and established fear/greed indices. Data is updated regularly and sourced from reputable financial data providers. Trading Strategy & Market Philosophy Contrarian Trading Approach The primary purpose of this indicator is based on the fundamental market principle that **the majority of retail investors are often wrong**, and markets typically move opposite to the positions held by the majority of market participants. Key Strategy Guidelines: - **Contrarian Signal**: When the majority of users are positioned on one side of the market, there is statistically greater market advantage in taking positions in the opposite direction - **Trend Exhaustion Signal**: An interesting observed phenomenon occurs when, during a long-lasting trend where the majority of investors have consistently been on the wrong side, the Sentiment indicator suddenly shows that the majority has flipped and opened positions in the direction of that long-running trend. This is often a signal of fuel exhaustion for further movement in that direction Interpretation Examples - High greed readings (majority bullish) → Consider bearish opportunities - High fear readings (majority bearish) → Consider bullish opportunities - Sudden sentiment flip during established trends → Potential trend reversal signal Technical Notes - Built with PineScript v6 - Dynamic symbol detection with fallback options - Optimized for performance with minimal resource usage - Color-coded visualization with customizable zones Data Sources & Expansion Acknowledgments We extend our gratitude to **TradingView** for enabling the use of custom data feeds based on GitHub repositories, making this comprehensive sentiment analysis possible. Data Expansion Opportunities As the operator of this indicator, I am **open to suggestions for new data sources** that could be integrated and published. If you have ideas for additional instruments or sentiment data: How to Submit Suggestions: 1. Send a **private message** with your proposal 2. Include: **instrument/data type**, **source**, and **brief description** 3. If technically feasible, we will work to import and publish the data Data Infrastructure Status Current Data Upload Process: Please note that sentiment data uploads may occasionally experience minor interruptions. However, this should not pose significant issues as sentiment data typically changes gradually rather than rapidly. Infrastructure Development: We are actively working on establishing permanent cloud-based infrastructure to ensure continuous, automated data collection and upload processes. This will provide more reliable and consistent data availability in the future. Disclaimer This indicator is for educational and informational purposes only. Sentiment data should be used as part of a comprehensive trading strategy and not as the sole basis for trading decisions. Past performance does not guarantee future results. The contrarian approach described is a market theory and may not always produce profitable results.
Pine Script® 인디케이터
OpenTrading_ai의
Volume-Weighted Money Flow [sgbpulse]Overview The VWMF indicator is an advanced technical analysis tool that combines and summarizes five leading momentum and volume indicators (OBV, PVT, A/D, CMF, MFI) into one clear oscillator. The indicator helps to provide a clear picture of market sentiment by measuring the pressure from buyers and sellers. Unlike single indicators, VWMF provides a comprehensive view of market money flow by weighting existing indicators and presenting them in a uniform and understandable format. Indicator Components VWMF combines the following indicators, each normalized to a range of 0 to 100 before being weighted: On-Balance Volume (OBV): A cumulative indicator that measures positive and negative volume flow. Price-Volume Trend (PVT): Similar to OBV, but incorporates relative price change for a more precise measure. Accumulation/Distribution Line (A/D): Used to identify whether an asset is being bought (accumulated) or sold (distributed). Chaikin Money Flow (CMF): Measures the money flow over a period based on the close price's position relative to the candle's range. Money Flow Index (MFI): A momentum oscillator that combines price and volume to measure buying and selling pressure. Understanding the Normalized Oscillators The indicator combines the five different momentum indicators by normalizing each one to a uniform range of 0 to 100 . Why is Normalization Important? Indicators like OBV, PVT, and the A/D Line are cumulative indicators whose values can become very large. To assess their trend, we use a Moving Average as a dynamic reference line . The Moving Average allows us to understand whether the indicator is currently trending up or down relative to its average behavior over time. How Does Normalization Work? Our normalization fully preserves the original trend of each indicator. For Cumulative Indicators (OBV, PVT, A/D): We calculate the difference between the current indicator value and its Moving Average. This difference is then passed to the normalization process. - If the indicator is above its Moving Average, the difference will be positive, and the normalized value will be above 50. - If the indicator is below its Moving Average, the difference will be negative, and the normalized value will be below 50. Handling Extreme Values: To overcome the issue of extreme values in indicators like OBV, PVT, and the A/D Line , the function calculates the highest absolute value over the selected period. This value is used to prevent sharp spikes or drops in a single indicator from compromising the accuracy of the normalization over time. It's a sophisticated method that ensures the oscillators remain relevant and accurate. For Bounded Indicators (CMF, MFI): These indicators already operate within a known range (for example, CMF is between -1 and 1, and MFI is between 0 and 100), so they are normalized directly without an additional reference line. Reference Line Settings: Moving Average Type: Allows the user to choose between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA). Volume Flow MA Length: Allows the user to set the lookback period for the Moving Average, which affects the indicator's sensitivity. The 50 line serves as the new "center line." This ensures that, even after normalization, the determination of whether a specific indicator supports a bullish or bearish trend remains clear. Settings and Visual Tools The indicator offers several customization options to provide a rich analysis experience: VWMF Oscillator (Blue Line): Represents the weighted average of all five indicators. Values above 50 indicate bullish momentum, and values below 50 indicate bearish momentum. Strength Metrics (Bullish/Bearish Strength %): Two metrics that appear on the status line, showing the percentage of indicators supporting the current trend. They range from 0% to 100%, providing a quick view of the strength of the consensus. Dynamic Background Colors: The background color of the chart automatically changes to bullish (a blue shade by default) or bearish (a default brown-gray shade) based on the trend. The transparency of the color shows the consensus strength—the more opaque the background, the more indicators support the trend. Advanced Settings: - Background Color Logic: Allows the user to choose the trigger for the background color: Weighted Value (based on the combined oscillator) or Strength (based on the majority of individual indicators). - Weights: Provides full control over the weight of each of the five indicators in the final oscillator. Using the Data Window TradingView provides a useful Data Window that allows you to see the exact numerical values of each normalized oscillator separately, in addition to the trend strength data. You can use this window to: Get more detailed information on each indicator: Viewing the precise numerical data of each of the five indicators can help in making trading decisions. Calibrate weights: If you want to manually adjust the indicator weights (in the settings menu), you can do so while tracking the impact of each indicator on the weighted oscillator in the Data Window. The indicator's default setting is an equal weight of 20% for each of the five indicators. Alert Conditions The indicator comes with a variety of built-in alerts that can be configured through the TradingView alerts menu: VWMF Cross Above 50: An alert when the VWMF oscillator crosses above the 50 line, indicating a potential bullish momentum shift. VWMF Cross Below 50: An alert when the VWMF oscillator crosses below the 50 line, indicating a potential bearish momentum shift. Bullish Strength: High But Not Absolute Consensus: An alert when the bullish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus. Bullish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bullish strength, indicating a full and absolute consensus. Bearish Strength: High But Not Absolute Consensus: An alert when the bearish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus. Bearish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bearish strength, indicating a full and absolute consensus. Summary The VWMF indicator is a powerful, all-in-one tool for analyzing market momentum, money flow, and sentiment. By combining and normalizing five different indicators into a single oscillator, it offers a holistic and accurate view of the market's underlying trend. Its dynamic visual features and customizable settings, including the ability to adjust indicator weights, provide a flexible experience for both novice and experienced traders. The built-in alerts for momentum shifts and trend consensus make it an effective tool for spotting trading opportunities with confidence. In essence, VWMF distills complex market data into clear, actionable signals. Important Note: Trading Risk This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever. Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Pine Script® 인디케이터
sgbpulse의
log.info() - 5 Exampleslog.info() is one of the most powerful tools in Pine Script that no one knows about. Whenever you code, you want to be able to debug, or find out why something isn’t working. The log.info() command will help you do that. Without it, creating more complex Pine Scripts becomes exponentially more difficult. The first thing to note is that log.info() only displays strings. So, if you have a variable that is not a string, you must turn it into a string in order for log.info() to work. The way you do that is with the str.tostring() command. And remember, it's all lower case! You can throw in any numeric value (float, int, timestamp) into str.string() and it should work. Next, in order to make your output intelligible, you may want to identify whatever value you are logging. For example, if an RSI value is 50, you don’t want a bunch of lines that just say “50”. You may want it to say “RSI = 50”. To do that, you’ll have to use the concatenation operator. For example, if you have a variable called “rsi”, and its value is 50, then you would use the “+” concatenation symbol. EXAMPLE 1 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ //@version=6 indicator("log.info()") rsi = ta.rsi(close,14) log.info(“RSI= ” + str.tostring(rsi)) Example Output =>  RSI= 50 Here, we use double quotes to create a string that contains the name of the variable, in this case “RSI = “, then we concatenate it with a stringified version of the variable, rsi. Now that you know how to write a log, where do you view them? There isn’t a lot of documentation on it, and the link is not conveniently located.  Open up the “Pine Editor” tab at the bottom of any chart view, and you’ll see a “3 dot” button at the top right of the pane. Click that, and right above the “Help” menu item you’ll see “Pine logs”. Clicking that will open  that to open a pane on the right of your browser - replacing whatever was in the right pane area before. This is where your log output will show up.  But, because you’re dealing with time series data, using the log.info() command without some type of condition will give you a fast moving stream of numbers that will be difficult to interpret. So, you may only want the output to show up once per bar, or only under specific conditions.  To have the output show up only after all computations have completed, you’ll need to use the barState.islast command. Remember, barState is camelCase, but islast is not! EXAMPLE 2 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ //@version=6 indicator("log.info()") rsi = ta.rsi(close,14) if barState.islast  log.info("RSI=" + str.tostring(rsi)) plot(rsi) However, this can be less than ideal, because you may want the value of the rsi variable on a particular bar, at a particular time, or under a specific chart condition. Let’s hit these one at a time. In each of these cases, the built-in bar_index variable will come in handy. When debugging, I typically like to assign a variable “bix” to represent bar_index, and include it in the output. So, if I want to see the rsi value when RSI crosses above 0.5, then I would have something like EXAMPLE 3 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ //@version=6 indicator("log.info()") rsi = ta.rsi(close,14) bix = bar_index rsiCrossedOver = ta.crossover(rsi,0.5) if rsiCrossedOver log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi)) plot(rsi) Example Output =>  bix=19964 - RSI=51.8449459867 bix=19972 - RSI=50.0975830828 bix=19983 - RSI=53.3529808079 bix=19985 - RSI=53.1595745146 bix=19999 - RSI=66.6466337654 bix=20001 - RSI=52.2191767466 Here, we see that the output only appears when the condition is met. A useful thing to know is that if you want to limit the number of decimal places, then you would use the command str.tostring(rsi,”#.##”), which tells the interpreter that the format of the number should only be 2 decimal places. Or you could round the rsi variable with a command like rsi2 = math.round(rsi*100)/100 . In either case you’re output would look like: bix=19964 - RSI=51.84 bix=19972 - RSI=50.1 bix=19983 - RSI=53.35 bix=19985 - RSI=53.16 bix=19999 - RSI=66.65 bix=20001 - RSI=52.22 This would decrease the amount of memory that’s being used to display your variable’s values, which can become a limitation for the log.info() command. It only allows 4096 characters per line, so when you get to trying to output arrays (which is another cool feature), you’ll have to keep that in mind. Another thing to note is that log output is always preceded by a timestamp, but for the sake of brevity, I’m not including those in the output examples. If you wanted to only output a value after the chart was fully loaded, that’s when barState.islast command comes in. Under this condition, only one line of output is created per tick update — AFTER the chart has finished loading. For example, if you only want to see what the the current bar_index and rsi values are, without filling up your log window with everything that happens before, then you could use the following code: EXAMPLE 4 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ //@version=6 indicator("log.info()") rsi = ta.rsi(close,14) bix = bar_index if barstate.islast log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi)) Example Output => bix=20203 - RSI=53.1103309071 This value would keep updating after every new bar tick. The log.info() command is a huge help in creating new scripts, however, it does have its limitations. As mentioned earlier, only 4096 characters are allowed per line. So, although you can use log.info() to output arrays, you have to be aware of how many characters that array will use. The following code DOES NOT WORK! And, the only way you can find out why will be the red exclamation point next to the name of the indicator. That, and nothing will show up on the chart, or in the logs. // CODE DOESN’T WORK //@version=6 indicator("MW - log.info()") var array rsi_arr = array.new() rsi = ta.rsi(close,14) bix = bar_index rsiCrossedOver = ta.crossover(rsi,50)  if rsiCrossedOver     array.push(rsi_arr, rsi) if barstate.islast     log.info("rsi_arr:" + str.tostring(rsi_arr))     log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi)) plot(rsi) // No code errors, but will not compile because too much is being written to the logs. However, after putting some time restrictions in with the i_startTime and i_endTime user input variables, and creating a dateFilter variable to use in the conditions, I can limit the size of the final array. So, the following code does work. EXAMPLE 5 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ // CODE DOES WORK //@version=6 indicator("MW - log.info()") i_startTime         = input.time(title="Start", defval=timestamp("01 Jan 2025 13:30 +0000")) i_endTime           = input.time(title="End", defval=timestamp("1 Jan 2099 19:30 +0000")) var array rsi_arr = array.new() dateFilter = time >= i_startTime and time <= i_endTime  rsi = ta.rsi(close,14) bix = bar_index rsiCrossedOver = ta.crossover(rsi,50) and dateFilter // <== The dateFilter condition keeps the array from getting too big if rsiCrossedOver     array.push(rsi_arr, rsi) if barstate.islast     log.info("rsi_arr:" + str.tostring(rsi_arr))     log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi)) plot(rsi) Example Output => rsi_arr: bix=20210 - RSI=56.9030578034 Of course, if you restrict the decimal places by using the rounding the rsi value with something like rsiRounded = math.round(rsi * 100) / 100 , then you can further reduce the size of your array. In this case the output may look something like: Example Output => rsi_arr: bix=20210 - RSI=55.6947486019 This will give your code a little breathing room. In a nutshell, I was coding for over a year trying to debug by pushing output to labels, tables, and using libraries that cluttered up my code. Once I was able to debug with log.info() it was a game changer. I was able to start building much more advanced scripts. Hopefully, this will help you on your journey as well.
