지금 시작

지표 및 전략

Mercury Retrograde — Daily boxes & bottom % (stable v6)水星逆行のアノマリー検証。対象は日経225の過去5年の値動き。水星逆行開始時の終値と水星逆行終了時の終値を比較。上昇率・下落率に応じて色分け。 Verification of Mercury Retrograde Anomalies. Subject: Nikkei 225 price movements over the past five years. Comparing closing prices at the start and end of Mercury retrograde periods. Color-coded based on percentage increase/decrease.
Pine Script® 인디케이터
neco33의
Financial-Conditions Brake Index (FCBI) — US10Y brake on USIRYYFinancial-Conditions Brake Index (FCBI) – US10Y Brake on USIRYY Concept The Financial-Conditions Brake Index (FCBI) measures how U.S. long-term yields (US10Y) interact with the Federal Funds Rate (USINTR) and inflation (CPI YoY) to shape real-rate conditions (USIRYY). It visualizes whether the bond market is tightening or loosening overall financial conditions relative to the Federal Reserve’s policy stance. Formula FCBI = (US10Y) − (USINTR) − (CPI YoY) How It Works The FCBI expresses the difference between the long-term yield curve and short-term policy rates, adjusted for inflation. It shows whether the long end of the curve is amplifying or counteracting the Fed’s stance. FCBI > +2 → Strong brake → Long yields remain elevated despite easing → tight conditions → recession delayed. FCBI +1 to +2 → Mild brake → Financial transmission slower; lag ≈ 12–18 months. FCBI 0 to +1 → Neutral → Typical early post-cut environment. FCBI < 0 → Accelerator → Long yields and inflation expectations falling → liquidity flows freely → recession often follows within 6–14 months. How to Read the Chart Blue line (FCBI) shows the strength of the financial brake. Red line (USIRYY) represents the real yield baseline. Recession shading (gray) marks NBER recessions for comparison. FCBI < USIRYY → Brake engaged → financial conditions tighter than real-rate baseline. FCBI > USIRYY → Brake released → long end easing faster than policy → liquidity surge → late-cycle setup. Historically, U.S. recessions begin on average about 14 months after the first Fed rate cut, and a decline of the FCBI below zero often precedes that window. Practical Use Use the FCBI to identify when policy transmission is blocked (brake engaged) or flowing (brake released). Cross-check with yield-curve inversions, Fed policy shifts, and inflation expectations to estimate macro timing windows. Current Example (Oct 2025) FCBI ≈ −3.1, USIRYY ≈ +3.0 → Brake still engaged. Once FCBI rises above USIRYY and crosses positive, it signals the “brake released” phase — historically the final liquidity surge before a U.S. recession. Summary FCBI shows how tight the brake is. USIRYY shows how fast the car is moving. When FCBI rises above USIRYY, the brake is released — liquidity accelerates and the historical recession countdown begins.
Pine Script® 인디케이터
AMTrader의
Strong PivotsThis finds pivots based on your inputs (number of candles back and forward that are above or below the range of the potential pivot points) and then optionally changes the color to help you visually identify the pivot. You can also specify pivots as strong pivots if they reverse in 1 time segment beyond a certain percentage (wick % of full candle range). For example, if the pivot is at a high point but has a green body candle and a wick > 35% of the candle, it will change the body color to red to help visually understand that the candle can be considered a strong part of the downtrend, regardless of it closing green. This