Pine Script® 인디케이터
mwrightinc의
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE) ## Advanced Multi-Dimensional Mathematical Analysis System *Where Quantum Mathematics Meets Market Structure* --- ## 🎓 THEORETICAL FOUNDATION The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry. ### 🌊 Multi-Dimensional Volatility with Jump Detection **Hawkes Process Implementation:** The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects. **Mathematical Foundation:** ``` Intensity λ(t) = μ + Σ α(t - Tᵢ) ``` Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99). **Mahalanobis Distance Calculation:** The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions: - **Dimension 1:** Price volatility (standard deviation of returns) - **Dimension 2:** Volume volatility (normalized volume fluctuations) - **Dimension 3:** Range volatility (high-low spread variations) - **Dimension 4:** Correlation volatility (price-volume relationship changes) - **Dimension 5:** Microstructure volatility (intrabar positioning analysis) This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches. ### 📐 Hurst Exponent Regime Detection **Fractal Market Hypothesis Integration:** The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification: - **H > 0.6:** Trending (persistent) markets - momentum strategies optimal - **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal - **H ≈ 0.5:** Random walk markets - breakout strategies preferred **Adaptive R/S Analysis:** Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions: ``` H = log(R/S) / log(n) ``` Where R is the range of cumulative deviations and S is the standard deviation over period n. **Dynamic Regime Classification:** The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods. ### 🔄 Transfer Entropy Analysis **Information Flow Quantification:** Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements: ``` TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log ``` **Causality Detection:** - **Volume → Price:** Indicates accumulation/distribution phases - **Price → Volume:** Suggests retail participation or momentum chasing - **Balanced Flow:** Market equilibrium or transition periods The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows. --- ## 🔧 COMPREHENSIVE INPUT SYSTEM ### Core Parameters Group **Primary Analysis Window (10-100, Default: 50)** The fundamental lookback period affecting all calculations. Optimization by timeframe: - **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements) - **15 minute-1 hour:** 30-50 (balanced responsiveness and stability) - **4 hour-daily:** 50-100 (smooth signals, reduced noise) - **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60 **Signal Sensitivity (0.1-2.0, Default: 0.7)** Master control affecting all threshold calculations: - **Conservative (0.3-0.6):** High-quality signals only, fewer false positives - **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles - **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering **Signal Generation Mode:** - **Aggressive:** Any component signals (highest frequency) - **Confluence:** 2+ components agree (balanced approach) - **Conservative:** All 3 components align (highest quality) ### Volatility Jump Detection Group **Volatility Dimensions (2-5, Default: 3)** Determines the mathematical space complexity: - **2D:** Price + Volume volatility (suitable for clean markets) - **3D:** + Range volatility (optimal for most conditions) - **4D:** + Correlation volatility (advanced multi-asset analysis) - **5D:** + Microstructure volatility (maximum sensitivity) **Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)** Standard deviations required for volatility jump classification: - **Cryptocurrency:** 2.0-2.5σ (naturally volatile) - **Stock Indices:** 2.5-3.0σ (moderate volatility) - **Forex Major Pairs:** 3.0-3.5σ (typically stable) - **Commodities:** 2.0-3.0σ (varies by commodity) **Jump Clustering Decay (0.5-0.99, Default: 0.85)** Hawkes process memory parameter: - **0.5-0.7:** Fast decay (jumps treated as independent) - **0.8-0.9:** Moderate clustering (realistic market behavior) - **0.95-0.99:** Strong clustering (crisis/event-driven markets) ### Hurst Exponent Analysis Group **Calculation Method Options:** - **Classic R/S:** Original Rescaled Range (fast, simple) - **Adaptive R/S:** Dynamic windowing (recommended for trading) - **DFA:** Detrended Fluctuation Analysis (best for noisy data) **Trending Threshold (0.55-0.8, Default: 0.60)** Hurst value defining persistent market behavior: - **0.55-0.60:** Weak trend persistence - **0.65-0.70:** Clear trending behavior - **0.75-0.80:** Strong momentum regimes **Mean Reversion Threshold (0.2-0.45, Default: 0.40)** Hurst value defining anti-persistent behavior: - **0.35-0.45:** Weak mean reversion - **0.25-0.35:** Clear ranging behavior - **0.15-0.25:** Strong reversion tendency ### Transfer Entropy Parameters Group **Information Flow Analysis:** - **Price-Volume:** Classic flow analysis for accumulation/distribution - **Price-Volatility:** Risk flow analysis for sentiment shifts - **Multi-Timeframe:** Cross-timeframe causality detection **Maximum Lag (2-20, Default: 5)** Causality detection window: - **2-5 bars:** Immediate causality (scalping) - **5-10 bars:** Short-term flow (day trading) - **10-20 bars:** Structural flow (swing trading) **Significance Threshold (0.05-0.3, Default: 0.15)** Minimum entropy for signal generation: - **0.05-0.10:** Detect subtle information flows - **0.10-0.20:** Clear causality only - **0.20-0.30:** Very strong flows only --- ## 🎨 ADVANCED VISUAL SYSTEM ### Tensor Volatility Field Visualization **Five-Layer Resonance Bands:** The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength: - **Core Layer (Purple):** Primary tensor field with highest intensity - **Layer 2 (Neutral):** Secondary mathematical resonance - **Layer 3 (Info Blue):** Tertiary harmonic frequencies - **Layer 4 (Warning Gold):** Outer field boundaries - **Layer 5 (Success Green):** Maximum field extension **Field Strength Calculation:** ``` Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity) ``` The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility. **Radiation Line Network:** During active tensor states, the system projects directional radiation lines showing field energy distribution: - **8 Directional Rays:** Complete angular coverage - **Tapering Segments:** Progressive transparency for natural visual flow - **Pulse Effects:** Enhanced visualization during volatility jumps ### Dimensional Portal System **Portal Mathematics:** Dimensional portals visualize regime transitions using category theory principles: - **Green Portals (◉):** Trending regime detection (appear below price for support) - **Red Portals (◎):** Mean-reverting regime (appear above price for resistance) - **Yellow Portals (○):** Random walk regime (neutral positioning) **Tensor Trail Effects:** Each portal generates 8 trailing particles showing mathematical momentum: - **Large Particles (●):** Strong mathematical signal - **Medium Particles (◦):** Moderate signal strength - **Small Particles (·):** Weak signal continuation - **Micro Particles (˙):** Signal dissipation ### Information Flow Streams **Particle Stream Visualization:** Transfer entropy creates flowing particle streams indicating information direction: - **Upward Streams:** Volume leading price (accumulation phases) - **Downward Streams:** Price leading volume (distribution phases) - **Stream Density:** Proportional to information flow strength **15-Particle Evolution:** Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent. ### Fractal Matrix Grid System **Multi-Timeframe Fractal Levels:** The system calculates and displays fractal highs/lows across five Fibonacci periods: - **8-Period:** Short-term fractal structure - **13-Period:** Intermediate-term patterns - **21-Period:** Primary swing levels - **34-Period:** Major structural levels - **55-Period:** Long-term fractal boundaries **Triple-Layer Visualization:** Each fractal level uses three-layer rendering: - **Shadow Layer:** Widest, darkest foundation (width 5) - **Glow Layer:** Medium white core line (width 3) - **Tensor Layer:** Dotted mathematical overlay (width 1) **Intelligent Labeling System:** Smart spacing prevents label overlap using ATR-based minimum distances. Labels include: - **Fractal Period:** Time-based identification - **Topological Class:** Mathematical complexity rating (0, I, II, III) - **Price Level:** Exact fractal price - **Mahalanobis Distance:** Current mathematical field strength - **Hurst Exponent:** Current regime classification - **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡) ### Wick Pressure Analysis **Rejection Level Mathematics:** The system analyzes candle wick patterns to project future pressure zones: - **Upper Wick Analysis:** Identifies selling pressure and resistance zones - **Lower Wick Analysis:** Identifies buying pressure and support zones - **Pressure Projection:** Extends lines forward based on mathematical probability **Multi-Layer Glow Effects:** Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart. ### Enhanced Regime Background **Dynamic Intensity Mapping:** Background colors reflect mathematical regime strength: - **Deep Transparency (98% alpha):** Subtle regime indication - **Pulse Intensity:** Based on regime strength calculation - **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random) **Smoothing Integration:** Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts. ### Color Scheme System **Six Professional Themes:** - **Dark (Default):** Professional trading environment optimization - **Light:** High ambient light conditions - **Classic:** Traditional technical analysis appearance - **Neon:** High-contrast visibility for active trading - **Neutral:** Minimal distraction focus - **Bright:** Maximum visibility for complex setups Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences. --- ## 📊 INSTITUTIONAL-GRADE DASHBOARD ### Tensor Field Status Section **Field Strength Display:** Real-time Mahalanobis distance calculation with dynamic emoji indicators: - **⚡ (Lightning):** Extreme field strength (>1.5× threshold) - **● (Solid Circle):** Strong field activity (>1.0× threshold) - **○ (Open Circle):** Normal field state **Signal Quality Rating:** Democratic algorithm assessment: - **ELITE:** All 3 components aligned (highest probability) - **STRONG:** 2 components aligned (good probability) - **GOOD:** 1 component active (moderate probability) - **WEAK:** No clear component signals **Threshold and Anomaly Monitoring:** - **Threshold Display:** Current mathematical threshold setting - **Anomaly Level (0-100%):** Combined volatility and volume spike measurement - **>70%:** High anomaly (red warning) - **30-70%:** Moderate anomaly (orange caution) - **<30%:** Normal conditions (green confirmation) ### Tensor State Analysis Section **Mathematical State Classification:** - **↑ BULL (Tensor State +1):** Trending regime with bullish bias - **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias - **◈ SUPER (Tensor State 0):** Random walk regime (neutral) **Visual State Gauge:** Five-circle progression showing tensor field polarity: - **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment - **⚪⚪🟡⚪⚪:** Neutral/transitional state - **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment **Trend Direction and Phase Analysis:** - **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification - **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength) - **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength) - **😴 CALM:** Low information flow (<1.0 flow strength) ### Trading Signals Section **Real-Time Signal Status:** - **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability - **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability - **Components (X/3):** Active algorithmic components - **Mode Display:** Current signal generation mode **Signal Strength Visualization:** Color-coded component count: - **Green:** 3/3 components (maximum confidence) - **Aqua:** 2/3 components (good confidence) - **Orange:** 1/3 components (moderate confidence) - **Gray:** 0/3 components (no signals) ### Performance Metrics Section **Win Rate Monitoring:** Estimated win rates based on signal quality with emoji indicators: - **🔥 (Fire):** ≥60% estimated win rate - **👍 (Thumbs Up):** 45-59% estimated win rate - **⚠️ (Warning):** <45% estimated win rate **Mathematical Metrics:** - **Hurst Exponent:** Real-time fractal dimension (0.000-1.000) - **Information Flow:** Volume/price leading indicators - **📊 VOL:** Volume leading price (accumulation/distribution) - **💰 PRICE:** Price leading volume (momentum/speculation) - **➖ NONE:** Balanced information flow - **Volatility Classification:** - **🔥 HIGH:** Above 1.5× jump threshold - **📊 NORM:** Normal volatility range - **😴 LOW:** Below 0.5× jump threshold ### Market Structure Section (Large Dashboard) **Regime Classification:** - **📈 TREND:** Hurst >0.6, momentum strategies optimal - **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal - **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred **Mathematical Field Analysis:** - **Dimensions:** Current volatility space complexity (2D-5D) - **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00) - **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal) ### Settings Summary Section (Large Dashboard) **Active Configuration Display:** - **Sensitivity:** Current master sensitivity setting - **Lookback:** Primary analysis window - **Theme:** Active color scheme - **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA) **Dashboard Sizing Options:** - **Small:** Essential metrics only (mobile/small screens) - **Normal:** Balanced information density (standard desktop) - **Large:** Maximum detail (multi-monitor setups) **Position Options:** - **Top Right:** Standard placement (avoids price action) - **Top Left:** Wide chart optimization - **Bottom Right:** Recent price focus (scalping) - **Bottom Left:** Maximum price visibility (swing trading) --- ## 🎯 SIGNAL GENERATION LOGIC ### Multi-Component Convergence System **Component Signal Architecture:** The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing: **Volatility Component:** - **Jump Detection:** Mahalanobis distance threshold breach - **Hawkes Intensity:** Self-exciting process activation (>0.2) - **Multi-dimensional:** Considers all volatility dimensions simultaneously **Hurst Regime Component:** - **Trending Markets:** Price above SMA-20 with positive momentum - **Mean-Reverting Markets:** Price at Bollinger Band extremes - **Random Markets:** Bollinger squeeze breakouts with directional confirmation **Transfer Entropy Component:** - **Volume Leadership:** Information flow from volume to price - **Volume Spike:** Volume 110%+ above 20-period average - **Flow Significance:** Above entropy threshold with directional bias ### Democratic Signal Weighting **Signal Mode Implementation:** - **Aggressive Mode:** Any single component triggers signal - **Confluence Mode:** Minimum 2 components must agree - **Conservative Mode:** All 3 components must align **Momentum Confirmation:** All signals require momentum confirmation: - **Long Signals:** RSI >50 AND price >EMA-9 - **Short Signals:** RSI <50 AND price 0.6):** - **Increase Sensitivity:** Catch momentum continuation - **Lower Mean Reversion Threshold:** Avoid counter-trend signals - **Emphasize Volume Leadership:** Institutional accumulation/distribution - **Tensor Field Focus:** Use expansion for trend continuation - **Signal Mode:** Aggressive or Confluence for trend following **Range-Bound Markets (Hurst <0.4):** - **Decrease Sensitivity:** Avoid false breakouts - **Lower Trending Threshold:** Quick regime recognition - **Focus on Price Leadership:** Retail sentiment extremes - **Fractal Grid Emphasis:** Support/resistance trading - **Signal Mode:** Conservative for high-probability reversals **Volatile Markets (High Jump Frequency):** - **Increase Hawkes Decay:** Recognize event clustering - **Higher Jump Threshold:** Avoid noise signals - **Maximum Dimensions:** Capture full volatility complexity - **Reduce Position Sizing:** Risk management adaptation - **Enhanced Visuals:** Maximum information for rapid decisions **Low Volatility Markets (Low Jump Frequency):** - **Decrease Jump Threshold:** Capture subtle movements - **Lower Hawkes Decay:** Treat moves as independent - **Reduce Dimensions:** Simplify analysis - **Increase Position Sizing:** Capitalize on compressed volatility - **Minimal Visuals:** Reduce distraction in quiet markets --- ## 🚀 ADVANCED TRADING STRATEGIES ### The Mathematical Convergence Method **Entry Protocol:** 1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels 2. **Tensor Field Confirmation:** Verify field expansion supporting direction 3. **Portal Signal:** Wait for dimensional portal appearance 4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals 5. **Component Consensus:** Confirm 2+ components agree in Confluence mode **Example Implementation:** - Price approaching 21-period fractal high - Tensor field expanding upward (bullish mathematical alignment) - Green portal appears below price (trending regime confirmation) - ELITE quality signal with 3/3 components active - Enter long position with stop below fractal level **Risk Management:** - **Stop Placement:** Below/above fractal level that generated signal - **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size) - **Profit Targets:** Next fractal level or tensor field resistance ### The Regime Transition Strategy **Regime Change Detection:** 1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds 2. **Portal Color Change:** Regime transitions show different portal colors 3. **Background Intensity:** Increasing regime background intensity 4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis) **Trading Implementation:** - **Trending Transitions:** Trade momentum breakouts, follow trend - **Mean Reversion Transitions:** Trade range boundaries, fade extremes - **Random Transitions:** Trade breakouts with tight stops **Advanced Techniques:** - **Multi-Timeframe:** Confirm regime on higher timeframe - **Early Entry:** Enter on regime transition rather than confirmation - **Regime Strength:** Larger positions during strong regime signals ### The Information Flow Momentum Strategy **Flow Detection Protocol:** 1. **Monitor Transfer Entropy:** Watch for significant information flow shifts 2. **Volume Leadership:** Strong edge when volume leads price 3. **Flow Acceleration:** Increasing flow strength indicates momentum 4. **Directional Confirmation:** Ensure flow aligns with intended trade direction **Entry Signals:** - **Volume → Price Flow:** Enter during accumulation/distribution phases - **Price → Volume Flow:** Enter on momentum confirmation breaks - **Flow Reversal:** Counter-trend entries when flow reverses **Optimization:** - **Scalping:** Use immediate flow detection (2-5 bar lag) - **Swing Trading:** Use structural flow (10-20 bar lag) - **Multi-Asset:** Compare flow between correlated assets ### The Tensor Field Expansion Strategy **Field Mathematics:** The tensor field expansion indicates mathematical pressure building in market structure: **Expansion Phases:** 1. **Compression:** Field contracts, volatility decreases 2. **Tension Building:** Mathematical pressure accumulates 3. **Expansion:** Field expands rapidly with directional movement 4. **Resolution:** Field stabilizes at new equilibrium **Trading Applications:** - **Compression Trading:** Prepare for breakout during field contraction - **Expansion Following:** Trade direction of field expansion - **Reversion Trading:** Fade extreme field expansion - **Multi-Dimensional:** Consider all field layers for confirmation ### The Hawkes Process Event Strategy **Self-Exciting Jump Trading:** Understanding that market shocks cluster and create follow-on opportunities: **Jump Sequence Analysis:** 1. **Initial Jump:** First volatility jump detected 2. **Clustering Phase:** Hawkes intensity remains elevated 3. **Follow-On Opportunities:** Additional jumps more likely 4. **Decay Period:** Intensity gradually decreases **Implementation:** - **Jump Confirmation:** Wait for mathematical jump confirmation - **Direction Assessment:** Use other components for direction - **Clustering Trades:** Trade subsequent moves during high intensity - **Decay Exit:** Exit positions as Hawkes intensity decays ### The Fractal Confluence System **Multi-Timeframe Fractal Analysis:** Combining fractal levels across different periods for high-probability zones: **Confluence Zones:** - **Double Confluence:** 2 fractal levels align - **Triple Confluence:** 3+ fractal levels cluster - **Mathematical Confirmation:** Tensor field supports the level - **Information Flow:** Transfer entropy confirms direction **Trading Protocol:** 1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR 2. **Mathematical Support:** Verify tensor field alignment 3. **Signal Quality:** Wait for STRONG or ELITE signal 4. **Risk Definition:** Use fractal level for stop placement 5. **Profit Targeting:** Next major fractal confluence zone --- ## ⚠️ COMPREHENSIVE RISK MANAGEMENT ### Mathematical Position Sizing **Mahalanobis Distance Integration:** Position size should inversely correlate with mathematical field strength: ``` Position Size = Base Size × (Threshold / Mahalanobis Distance) ``` **Risk Scaling Matrix:** - **Low Field Strength (<2.0):** Standard position sizing - **Moderate Field Strength (2.0-3.0):** 75% position sizing - **High Field Strength (3.0-4.0):** 50% position sizing - **Extreme Field Strength (>4.0):** 25% position sizing or no trade ### Signal Quality Risk Adjustment **Quality-Based Position Sizing:** - **ELITE Signals:** 100% of planned position size - **STRONG Signals:** 75% of planned position size - **GOOD Signals:** 50% of planned position size - **WEAK Signals:** No position or paper trading only **Component Agreement Scaling:** - **3/3 Components:** Full position size - **2/3 Components:** 75% position size - **1/3 Components:** 50% position size or skip trade ### Regime-Adaptive Risk Management **Trending Market Risk:** - **Wider Stops:** Allow for trend continuation - **Trend Following:** Trade with regime direction - **Higher Position Size:** Trend probability advantage - **Momentum Stops:** Trail stops based on momentum indicators **Mean-Reverting Market Risk:** - **Tighter Stops:** Quick exits on trend continuation - **Contrarian Positioning:** Trade against extremes - **Smaller Position Size:** Higher reversal failure rate - **Level-Based Stops:** Use fractal levels for stops **Random Market Risk:** - **Breakout Focus:** Trade only clear breakouts - **Tight Initial Stops:** Quick exit if breakout fails - **Reduced Frequency:** Skip marginal setups - **Range-Based Targets:** Profit targets at range boundaries ### Volatility-Adaptive Risk Controls **High Volatility Periods:** - **Reduced Position Size:** Account for wider price swings - **Wider Stops:** Avoid noise-based exits - **Lower Frequency:** Skip marginal setups - **Faster Exits:** Take profits more quickly **Low Volatility Periods:** - **Standard Position Size:** Normal risk parameters - **Tighter Stops:** Take advantage of compressed ranges - **Higher Frequency:** Trade more setups - **Extended Targets:** Allow for compressed volatility expansion ### Multi-Timeframe Risk Alignment **Higher Timeframe Trend:** - **With Trend:** Standard or increased position size - **Against Trend:** Reduced position size or skip - **Neutral Trend:** Standard position size with tight management **Risk Hierarchy:** 1. **Primary:** Current timeframe signal quality 2. **Secondary:** Higher timeframe trend alignment 3. **Tertiary:** Mathematical field strength 4. **Quaternary:** Market regime classification --- ## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS ### Advanced Mathematical Concepts **Tensor Analysis in Markets:** The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture. **Information Theory Applications:** Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior. **Fractal Geometry in Trading:** The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure. **Stochastic Process Theory:** The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects. ### Learning Progressive Complexity **Beginner Mathematical Concepts:** - **Volatility Dimensions:** Understanding multi-dimensional analysis - **Regime Classification:** Learning market personality types - **Signal Democracy:** Algorithmic consensus building - **Visual Mathematics:** Interpreting mathematical concepts visually **Intermediate Mathematical Applications:** - **Mahalanobis Distance:** Statistical distance in multi-dimensional space - **Rescaled Range Analysis:** Fractal dimension measurement - **Information Entropy:** Quantifying uncertainty and causality - **Field Theory:** Understanding mathematical fields in market context **Advanced Mathematical Integration:** - **Tensor Field Dynamics:** Multi-dimensional market force analysis - **Stochastic Self-Excitation:** Event clustering and memory effects - **Categorical Composition:** Mathematical signal combination theory - **Topological Market Analysis:** Understanding market shape and connectivity ### Practical Mathematical Intuition **Developing Market Mathematics Intuition:** The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of: - **How markets exhibit mathematical structure beneath apparent randomness** - **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches** - **How information flows through markets in measurable, predictable ways** - **Why mathematical models provide probabilistic edges rather than certainties** --- ## 🔬 IMPLEMENTATION AND OPTIMIZATION ### Getting Started Protocol **Phase 1: Observation (Week 1)** 1. **Apply with defaults:** Use standard settings on your primary trading timeframe 2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams 3. **Monitor dashboard:** Observe how metrics change with market conditions 4. **No trading:** Focus entirely on pattern recognition and understanding **Phase 2: Pattern Recognition (Week 2-3)** 1. **Identify signal patterns:** Note what market conditions produce different signal qualities 2. **Regime correlation:** Observe how Hurst regimes affect signal performance 3. **Visual confirmation:** Learn to read tensor field expansion and portal signals 4. **Component analysis:** Understand which components drive signals in different markets **Phase 3: Parameter Optimization (Week 4-5)** 1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument 2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe 3. **Sensitivity adjustment:** Balance signal frequency with quality 4. **Visual customization:** Optimize colors and intensity for your trading environment **Phase 4: Live Implementation (Week 6+)** 1. **Paper trading:** Test signals with hypothetical trades 2. **Small position sizing:** Begin with minimal risk during learning phase 3. **Performance tracking:** Monitor actual vs. expected signal performance 4. **Continuous optimization:** Refine settings based on real performance data ### Performance Monitoring System **Signal Quality Tracking:** - **ELITE Signal Win Rate:** Track highest quality signals separately - **Component Performance:** Monitor which components provide best signals - **Regime Performance:** Analyze performance across different market regimes - **Timeframe Analysis:** Compare performance across different session times **Mathematical Metric Correlation:** - **Field Strength vs. Performance:** Higher field strength should correlate with better performance - **Component Agreement vs. Win Rate:** More component agreement should improve win rates - **Regime Alignment vs. Success:** Trading with mathematical regime should outperform ### Continuous Optimization Process **Monthly Review Protocol:** 1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown 2. **Parameter Assessment:** Evaluate if current settings remain optimal 3. **Market Adaptation:** Adjust for changes in market character or volatility 4. **Component Weighting:** Consider if certain components should receive more/less emphasis **Quarterly Deep Analysis:** 1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid 2. **Regime Distribution:** Analyze time spent in different market regimes 3. **Signal Evolution:** Track how signal characteristics change over time 4. **Correlation Analysis:** Monitor correlations between different mathematical components --- ## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS ### Revolutionary Mathematical Integration **First-Ever Implementations:** 1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility 2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes 3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation 4. **Democratic Component Voting:** First algorithmic consensus system for signal generation 5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels ### Advanced Visualization Innovations **Mathematical Visualization Breakthroughs:** - **Tensor Field Radiation:** Visual representation of mathematical field energy - **Dimensional Portal System:** Category theory visualization for regime transitions - **Information Flow Streams:** Real-time visual display of market information transfer - **Multi-Layer Fractal Grid:** Intelligent spacing and projection system - **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength ### Practical Trading Innovations **Trading System Advances:** - **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence - **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality - **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering - **Component Performance Tracking:** Real-time monitoring of algorithmic component success - **Field-Strength Position Sizing:** Mathematical volatility integration for risk management --- ## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS ### Mathematical Model Limitations **Understanding Model Boundaries:** While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations: - **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements - **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely - **Model Risk:** Complex models can fail during unprecedented market conditions - **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions ### Proper Implementation Guidelines **Risk Management Requirements:** - **Never Risk More Than 2% Per Trade:** Regardless of signal quality - **Diversification Mandatory:** Don't rely solely on mathematical signals - **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence - **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters **Realistic Expectations:** - **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes - **Learning Curve Required:** Complex mathematical concepts require time to master - **Market Adaptation Necessary:** Parameters must evolve with changing market conditions - **Continuous Education Important:** Understanding underlying mathematics improves application ### Ethical Trading Considerations **Market Impact Awareness:** - **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants - **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure - **Sharing Knowledge:** Consider educational contributions to trading community - **Fair Market Participation:** Use mathematical advantages responsibly within market framework ### Professional Development Path **Skill Development Sequence:** 1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application 2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals 3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights 4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution --- ## 🔮 CONCLUSION The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability. ### Mathematical Innovation Legacy This indicator establishes new paradigms in technical analysis: - **Tensor analysis for market volatility understanding** - **Stochastic self-excitation for event clustering prediction** - **Information theory for causality-based trade generation** - **Democratic algorithmic consensus for signal quality enhancement** - **Mathematical field visualization for intuitive market understanding** ### Practical Trading Revolution Beyond mathematical innovation, the TMAE transforms practical trading: - **Quality-rated signals replace binary buy/sell decisions** - **Regime-adaptive strategies automatically optimize for market personality** - **Multi-dimensional risk management integrates mathematical volatility measures** - **Visual mathematical concepts make complex analysis immediately interpretable** - **Educational value creates lasting improvement in trading understanding** ### Future-Proof Design The mathematical foundations ensure lasting relevance: - **Universal mathematical principles transcend market evolution** - **Multi-dimensional analysis adapts to new market structures** - **Regime detection automatically adjusts to changing market personalities** - **Component democracy allows for future algorithmic additions** - **Mathematical visualization scales with increasing market complexity** ### Commitment to Excellence The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value. ### Trading with Mathematical Precision In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals. By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics. ### Final Perspective Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure. Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior. Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE. *"In mathematics, you don't understand things. You just get used to them." - John von Neumann* *With the TMAE, mathematical market understanding becomes not just possible, but intuitive.* — Dskyz, Trade with insight. Trade with anticipation.
Pine Script® 인디케이터
DskyzInvestments의
16
Percent Change of Range Candles - FullPercent Change of Range Candles – Full (PCR Full) Description: PCR Full is a custom momentum indicator that measures the percentage price change relative to a defined range, offering traders a unique way to evaluate strength, direction, and potential reversals in price movement. How it works: The main value (PCR) is calculated by comparing the price change over a selected number of candles (length) to the range between the highest high and lowest low in the same period. This percentage change is normalized and visualized with dynamic candles on the subgraph. Reference levels at +100, +50, 0, -50, and -100 serve as key zones to indicate potential overbought/oversold conditions, continuation, or neutrality. How to read the indicator: 1. Trend continuation: When PCR breaks above +50 and holds, it often confirms a strong bullish move. Similarly, values below -50 and staying low signal a bearish continuation. 2. Wick behavior (volatility insight): Long wicks on PCR candles suggest uncertainty or failed breakout attempts. Short or no wicks with strong body color show stable momentum and conviction. On the chart, multiple long wicks near -50 suggest bulls are attempting to push price upward, but lack the strength — until a confirmed breakout. 3. Polarity transition (Bearish to Bullish or vice versa): A transition from negative PCR values to above zero shows that the market is possibly turning. Especially if PCR climbs gradually and stabilizes above zero, it indicates a developing bullish phase. Components: Main PCR line: Color-coded (green for rising, red for falling). Open Average (gray line): Smooths recent PCR values, indicating balance. High/Low adaptive bands: Adjust dynamically to PCR polarity. PCR Candles: Visualize OHLC of PCR data for enhanced interpretation. Suggested use cases: Enter trend trades when PCR crosses +50 or -50 with volume or price confirmation. Watch for reversal signs near ±100 if PCR fails to break further. Use 0 line as a neutral zone — markets hovering near 0 are often in consolidation. Combine with price action or oscillators like RSI/MACD for additional signals. Customization: The length input allows users to define the range for PCR calculations, making it adjustable to various timeframes and strategies (scalping, intraday, swing).
Pine Script® 인디케이터
Aleksin_Aleksandar의
Canuck Trading Projection IndicatorCanuck Trading Projection Indicator Overview The Canuck Trading Projection Indicator is a powerful PineScript v6 tool designed for TradingView to project potential bullish and bearish price trajectories based on historical price and volume movements. It provides traders with actionable insights by estimating future price targets and assigning confidence levels to each outlook, helping to identify probable market directions across any timeframe. Ideal for both short-term and long-term traders, this indicator combines momentum analysis, RSI filtering, support/resistance detection, and time-weighted trend analysis to deliver robust projections. Features Bullish and Bearish Projections: Forecasts price targets for upward (bullish) and downward (bearish) movements over a user-defined projection period (default 20 bars). Confidence Levels: Assigns percentage confidence scores to each outlook, reflecting the likelihood of the projected price based on historical trends, volatility, and volume. RSI Filter: Incorporates a 14-period Relative Strength Index (RSI) to validate trends, requiring RSI > 50 for bullish and RSI < 50 for bearish signals. Support/Resistance Detection: Adjusts confidence levels when projections are near key swing highs/lows (within 2% of average price), boosting confidence by 5% for alignments. Time-Based Weighting: Prioritizes recent price movements in trend analysis, giving more weight to newer bars for improved relevance. Customizable Inputs: Allows users to tailor lookback period, projection bars, RSI period, confidence threshold, colors, and label positioning. Forced Label Spacing: Prevents overlap of bullish and bearish text labels, even for tight projections, using fixed vertical slots when price differences are small (<2% of average price). Timeframe Flexibility: Works seamlessly across all TradingView timeframes (e.g., 30-minute, hourly, daily, weekly, monthly), adapting projections to the chart’s resolution. Clean Visualization: Displays projections as green (bullish) and red (bearish) dashed lines, with non-overlapping text labels at the projection endpoints showing price targets and confidence levels. How It Works The indicator analyzes historical price and volume data over a user-defined lookback period (default 50 bars) to calculate: Momentum: Combines price changes and volume to assess trend strength, using a weighted moving average (WMA) for directional bias. Trend Analysis: Counts bullish (price up, volume above average, RSI > 50) and bearish (price down, volume above average, RSI < 50) trends, weighting recent bars more heavily. Projections: Bullish Slope: Positive or flat when momentum is upward, scaled by price change and momentum intensity. Bearish Slope: Negative or flat when momentum is downward, amplified by bearish confidence for stronger projections. Projects prices forward by 20 bars (default) using current close plus slope times projection bars. Confidence Levels: Base confidence derived from the proportion of bullish/bearish trends, with a 5% minimum to avoid zero confidence. Adjusted by volatility (lower volatility increases confidence), volume trends, and proximity to support/resistance levels. Visualization: Draws projection lines from the current close to the 20-bar future target. Places text labels at line endpoints, showing price targets and confidence percentages, with forced spacing for readability. Input Parameters Lookback Period (default: 50): Number of bars for historical analysis (minimum 10). Projection Bars (default: 20): Number of bars to project forward (minimum 5). Confidence Threshold (default: 0.6): Minimum confidence for strong trend indication (0.1 to 1.0). Bullish Projection Line Color (default: Green): Color for bullish projection line and label. Bearish Projection Line Color (default: Red): Color for bearish projection line and label. RSI Period (default: 14): Period for RSI momentum filter (minimum 5). Label Vertical Offset (%) (default: 1.0): Base offset for labels as a percentage of price range (0.1% to 5.0%). Minimum Label Spacing (%) (default: 2.0): Minimum vertical spacing between labels for tight projections (0.5% to 10.0%). Usage Instructions Add to Chart: Copy the script into TradingView’s Pine Editor, save, and add the indicator to your chart. Select Timeframe: Apply to any timeframe (e.g., 30-minute, hourly, daily, weekly, monthly) to match your trading strategy. Interpret Outputs: Green Line/Label: Bullish price target and confidence (e.g., "Bullish: 414.37, Confidence: 35%"). Red Line/Label: Bearish price target and confidence (e.g., "Bearish: 279.08, Confidence: 41.3%"). Higher confidence indicates a stronger likelihood of the projected outcome. Adjust Inputs: Modify Lookback Period to focus on shorter/longer historical trends (e.g., 20 for short-term, 100 for long-term). Change Projection Bars to adjust forecast horizon (e.g., 10 for shorter, 50 for longer). Tweak RSI Period or Confidence Threshold for sensitivity to momentum or trend strength. Customize Colors for visual preference. Increase Minimum Label Spacing if labels overlap in volatile markets. Combine with Analysis: Use alongside other indicators (e.g., moving averages, Bollinger Bands) or fundamental analysis to confirm signals, as projections are probabilistic. Example: TSLA Across Timeframes Using live TSLA data (close ~346.46 USD, May 31, 2025), the indicator produces: 30-Minute: Bullish 341.93 (13.3%), Bearish 327.96 (86.7%) – Strong bearish sentiment due to intraday volatility. 1-Hour: Bullish 342.00 (33.9%), Bearish 327.50 (62.3%) – Bearish but less intense, reflecting hourly swings. 4-Hour: Bullish 345.52 (73.4%), Bearish 344.44 (19.0%) – Flat outlook, indicating consolidation. Daily: Bullish 391.26 (68.8%), Bearish 302.22 (31.2%) – Bullish bias from recent uptrend, bearish tempered by longer lookback. Weekly: Bullish 414.37 (35.0%), Bearish 279.08 (41.3%) – Wide range, reflecting annual volatility. Monthly: Bullish 396.70 (54.9%), Bearish 296.93 (10.2%) – Long-term bullish optimism. These results align with market dynamics: short-term intervals capture volatility, while longer intervals smooth trends, providing balanced outlooks. Notes Accuracy: Projections are estimates based on historical data and should be used with other analysis tools. Confidence levels indicate likelihood, not certainty. Timeframe Sensitivity: Short-term intervals (e.g., 30-minute) show larger price swings and higher confidence due to volatility, while longer intervals (e.g., monthly) are more stable. Customization: Adjust inputs to match your trading style (e.g., shorter lookback for day trading, longer for swing trading). Performance: Tested on volatile stocks like TSLA, NVIDIA, and others, ensuring robust performance across markets. Limitations: May produce conservative bearish projections in strong uptrends due to momentum weighting. Adjust lookback or projection_bars for sensitivity. Feedback If you encounter issues (e.g., label overlap, projection mismatches), please share your timeframe, settings, or a screenshot. Suggestions for enhancements (e.g., additional filters, visual tweaks) are welcome! Disclaimer The Canuck Trading Projection Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
Pine Script® 인디케이터
ctoincanada의
Mandelbrot-Fibonacci Cascade Vortex (MFCV)Mandelbrot-Fibonacci Cascade Vortex (MFCV) - Where Chaos Theory Meets Sacred Geometry A Revolutionary Synthesis of Fractal Mathematics and Golden Ratio Dynamics What began as an exploration into Benoit Mandelbrot's fractal market hypothesis and the mysterious appearance of Fibonacci sequences in nature has culminated in a groundbreaking indicator that reveals the hidden mathematical structure underlying market movements. This indicator represents months of research into chaos theory, fractal geometry, and the golden ratio's manifestation in financial markets. The Theoretical Foundation Mandelbrot's Fractal Market Hypothesis Traditional efficient market theory assumes normal distributions and random walks. Mandelbrot proved markets are fractal - self-similar patterns repeating across all timeframes with power-law distributions. The MFCV implements this through: Hurst Exponent Calculation: H = log(R/S) / log(n/2) Where: R = Range of cumulative deviations S = Standard deviation n = Period length This measures market memory: H > 0.5: Trending (persistent) behavior H = 0.5: Random walk H < 0.5: Mean-reverting (anti-persistent) behavior Fractal Dimension: D = 2 - H This quantifies market complexity, where higher dimensions indicate more chaotic behavior. Fibonacci Vortex Theory Markets don't move linearly - they spiral. The MFCV reveals these spirals using Fibonacci sequences: Vortex Calculation: Vortex(n) = Price + sin(bar_index × φ / Fn) × ATR(Fn) × Volume_Factor Where: φ = 0.618 (golden ratio) Fn = Fibonacci number (8, 13, 21, 34, 55) Volume_Factor = 1 + (Volume/SMA(Volume,50) - 1) × 0.5 This creates oscillating spirals that contract and expand with market energy. The Volatility Cascade System Markets exhibit volatility clustering - Mandelbrot's "Noah Effect." The MFCV captures this through cascading volatility bands: Cascade Level Calculation: Level(i) = ATR(20) × φ^i Each level represents a different fractal scale, creating a multi-dimensional view of market structure. The golden ratio spacing ensures harmonic resonance between levels. Implementation Architecture Core Components: Fractal Analysis Engine Calculates Hurst exponent over user-defined periods Derives fractal dimension for complexity measurement Identifies market regime (trending/ranging/chaotic) Fibonacci Vortex Generator Creates 5 independent spiral oscillators Each spiral follows a Fibonacci period Volume amplification creates dynamic response Cascade Band System Up to 8 volatility levels Golden ratio expansion between levels Dynamic coloring based on fractal state Confluence Detection Identifies convergence of vortex and cascade levels Highlights high-probability reversal zones Real-time confluence strength calculation Signal Generation Logic The MFCV generates two primary signal types: Fractal Signals: Generated when: Hurst > 0.65 (strong trend) AND volatility expanding Hurst < 0.35 (mean reversion) AND RSI < 35 Trend strength > 0.4 AND vortex alignment Cascade Signals: Triggered by: RSI > 60 AND price > SMA(50) AND bearish vortex RSI < 40 AND price < SMA(50) AND bullish vortex Volatility expansion AND trend strength > 0.3 Both signals implement a 15-bar cooldown to prevent overtrading. Advanced Input System Mandelbrot Parameters: Cascade Levels (3-8): Controls number of volatility bands Crypto: 5-7 (high volatility) Indices: 4-5 (moderate volatility) Forex: 3-4 (low volatility) Hurst Period (20-200): Lookback for fractal calculation Scalping: 20-50 Day Trading: 50-100 Swing Trading: 100-150 Position Trading: 150-200 Cascade Ratio (1.0-3.0): Band width multiplier 1.618: Golden ratio (default) Higher values for trending markets Lower values for ranging markets Fractal Memory (21-233): Fibonacci retracement lookback Uses Fibonacci numbers for harmonic alignment Fibonacci Vortex Settings: Spiral Periods: Comma-separated Fibonacci sequence Fast: "5,8,13,21,34" (scalping) Standard: "8,13,21,34,55" (balanced) Extended: "13,21,34,55,89" (swing) Rotation Speed (0.1-2.0): Controls spiral oscillation frequency 0.618: Golden ratio (balanced) Higher = more signals, more noise Lower = smoother, fewer signals Volume Amplification: Enables dynamic spiral expansion Essential for stocks and crypto Disable for forex (no central volume) Visual System Architecture Cascade Bands: Multi-level volatility envelopes Gradient coloring from primary to secondary theme Transparency increases with distance from price Fill between bands shows fractal structure Vortex Spirals: 5 Fibonacci-period oscillators Blue above price (bullish pressure) Red below price (bearish pressure) Multiple display styles: Lines, Circles, Dots, Cross Dynamic Fibonacci Levels: Auto-updating retracement levels Smart update logic prevents disruption near levels Distance-based transparency (closer = more visible) Updates every 50 bars or on volatility spikes Confluence Zones: Highlighted boxes where indicators converge Stronger confluence = stronger support/resistance Key areas for reversal trades Professional Dashboard System Main Fractal Dashboard: Displays real-time: Hurst Exponent with market state Fractal Dimension with complexity level Volatility Cascade status Vortex rotation impact Market regime classification Signal strength percentage Active indicator levels Vortex Metrics Panel: Shows: Individual spiral deviations Convergence/divergence metrics Real-time vortex positioning Fibonacci period performance Fractal Metrics Display: Tracks: Dimension D value Market complexity rating Self-similarity strength Trend quality assessment Theory Guide Panel: Educational reference showing: Mandelbrot principles Fibonacci vortex concepts Dynamic trading suggestions Trading Applications Trend Following: High Hurst (>0.65) indicates strong trends Follow cascade band direction Use vortex spirals for entry timing Exit when Hurst drops below 0.5 Mean Reversion: Low Hurst (<0.35) signals reversal potential Trade toward vortex spiral convergence Use Fibonacci levels as targets Tighten stops in chaotic regimes Breakout Trading: Monitor cascade band compression Watch for vortex spiral alignment Volatility expansion confirms breakouts Use confluence zones for targets Risk Management: Position size based on fractal dimension Wider stops in high complexity markets Tighter stops when Hurst is extreme Scale out at Fibonacci levels Market-Specific Optimization Cryptocurrency: Cascade Levels: 5-7 Hurst Period: 50-100 Rotation Speed: 0.786-1.2 Enable volume amplification Stock Indices: Cascade Levels: 4-5 Hurst Period: 80-120 Rotation Speed: 0.5-0.786 Moderate cascade ratio Forex: Cascade Levels: 3-4 Hurst Period: 100-150 Rotation Speed: 0.382-0.618 Disable volume amplification Commodities: Cascade Levels: 4-6 Hurst Period: 60-100 Rotation Speed: 0.5-1.0 Seasonal adjustment consideration Innovation and Originality The MFCV represents several breakthrough innovations: First Integration of Mandelbrot Fractals with Fibonacci Vortex Theory Unique synthesis of chaos theory and sacred geometry Novel application of Hurst exponent to spiral dynamics Dynamic Volatility Cascade System Golden ratio-based band expansion Multi-timeframe fractal analysis Self-adjusting to market conditions Volume-Amplified Vortex Spirals Revolutionary spiral calculation method Dynamic response to market participation Multiple Fibonacci period integration Intelligent Signal Generation Cooldown system prevents overtrading Multi-factor confirmation required Regime-aware signal filtering Professional Analytics Dashboard Institutional-grade metrics display Real-time fractal analysis Educational integration Development Journey Creating the MFCV involved overcoming numerous challenges: Mathematical Complexity: Implementing Hurst exponent calculations efficiently Visual Clarity: Displaying multiple indicators without cluttering Performance Optimization: Managing array operations and calculations Signal Quality: Balancing sensitivity with reliability User Experience: Making complex theory accessible The result is an indicator that brings PhD-level mathematics to practical trading while maintaining visual elegance and usability. Best Practices and Guidelines Start Simple: Use default settings initially Match Timeframe: Adjust parameters to your trading style Confirm Signals: Never trade MFCV signals in isolation Respect Regimes: Adapt strategy to market state Manage Risk: Use fractal dimension for position sizing Color Themes Six professional themes included: Fractal: Balanced blue/purple palette Golden: Warm Fibonacci-inspired colors Plasma: Vibrant modern aesthetics Cosmic: Dark mode optimized Matrix: Classic green terminal Fire: Heat map visualization Disclaimer This indicator is for educational and research purposes only. It does not constitute financial advice. While the MFCV reveals deep market structure through advanced mathematics, markets remain inherently unpredictable. Past performance does not guarantee future results. The integration of Mandelbrot's fractal theory with Fibonacci vortex dynamics provides unique market insights, but should be used as part of a comprehensive trading strategy. Always use proper risk management and never risk more than you can afford to lose. Acknowledgments Special thanks to Benoit Mandelbrot for revolutionizing our understanding of markets through fractal geometry, and to the ancient mathematicians who discovered the golden ratio's universal significance. "The geometry of nature is fractal... Markets are fractal too." - Benoit Mandelbrot Revealing the Hidden Order in Market Chaos Trade with Mathematical Precision. Trade with MFCV. — Created with passion for the TradingView community Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
Pine Script® 인디케이터
DskyzInvestments의
26
Liquid Pulse Liquid Pulse by Dskyz (DAFE) Trading Systems Liquid Pulse is a trading algo built by Dskyz (DAFE) Trading Systems for futures markets like NQ1!, designed to snag high-probability trades with tight risk control. it fuses a confluence system—VWAP, MACD, ADX, volume, and liquidity sweeps—with a trade scoring setup, daily limits, and VIX pauses to dodge wild volatility. visuals include simple signals, VWAP bands, and a dashboard with stats. Core Components for Liquid Pulse Volume Sensitivity (volumeSensitivity) controls how much volume spikes matter for entries. options: 'Low', 'Medium', 'High' default: 'High' (catches small spikes, good for active markets) tweak it: 'Low' for calm markets, 'High' for chaos. MACD Speed (macdSpeed) sets the MACD’s pace for momentum. options: 'Fast', 'Medium', 'Slow' default: 'Medium' (solid balance) tweak it: 'Fast' for scalping, 'Slow' for swings. Daily Trade Limit (dailyTradeLimit) caps trades per day to keep risk in check. range: 1 to 30 default: 20 tweak it: 5-10 for safety, 20-30 for action. Number of Contracts (numContracts) sets position size. range: 1 to 20 default: 4 tweak it: up for big accounts, down for small. VIX Pause Level (vixPauseLevel) stops trading if VIX gets too hot. range: 10 to 80 default: 39.0 tweak it: 30 to avoid volatility, 50 to ride it. Min Confluence Conditions (minConditions) sets how many signals must align. range: 1 to 5 default: 2 tweak it: 3-4 for strict, 1-2 for more trades. Min Trade Score (Longs/Shorts) (minTradeScoreLongs/minTradeScoreShorts) filters trade quality. longs range: 0 to 100 default: 73 shorts range: 0 to 100 default: 75 tweak it: 80-90 for quality, 60-70 for volume. Liquidity Sweep Strength (sweepStrength) gauges breakouts. range: 0.1 to 1.0 default: 0.5 tweak it: 0.7-1.0 for strong moves, 0.3-0.5 for small. ADX Trend Threshold (adxTrendThreshold) confirms trends. range: 10 to 100 default: 41 tweak it: 40-50 for trends, 30-35 for weak ones. ADX Chop Threshold (adxChopThreshold) avoids chop. range: 5 to 50 default: 20 tweak it: 15-20 to dodge chop, 25-30 to loosen. VWAP Timeframe (vwapTimeframe) sets VWAP period. options: '15', '30', '60', '240', 'D' default: '60' (1-hour) tweak it: 60 for day, 240 for swing, D for long. Take Profit Ticks (Longs/Shorts) (takeProfitTicksLongs/takeProfitTicksShorts) sets profit targets. longs range: 5 to 100 default: 25.0 shorts range: 5 to 100 default: 20.0 tweak it: 30-50 for trends, 10-20 for chop. Max Profit Ticks (maxProfitTicks) caps max gain. range: 10 to 200 default: 60.0 tweak it: 80-100 for big moves, 40-60 for tight. Min Profit Ticks to Trail (minProfitTicksTrail) triggers trailing. range: 1 to 50 default: 7.0 tweak it: 10-15 for big gains, 5-7 for quick locks. Trailing Stop Ticks (trailTicks) sets trail distance. range: 1 to 50 default: 5.0 tweak it: 8-10 for room, 3-5 for fast locks. Trailing Offset Ticks (trailOffsetTicks) sets trail offset. range: 1 to 20 default: 2.0 tweak it: 1-2 for tight, 5-10 for loose. ATR Period (atrPeriod) measures volatility. range: 5 to 50 default: 9 tweak it: 14-20 for smooth, 5-9 for reactive. Hardcoded Settings volLookback: 30 ('Low'), 20 ('Medium'), 11 ('High') volThreshold: 1.5 ('Low'), 1.8 ('Medium'), 2 ('High') swingLen: 5 Execution Logic Overview trades trigger when confluence conditions align, entering long or short with set position sizes. exits use dynamic take-profits, trailing stops after a profit threshold, hard stops via ATR, and a time stop after 100 bars. Features Multi-Signal Confluence: needs VWAP, MACD, volume, sweeps, and ADX to line up. Risk Control: ATR-based stops (capped 15 ticks), take-profits (scaled by volatility), and trails. Market Filters: VIX pause, ADX trend/chop checks, volatility gates. Dashboard: shows scores, VIX, ADX, P/L, win %, streak. Visuals Simple signals (green up triangles for longs, red down for shorts) and VWAP bands with glow. info table (bottom right) with MACD momentum. dashboard (top right) with stats. Chart and Backtest: NQ1! futures, 5-minute chart. works best in trending, volatile conditions. tweak inputs for other markets—test thoroughly. Backtesting: NQ1! Frame: Jan 19, 2025, 09:00 — May 02, 2025, 16:00 Slippage: 3 Commission: $4.60 Fee Typical Range (per side, per contract) CME Exchange $1.14 – $1.20 Clearing $0.10 – $0.30 NFA Regulatory $0.02 Firm/Broker Commis. $0.25 – $0.80 (retail prop) TOTAL $1.60 – $2.30 per side Round Turn: (enter+exit) = $3.20 – $4.60 per contract Disclaimer this is for education only. past results don’t predict future wins. trading’s risky—only use money you can lose. backtest and validate before going live. (expect moderators to nitpick some random chart symbol rule—i’ll fix and repost if they pull it.) About the Author Dskyz (DAFE) Trading Systems crafts killer trading algos. Liquid Pulse is pure research and grit, built for smart, bold trading. Use it with discipline. Use it with clarity. Trade smarter. I’ll keep dropping badass strategies ‘til i build a brand or someone signs me up. 2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
Pine Script™ 전략
DskyzInvestments의
1
Fibonacci - RSI OscillatorIndicator Overview The Fibonacci RSI Oscillator calculates the Relative Strength Index (RSI) based on a dynamically adjusting level derived from recent price action and a fixed Fibonacci ratio (0.236). This differs from standard RSI, which is calculated directly on the closing price. The objective is to measure momentum relative to a level that adapts to recent peaks and valleys. Core Calculation Mechanism Peak/Valley Tracking: The script identifies the highest high (state_peak) and lowest low (state_valley) since the last detected change in short-term directional bias (state_dir). Dynamic Level Calculation: A level (state_dyn_level) is calculated using a fixed 0.236 Fibonacci ratio relative to the tracked peak and valley: If bias is up: state_dyn_level = state_peak - (state_peak - state_valley) * 0.236 If bias is down: state_dyn_level = state_valley + (state_peak - state_valley) * 0.236 This level adjusts automatically when a new peak or valley is established in the current directional bias. If price crosses the dynamic level against the current bias, the bias flips, and the level recalculates. Optional Source Smoothing: The calculated state_dyn_level can optionally be smoothed using a user-selected moving average (SMA, EMA, WMA, HMA, RMA) before the RSI calculation. RSI Calculation: The standard RSI formula is applied to the (optionally smoothed) state_dyn_level series to produce the primary oscillator value (val_primary_osc). Signal Line: A moving average (type and length configurable) is calculated on the val_primary_osc to generate the val_sig_line. Key Features & Components Dynamic Fibonacci Level: The core input for the RSI calculation, based on recent peaks/valleys and the 0.236 ratio. Fibonacci Level RSI: The primary oscillator line representing the RSI of the dynamic level. Signal Line: A moving average of the primary RSI line. Overbought/Oversold Levels: User-defined threshold lines. Optional Source Smoothing: Configurable MA smoothing applied to the dynamic level before RSI calculation. Gradient RSI Color : Option to color the primary RSI line based on its value relative to OB/Mid/OS levels. Zone & OB/OS Fills: Visual fills for the 0-50 / 50-100 zones and specific fills when the RSI enters OB/OS territory. Background Gradient: Optional vertical background color gradient based on the RSI's position between 0 and 100. Configurable Parameters: Inputs for lengths, MA types, OB/OS levels, colors, line widths, and feature toggles. Visual Elements Explained Fibonacci Level RSI Line: The main plotted oscillator (color/gradient/width configurable). Signal Line: The moving average of the RSI line (color/width/MA type configurable). OB/OS Lines: Horizontal lines plotted at the set OB/OS levels (color/width configurable). Mid-Line (50): Horizontal line plotted at 50 (color/width configurable). Zone Fills: Background fill between 0-50 and 50-100 (colors configurable). Conditional fill between the RSI line and the 50 line when RSI > OB level or RSI < OS level (colors configurable). Background Gradient: Optional background coloring where transparency varies vertically with the RSI level (base colors and transparency range configurable). Configuration Options Users can adjust the following parameters in the indicator settings: Smoothing: Enable/disable dynamic level smoothing; set length and MA type. RSI: Set the RSI calculation length. Signal Line: Set the signal line smoothing length and MA type. Levels: Define Overbought and Oversold numeric thresholds. Visuals: Configure colors and widths for the RSI line, signal line, OB/OS lines, mid-line, zone fills, and OB/OS fills. Gradients: Enable/disable and configure colors for the RSI line gradient; enable/disable and configure colors/transparency for the background gradient. Interpretation Notes The oscillator reflects the momentum of the dynamic Fibonacci level, not directly the price. Divergences, OB/OS readings, and signal line crossovers should be interpreted in this context. The behavior may differ from standard RSI, potentially offering a smoother output or highlighting different momentum patterns depending on market structure and volatility. As with any indicator, signals should be used in conjunction with other analysis methods and risk management practices. It is not designed as a standalone trading system. Risk Disclaimer: Trading involves significant risk. This indicator is provided for analytical purposes only and does not constitute financial advice. Past performance is not indicative of future results. Use sound risk management practices and never trade with capital you cannot afford to lose.
Pine Script® 인디케이터
sizzlinsoft의
2
Combined ATR + VolumeOverview The Combined ATR + Volume indicator (C-ATR+Vol) is designed to measure both price volatility and market participation by merging the Average True Range (ATR) and trading volume into a single normalized value. This provides traders with a more comprehensive tool than ATR alone, as it highlights not only how much price is moving, but also whether there is sufficient volume behind those moves. Originality & Utility Two Key Components ATR (Average True Range): Measures price volatility by analyzing the range (high–low) over a specified period. A higher ATR often indicates larger price swings. Volume: Reflects how actively traders are participating in the market. High volume typically indicates strong buying or selling interest. Normalized Combination Both ATR and volume are independently normalized to a 0–100 range. The final output (C-ATR+Vol) is the average of these two normalized values. This makes it easy to see when both volatility and market participation are relatively high. Practical Use Above 80: Signifies elevated volatility and strong volume. Markets may experience significant moves. Around 50–80: Indicates moderate activity. Price swings and volume are neither extreme nor minimal. Below 50: Suggests relatively low volatility and lower participation. The market may be ranging or consolidating. This combined approach can help filter out situations where volatility is high but volume is absent—or vice versa—providing a more reliable context for potential breakouts or trend continuations. Indicator Logic ATR Calculation Uses Pine Script’s built-in ta.tr(true) function to measure true range, then smooths it with a user-selected method (RMA, SMA, EMA, or WMA). Key Input: ATR Length (default 14). Volume Calculation Smooths the built-in volume variable using the same selectable smoothing methods. Key Input: Volume Length (default 14). Normalization For each metric (ATR and Volume), the script finds the lowest and highest values over the lookback period and converts them into a 0–100 scale: normalized value =(current value−min)(max−min)×100 normalized value= (max−min)(current value−min) ×100 Combined Score The final plot is the average of Normalized ATR and Normalized Volume. This single value simplifies the process of identifying high-volatility, high-volume conditions. How to Use Setup Add the indicator to your chart. Adjust ATR Length, Volume Length, and Smoothing to match your preferred time horizon or chart style. Interpretation High Values (above 80): The market is experiencing significant price movement with high participation. Potential for strong trends or breakouts. Moderate Range (50–80): Conditions are active but not extreme. Trend setups may be forming. Low Values (below 50): Indicates quieter markets with reduced liquidity. Expect ranging or less decisive moves. Strategy Integration Use C-ATR+Vol alongside other trend or momentum indicators (e.g., Moving Averages, RSI, MACD) to confirm potential entries/exits. Combine it with support/resistance or price action analysis for a broader market view. Important Notes This script is open-source and intended as a community contribution. No Future Guarantee: Past market behavior does not guarantee future results. Always use proper risk management and validate signals with additional tools. The indicator’s performance may vary depending on timeframes, asset classes, and market conditions. Adjust inputs as needed to suit different instruments or personal trading styles. By adhering to TradingView’s publishing rules, this script is provided with sufficient detail on what it does, how it’s unique, and how traders can use it. Feel free to customize the settings and experiment with other technical indicators to develop a trading methodology that fits your objectives. 🔹 Combined ATR + Volume (C-ATR+Vol) 지표 설명 이 인디케이터는 ATR(Average True Range)와 거래량(Volume)을 결합하여 시장의 변동성과 유동성을 동시에 측정하는 지표입니다. ATR은 가격 변동성의 크기를 나타내며, 거래량은 시장 참여자의 활동 수준을 반영합니다. 보통 높은 ATR은 가격 변동이 크다는 의미이고, 높은 거래량은 시장에서 적극적인 거래가 이루어지고 있음을 나타냅니다. 이 두 지표를 각각 0~100 범위로 정규화한 후, 평균을 구하여 "Combined ATR + Volume (C-ATR+Vol)" 값을 계산합니다. 이를 통해 단순한 가격 변동성뿐만 아니라 거래량까지 고려하여, 더욱 신뢰성 있는 변동성 판단을 할 수 있도록 도와줍니다. 📌 핵심 개념 1️⃣ ATR (Average True Range)란? 시장의 변동성을 측정하는 지표로, 일정 기간 동안의 고점-저점 변동폭을 기반으로 계산됩니다. ATR이 높을수록 가격 변동이 크며, 낮을수록 횡보장이 지속될 가능성이 큽니다. 하지만 ATR은 방향성을 제공하지 않으며, 단순히 변동성의 크기만을 나타냅니다. 2️⃣ 거래량 (Volume)의 역할 거래량은 시장 참여자의 관심과 유동성을 반영하는 중요한 요소입니다. 높은 거래량은 강한 매수 또는 매도세가 존재함을 의미하며, 낮은 거래량은 시장 참여가 적거나 관심이 줄어들었음을 나타냅니다. 3️⃣ ATR + 거래량의 결합 (C-ATR+Vol) 단순한 ATR 값만으로는 변동성이 커도 거래량이 부족할 수 있으며, 반대로 거래량이 많아도 변동성이 낮을 수 있습니다. 이를 해결하기 위해 ATR과 거래량을 각각 0~100으로 정규화하여 균형 잡힌 변동성 지표를 만들었습니다. 두 지표의 평균값을 계산하여, 가격 변동과 거래량이 동시에 높은지를 측정할 수 있도록 설계되었습니다. 📊 사용법 및 해석 80 이상 → 강한 변동성 구간 가격 변동성이 크고 거래량도 높은 상태 강한 추세가 진행 중이거나 큰 변동이 일어날 가능성이 큼 상승/하락 방향성을 확인한 후 트렌드를 따라가는 전략이 유리 50~80 구간 → 보통 수준의 변동성 가격 움직임이 일정하며, 거래량도 적절한 수준 점진적인 추세 형성이 이루어질 가능성이 있음 시장이 점진적으로 상승 혹은 하락할 가능성이 크므로, 보조지표를 활용하여 매매 타이밍을 결정하는 것이 중요 50 이하 → 낮은 변동성 및 유동성 부족 가격 변동이 적고, 거래량도 낮은 상태 시장이 횡보하거나 조정 기간에 들어갈 가능성이 큼 박스권 매매(지지/저항 활용) 또는 돌파 전략을 고려할 수 있음 💡 활용 방법 및 전략 ✅ 1. 트렌드 판단 보조지표로 활용 단독으로 사용하는 것보다는 RSI, MACD, 이동평균선(MA) 등의 지표와 함께 활용하는 것이 효과적입니다. 예를 들어, MACD가 상승 신호를 주고, C-ATR+Vol 값이 80을 초과하면 강한 상승 추세로 해석할 수 있습니다. ✅ 2. 변동성 돌파 전략에 활용 C-ATR+Vol이 80 이상인 구간에서 가격이 특정 저항선을 돌파한다면, 강한 추세의 시작을 의미할 수 있습니다. 반대로, C-ATR+Vol이 50 이하에서 가격이 저항선에 가까워지면 돌파 가능성이 낮아질 수 있습니다. ✅ 3. 시장 참여도와 변동성 확인 단순히 ATR만 높아서는 신뢰하기 어려운 경우가 많습니다. 예를 들어, 급등 후 거래량이 급감하면 상승 지속 가능성이 낮아질 수도 있습니다. 하지만 C-ATR+Vol을 사용하면 거래량이 함께 증가하는지를 확인하여 보다 신뢰할 수 있는 분석이 가능합니다. 🚀 결론 🔹 Combined ATR + Volume (C-ATR+Vol) 인디케이터는 단순한 ATR이 아니라 거래량까지 고려하여 변동성을 측정하는 강력한 도구입니다. 🔹 시장이 큰 움직임을 보일 가능성이 높은 구간을 찾는 데 유용하며, 80 이상일 경우 강한 변동성이 있음을 나타냅니다. 🔹 단독으로 사용하기보다는 보조지표와 함께 활용하여, 트렌드 분석 및 돌파 전략 등에 효과적으로 적용할 수 있습니다. 📌 주의사항 변동성이 크다고 해서 반드시 가격이 급등/급락한다는 보장은 없습니다. 특정한 매매 전략 없이 단순히 이 지표만 보고 매수/매도를 결정하는 것은 위험할 수 있습니다. 시장 상황에 따라 변동성의 의미가 다르게 작용할 수 있으므로, 반드시 다른 보조지표와 함께 활용하는 것이 중요합니다. 🔥 이 지표를 활용하여 시장의 변동성과 거래량을 보다 효과적으로 분석해보세요! 🚀
Pine Script® 인디케이터
kdhchgo의
1
MA Cross Multi Alert KrafturMA Cross Multi Alert Kraftur Description The "MA Cross Multi Alert Kraftur" indicator is a versatile tool designed to help traders identify potential buy and sell opportunities based on the crossings of multiple moving averages (MAs). Unlike traditional MA crossover indicators that focus on a single pair of averages, this script offers three distinct crossover levels (e.g., 21/50, 50/90, 50/200) for greater flexibility and precision. It overlays signals directly on the price chart and delivers real-time alerts when crossings occur, making it an excellent choice for traders seeking to pinpoint entry and exit points across various market conditions. Key Features Multi-Level Crossovers: Tracks crossings between configurable moving averages (e.g., 21 crossing 50, 50 crossing 90, 50 crossing 200) to detect varying trend strengths and reversals. Visual Signals: Buy signals are displayed as upward triangles below the bars, and sell signals as downward triangles above the bars, each color-coded for quick recognition. Real-Time Alerts: Triggers alerts once per bar when a crossover occurs, with a filter to avoid repetitive notifications during minor fluctuations. Customizable: Adjustable MA lengths, timeframe, and signal colors allow tailoring to individual trading preferences and strategies. Recommended Usage This indicator shines as a scanning tool for identifying trade setups across multiple assets. Apply it to your watchlist of stocks, forex pairs, or cryptocurrencies, and set up alerts to catch crossover signals in real time. It performs exceptionally well in trending or consolidating markets and can be paired with additional tools (e.g., trendlines, RSI, or volume analysis) to validate signals and boost reliability. Ideal for multi-timeframe traders or those managing diverse portfolios. How to Use Add the indicator to your chart. Adjust the MA lengths (e.g., 21, 50, 90, 200), timeframe, and signal colors to align with your trading approach. Configure alerts for the indicator and apply them to your asset watchlist. Watch for buy (upward triangles) and sell (downward triangles) signals on the chart, or rely on alert notifications for timely updates. Perfect for day traders, swing traders, or anyone aiming to streamline signal detection and automate their workflow!
Pine Script® 인디케이터
Kraftur의
Multi SMA EMA VWAP1. Moving Average Crossover This is one of the most common strategies with moving averages, and it involves observing crossovers between EMAs and SMAs to determine buy or sell signals. Buy signal: When a faster EMA (like a short-term EMA) crosses above a slower SMA, it can indicate a potential upward movement. Sell signal: When a faster EMA crosses below a slower SMA, it can indicate a potential downward movement. With 4 EMAs and 5 SMAs, you can set up crossovers between different combinations, such as: EMA(9) crosses above SMA(50) → buy. EMA(9) crosses below SMA(50) → sell. 2. Divergence Confirmation Between EMAs and SMAs Divergence between the EMAs and SMAs can offer additional confirmation. If the EMAs are pointing in one direction and the SMAs are still in the opposite direction, it is a sign that the movement could be stronger and continue in the same direction. Positive divergence: If the EMAs are making new highs while the SMAs are still below, it could be a sign that the market is in a strong trend. Negative divergence: If the EMAs are making new lows and the SMAs are still above, you might consider that the market is in a downtrend or correction. 3. Using EMAs as Dynamic Support and Resistance EMAs can act as dynamic support and resistance in strong trends. If the price approaches a faster EMA from above and doesn’t break it, it could be a good entry point for a long position (buy). If the price approaches a slower EMA from below and doesn't break it, it could be a good point to sell (short). Buy: If the price is above all EMAs and approaches the fastest EMA (e.g., EMA(9)), it could be a good buy point if the price bounces upward. Sell: If the price is below all EMAs and approaches the fastest EMA, it could be a good sell point if the price bounces downward. 4. Combining SMAs and EMAs to Filter Signals SMAs can serve as a trend filter to avoid trading in sideways markets. For example: Bullish trend condition: If the longer-term SMAs (such as SMA(100) or SMA(200)) are below the price, and the shorter EMAs are aligned upward, you can look for buy signals. Bearish trend condition: If the longer-term SMAs are above the price and the shorter EMAs are aligned downward, you can look for sell signals. 5. Consolidation Zone Between EMAs and SMAs When the price moves between EMAs and SMAs without a clear trend (consolidation zone), you can expect a breakout. In this case, you can use the EMAs and SMAs to identify the direction of the breakout: If the price is in a narrow range between the EMAs and SMAs and then breaks above the fastest EMA, it’s a sign that an upward trend may begin. If the price breaks below the fastest EMA, it could indicate a potential downward trend. 6. "Golden Cross" and "Death Cross" Strategy These are classic strategies based on crossovers between moving averages of different periods. Golden Cross: Occurs when a faster EMA (e.g., EMA(50)) crosses above a slower SMA (e.g., SMA(200)), which suggests a potential bullish trend. Death Cross: Occurs when a faster EMA crosses below a slower SMA, which suggests a potential bearish trend. Additional Recommendations: Combining with other indicators: You can combine EMA and SMA signals with other indicators like the RSI (Relative Strength Index) or MACD (Moving Average Convergence/Divergence) for confirmation and to avoid false signals. Risk management: Always use stop-loss and take-profit orders to protect your capital. Moving averages are trend-following indicators but don’t guarantee that the price will move in the same direction. Timeframe analysis: It’s recommended to use different timeframes to confirm the trend (e.g., use EMAs on hourly charts along with SMAs on daily charts). VWAP 1. VWAP + EMAs for Trend Confirmation VWAP can act as a trend filter, confirming the direction provided by the EMAs. Buy Signal: If the price is above the VWAP and the EMAs are aligned in an uptrend (e.g., short-term EMAs are above longer-term EMAs), this indicates that the trend is bullish and you can look for buy opportunities. Sell Signal: If the price is below the VWAP and the EMAs are aligned in a downtrend (e.g., short-term EMAs are below longer-term EMAs), this suggests a bearish trend and you can look for sell opportunities. In this case, VWAP is used to confirm the overall trend. For example: Bullish: Price above VWAP, EMAs aligned to the upside (e.g., EMA(9) > EMA(50) > EMA(200)), buy. Bearish: Price below VWAP, EMAs aligned to the downside (e.g., EMA(9) < EMA(50) < EMA(200)), sell. 2. VWAP as Dynamic Support and Resistance VWAP can act as a dynamic support or resistance level during the day. Combining this with EMAs and SMAs helps you refine your entry and exit points. Support: If the price is above VWAP and starts pulling back to VWAP, it could act as support. If the price bounces off the VWAP and aligns with bullish EMAs (e.g., EMA(9) crossing above EMA(50)), you can consider entering a buy position. Resistance: If the price is below VWAP and approaches VWAP from below, it can act as resistance. If the price fails to break through VWAP and aligns with bearish EMAs (e.g., EMA(9) crossing below EMA(50)), it could be a good signal for a sell.
Pine Script® 인디케이터
laguiler의
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib Description: The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals. The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal. Features: Three Simple Moving Averages (SMA): SMA 20: Short-term moving average reflecting immediate market trends. SMA 50: Medium-term moving average showing the prevailing trend. SMA 200: Long-term moving average that indicates the overall market trend. Buy Signal (B1): Triggered when: SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure. The closing price is positioned below all three SMAs, confirming a potential upward reversal. A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated. Second Buy Signal (B2): Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price. A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises. Sell Signal (S): Triggered when: SMA 20 > SMA 50 > SMA 200, indicating a bearish trend. The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement. A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered. How It Works: Buy Conditions: SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20). Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal. Sell Conditions: SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend. Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement. Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry. Labeling System: B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs. B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal. S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs. How to Use: Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView. Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish. Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity. Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs. Conclusion: The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
Pine Script® 인디케이터
plsadv03의
UVR Crypto TrendINDICATOR OVERVIEW: UVR CRYPTO TREND The UVR Crypto Trend indicator is a custom-built tool designed specifically for cryptocurrency markets, utilizing advanced volatility, momentum, and trend-following techniques. It aims to identify trend reversals and provide buy and sell signals by analyzing multiple factors, such as price volatility(UVR), RSI (Relative Strength Index), CMF (Chaikin Money Flow), and EMA (Exponential Moving Average). The indicator is optimized for CRYPTO MARKETS only. KEY FEATURES AND HOW IT WORKS Volatility Analysis with UVR The UVR (Ultimate Volatility Rate) is a proprietary calculation that measures market volatility by comparing significant price extremes and smoothing the data over time. Purpose: UVR aims to reduce noise in low-volatility environments and highlight significant movements during higher-volatility periods. While it strives to improve filtering in low-volatility conditions, it does not guarantee perfect performance, making it a balanced and adaptable tool for dynamic markets like cryptocurrency. HOW UVR (ULTIMATE VOLATILITY RATE) IS CALCULATED UVR is calculated using a method that ensures precise measurement of market volatility by comparing price extremes across consecutive candles: Volatility Components: Two values are calculated to represent potential price fluctuations: The absolute difference between the current candle's high and the previous candle's low: Volatility Component 1=∣High−Low ∣ The absolute difference between the previous candle's high and the current candle's low: Volatility Component 2=∣High −Low∣ Volatility Ratio: The larger of the two components is selected as the Volatility Ratio, ensuring UVR captures the most significant movement: Volatility Ratio=max(Volatility Component 1,Volatility Component 2) Smoothing with SMMA: To stabilize the volatility calculation, the Volatility Ratio is smoothed using a Smoothed Moving Average (SMMA) over a user-defined period (e.g., 14 candles): UVR=(UVR(Previous)×(Period−1)+Volatility Ratio)/Period ​ This calculation ensures UVR adapts dynamically to market conditions, focusing on significant price movements while filtering out noise. RSI FOR MOMENTUM DETECTION RSI (Relative Strength Index) identifies overbought and oversold conditions. Trend Confirmation at the 50 Level RSI values crossing above 50 signal the potential start of an upward trend. RSI values crossing below 50 indicate the potential start of a downward trend. Key Reversals at Extreme Levels RSI detects trend reversals at overbought (>70) and oversold (<30) levels. For example: Overbought Trend Reversal: RSI >70 followed by bearish price action signals a potential downtrend. Oversold Trend Reversal: RSI <30 with bullish confirmation signals a potential uptrend. Rare Extreme RSI Readings Extreme levels, such as RSI <12 (oversold) or RSI >88 (overbought), are used to identify rare yet powerful reversals. ---HOW IT DIFFERS FROM OTHER INDICATORS--- Using UVR High and Low Values The Ultimate Volatility Rate (UVR) focuses on analyzing the high and low price ranges of the market to measure volatility. Unlike traditional trend indicators that rely primarily on momentum or moving average crossovers, UVR leverages price extremes to better identify trend reversals. This approach ensures fewer false signals during low-volatility phases and more accurate trend detection during high-volatility conditions. UVR as the Core Component The indicator is fundamentally built around UVR as the primary filter, while supporting tools like RSI (momentum detection), CMF (volume confirmation), and EMA (trend validation) complement its functionality. By integrating these additional components, the indicator provides a multidimensional analysis rather than relying solely on a single approach. Dynamic Adaptation to Volatility UVR dynamically adjusts to market conditions, striving to improve filtering in low-volatility phases. While not flawless, this approach minimizes false signals and adapts more effectively to varying levels of market activity. Trend Clouds for Visual Guidance UVR-based dynamic clouds visually mark high and low price areas, highlighting potential consolidation or retracement zones. These clouds serve as guides for setting stop-loss or take-profit levels, offering clear risk management strategies. BUY AND SELL SIGNAL LOGIC BUY CONDITIONS Momentum-Based Buy-Entry RSI >50, CMF >0, and the close price is above EMA50. The price difference between open and close exceeds a threshold based on UVR. Oversold Reversal RSI <30 and CMF >0 with a strong bullish candle (close > open and UVR-based sensitivity filter). Breakout Confirmation The price breaks above a previously identified resistance, with conditions for RSI and CMF supporting the breakout. Reversal from Oversold RSI Extreme RSI <12 on the previous candle with a strong rebound on the current candle with UVR confirmation filter. SELL CONDITIONS Momentum-Based Sell-Entry RSI <50, CMF <0, and the close price is below EMA50. The price difference between open and close exceeds the UVR threshold. Overbought Reversal RSI >70 with bearish price action (open > close and UVR-based sensitivity filter). Breakdown Confirmation The price breaks below a previously identified support, with RSI and CMF supporting the breakdown. Reversal from Overbought RSI Extreme RSI >88 on the previous candle with a bearish confirmation on the current candle with UVR confirmation filter. BUY AND SELL SIGNALS VISUALIZATION The UVR Crypto Trend Indicator visually represents buy and sell conditions using dynamic plots, making it easier for traders to interpret and act on the signals. Below is an explanation of the visual representation: Buy Signals and Visualization Signal Trigger: A buy signal is generated when one of the defined Buy Conditions is met (e.g., RSI >50, CMF >0, price above EMA50). Visual Representation: A blue upward arrow appears at the candle where the buy condition is triggered. A blue cloud forms above the price candles, representing the strength of the bullish trend. The cloud dynamically adapts to market volatility, using the UVR calculation to mark support zones or consolidation levels. Purpose of the Blue Cloud: It acts as a visual guide for price movements and stay horizontal when the trend is not moving up Sell Signals and Visualization Signal Trigger: A sell signal is generated when one of the defined Sell Conditions is met (e.g., RSI <50, CMF <0, price below EMA50). Visual Representation: A red downward arrow appears at the candle where the sell condition is triggered. A red cloud forms below the price candles, representing the strength of the bearish trend. Like the blue cloud, it uses the UVR calculation to dynamically mark resistance zones or potential retracement levels. Purpose of the Red Cloud: It acts as a visual guide for price movements and stay horizontal when the trend is not moving down. CONCLUSION The UVR Crypto Trend indicator provides a powerful tool for trend reversal detection by combining volatility analysis, momentum confirmation, and trend-following techniques. Its unique use of the Ultimate Volatility Rate (UVR) as a core element, supported by proven indicators like RSI, CMF, and EMA, ensures reliable and actionable signals tailored for the crypto market's dynamic nature. By leveraging UVR’s high and low price range analysis, it achieves a level of precision that traditional indicators lack, making it a high-performing system for cryptocurrency traders.
Pine Script® 인디케이터
ebecihalil의
simple swing indicator-KTRNSE:NIFTY 1. Pivot High/Low as Lines: Purpose: Identifies local peaks (pivot highs) and troughs (pivot lows) in price and draws horizontal lines at these levels. How it Works: A pivot high occurs when the price is higher than the surrounding bars (based on the pivotLength parameter). A pivot low occurs when the price is lower than the surrounding bars. These pivots are drawn as horizontal lines at the price level of the pivot. Visualization: Pivot High: A red horizontal line is drawn at the price level of the pivot high. Pivot Low: A green horizontal line is drawn at the price level of the pivot low. Example: Imagine the price is trending up, and at some point, it forms a peak. The script identifies this peak as a pivot high and draws a red line at the price of that peak. Similarly, if the price forms a trough, the script will draw a green line at the low point. 2. Moving Averages (20-day and 50-day): Purpose: Plots the 20-day and 50-day simple moving averages (SMA) on the chart. How it Works: The 20-day SMA smooths the closing price over the last 20 days. The 50-day SMA smooths the closing price over the last 50 days. These lines provide an overview of short-term and long-term price trends. Visualization: 20-day SMA: A blue line showing the 20-day moving average. 50-day SMA: An orange line showing the 50-day moving average. Example: When the price is above both moving averages, it indicates an uptrend. If the price crosses below these averages, it might signal a downtrend. 3. Supertrend: Purpose: The Supertrend is an indicator based on the Average True Range (ATR) and is used to track the market trend. How it Works: When the market is in an uptrend, the Supertrend line will be green. When the market is in a downtrend, the Supertrend line will be red. Visualization: Uptrend: The Supertrend line will be plotted in green. Downtrend: The Supertrend line will be plotted in red. Example: If the price is above the Supertrend, the market is considered to be in an uptrend, and if the price is below the Supertrend, the market is in a downtrend. 4. Momentum (Rate of Change): Purpose: Measures the rate at which the price changes over a set period, showing if the momentum is positive or negative. How it Works: The Rate of Change (ROC) measures how much the price has changed over a certain number of periods (e.g., 14). Positive ROC indicates upward momentum, and negative ROC indicates downward momentum. Visualization: Positive ROC: A purple line is plotted above the zero line. Negative ROC: A purple line is plotted below the zero line. Example: If the ROC line is above zero, it means the price is increasing, suggesting bullish momentum. If the ROC is below zero, it indicates bearish momentum. 5. Volume: Purpose: Displays the volume of traded assets, giving insight into the strength of price movements. How it Works: The script will color the volume bars based on whether the price closed higher or lower than the previous bar. Green bars indicate bullish volume (closing price higher than the previous bar), and red bars indicate bearish volume (closing price lower than the previous bar). Visualization: Bullish Volume: Green volume bars when the price closes higher. Bearish Volume: Red volume bars when the price closes lower. Example: If you see a green volume bar, it suggests that the market is participating in an uptrend, and the price has closed higher than the previous period. Red bars indicate a downtrend or selling pressure. 6. MACD (Moving Average Convergence Divergence): Purpose: The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of the price. How it Works: The MACD Line is the difference between the 12-period EMA (Exponential Moving Average) and the 26-period EMA. The Signal Line is the 9-period EMA of the MACD Line. The MACD Histogram shows the difference between the MACD line and the Signal line. Visualization: MACD Line: A blue line representing the difference between the 12-period and 26-period EMAs. Signal Line: An orange line representing the 9-period EMA of the MACD line. MACD Histogram: A red or green histogram that shows the difference between the MACD line and the Signal line. Example: When the MACD line crosses above the Signal line, it’s considered a bullish signal. When the MACD line crosses below the Signal line, it’s considered a bearish signal. Full Chart Example: Imagine you're looking at a price chart with all the indicators: Pivot High/Low Lines are drawn as red and green horizontal lines. 20-day and 50-day SMAs are plotted as blue and orange lines, respectively. Supertrend shows a green or red line indicating the trend. Momentum (ROC) is shown as a purple line oscillating around zero. Volume bars are green or red based on whether the close is higher or lower. MACD appears as a blue line and orange line, with a red or green histogram showing the MACD vs. Signal line difference. How the Indicators Work Together: Trend Confirmation: If the price is above the Supertrend line and both SMAs are trending up, it indicates a strong bullish trend. Momentum: If the ROC is positive and the MACD line is above the Signal line, it further confirms bullish momentum. Volume: Increasing volume, especially with green bars, suggests that the trend is being supported by active participation. By using these combined indicators, you can get a comprehensive view of the market's trend, momentum, and potential reversal points (via pivot highs and lows).
Pine Script® 인디케이터
kathir0의
Swiss Knife [MERT]Introduction The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format. --- Key Features Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes. Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection. Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score. Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart. Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots. --- Explanation of Each Indicator Moving Average Convergence Divergence (MACD) - Purpose : Measures the relationship between two moving averages of price. - Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum. Awesome Oscillator (AO) - Purpose : Gauges market momentum by comparing recent market movements to historic ones. - Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum. Parabolic SAR (SAR) - Purpose : Identifies potential reversal points in price direction. - Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend. SuperTrend - Purpose : Determines the prevailing market trend. - Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line. Detrended Price Oscillator (DPO) - Purpose : Removes trend from price to identify cycles. - Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below. Relative Strength Index (RSI) - Purpose : Measures the speed and change of price movements. - Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum. Stochastic Oscillator - Purpose : Compares a particular closing price to a range of its prices over a certain period. - Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions. Bollinger Bands (BB) - Purpose : Measures market volatility and provides relative price levels. - Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness. Ichimoku Cloud - Purpose : Provides support and resistance levels, trend direction, and momentum. - Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud. Chande Momentum Oscillator (CMO) - Purpose : Measures momentum on both up and down days. - Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum. Donchian Channels - Purpose : Identifies volatility and potential breakouts. - Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout. Average Directional Index (ADX) - Purpose : Measures the strength of a trend. - Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend. Volume Momentum Indicators (VolMom, CumVolMom, POCMom) - Purpose : Analyze volume to assess buying and selling pressure. - Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum. Fractals - Purpose : Identify potential reversal points in the market. - Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend. Divergence Detection - Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line). - Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal. - Note : This functionality utilizes the library from Divergence Indicator . --- Coloring Scheme Background Color - Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes. - Interpretation : - Green Shades : Indicate bullish market sentiment. - Red Shades : Indicate bearish market sentiment. - Intensity : The strength of the color corresponds to the strength of the sentiment score. Sentiment Table - Purpose : Displays the status of each indicator across different timeframes. - Interpretation : - Green Cell : The indicator suggests a bullish signal. - Red Cell : The indicator suggests a bearish signal. - Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe. Exponential Moving Averages (EMAs) - Purpose : Provide dynamic support and resistance levels. - Colors : - EMA 10 : Lime - EMA 20 : Yellow - EMA 50 : Orange - EMA 100 : Red - EMA 200 : Purple Trendlines - Purpose : Visual representation of support and resistance levels based on pivot points. - Interpretation : - Upward Trendlines : Colored green , indicating support levels. - Downward Trendlines : Colored red , indicating resistance levels. - Note : Trendlines are drawn using the library from Simple Trendlines . --- Utility of Market Sentiment The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by: Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend. Identifying Reversals : Divergences and fractals can signal potential turning points. Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades. --- Divergences Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal. - Bullish Divergence : Price makes a lower low, but the indicator makes a higher low. - Bearish Divergence : Price makes a higher high, but the indicator makes a lower high. The indicator detects divergences for: RSI MACD Stochastic Oscillator On-Balance Volume (OBV) Money Flow Index (MFI) Accumulation/Distribution Line (A/D Line) By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly. --- Trendlines Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points: - Upward Trendlines (Support) : Connect higher lows, indicating an uptrend. - Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend. These trendlines help traders visualize the trend direction and potential breakout or reversal points. --- Super Trend Reversals (ST Reversal) The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders: Engage Early : Enter the market as reversal momentum builds up. Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes. By capturing these reversal points, traders can enhance their trading performance. --- Conclusion The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions. --- Citations - Divergence Detection Library : Divergence Indicator by DevLucem - Trendline Drawing Library : Simple Trendlines by HoanGhetti --- Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions. ---
Pine Script® 인디케이터
UnknownUnicorn13336802의
10
Uptrick: EMA Trend Indicator ### Overview The goal of this script is to visually indicate on a trading chart whether all three Exponential Moving Averages (EMAs) are trending upwards (i.e., their slopes are positive). If all EMAs are trending upwards, the script will color the bars green. If not, the bars will be colored red. ### Key Concepts 1. **Exponential Moving Average (EMA)**: An EMA is a type of moving average that places more weight on recent data, making it more responsive to price changes compared to a simple moving average (SMA). In this script, we use three different EMAs with different lengths (20, 50, and 200 periods). 2. **Slope of an EMA**: The slope of an EMA refers to the direction in which the EMA is moving. If the current value of the EMA is higher than its value in the previous bar, the slope is positive (upward). Conversely, if the current value is lower than its previous value, the slope is negative (downward). 3. **Bar Color Coding**: The script changes the color of the bars on the chart to provide a visual cue: - **Green Bars**: Indicate that all three EMAs are trending upwards. - **Red Bars**: Indicate that one or more EMAs are not trending upwards. ### Detailed Breakdown #### 1. Input Fields - **EMA Lengths**: The script starts by allowing the user to input the lengths for the three EMAs. These lengths determine how many periods (e.g., days) are used to calculate each EMA. - `ema20_length` is set to 20, meaning the first EMA uses the last 20 bars of data. - `ema50_length` is set to 50, meaning the second EMA uses the last 50 bars of data. - `ema200_length` is set to 200, meaning the third EMA uses the last 200 bars of data. #### 2. EMA Calculation - The script calculates the values of the three EMAs: - **EMA 20**: This is calculated using the last 20 bars of closing prices. - **EMA 50**: This is calculated using the last 50 bars of closing prices. - **EMA 200**: This is calculated using the last 200 bars of closing prices. These calculations result in three values for each bar on the chart, each representing the EMA value at that point in time. #### 3. Determining EMA Slopes - **EMA Slopes**: To understand the trend of each EMA, the script compares the current value of each EMA to its value in the previous bar: - For the 20-period EMA, the script checks if today’s EMA value is higher than yesterday’s EMA value. - This process is repeated for the 50-period and 200-period EMAs. - If today’s EMA value is greater than yesterday’s value, the slope is positive (upward). - If today’s EMA value is not greater (it is either equal to or less than yesterday’s value), the slope is not positive. #### 4. Evaluating All Slopes - **All Slopes Positive Condition**: The script combines the results of the individual slope checks into a single condition. It uses a logical "AND" operation: - The condition will be `true` only if all three EMAs (20, 50, and 200) have positive slopes. - If any one of the EMAs does not have a positive slope, the condition will be `false`. #### 5. Coloring the Bars - **Bar Coloring Logic**: Based on the above condition, the script decides the color of each bar on the chart: - If all slopes are positive (condition is `true`), the bar is colored green. - If any slope is not positive (condition is `false`), the bar is colored red. - **Visual Cue**: This provides a quick, visual indication to traders: - Green bars suggest that the market is in an upward trend across all three EMAs, which might indicate a strong bullish trend. - Red bars suggest that the trend is not uniformly upward, which could be a sign of weakening momentum or a potential reversal. #### 6. Alerts - **Alert Conditions**: The script also allows for alert conditions to be set based on the slope analysis: - An alert can be triggered when all EMA slopes are positive. This might be useful for traders who want to be notified when the market shows strong upward momentum. ### Summary - The script essentially takes the market data and applies three different EMAs to it, each with a different time frame. - It then checks the direction (slope) of each of these EMAs to determine if they are all trending upwards. - If they are, the script colors the bar green, signaling a potentially strong bullish trend. - If any of the EMAs is not trending upwards, it colors the bar red, indicating a potential issue with the strength of the trend. This approach helps traders quickly assess market conditions based on multiple EMAs, providing a clearer picture of the overall trend across different time frames.
Pine Script® 인디케이터
Uptrick의
1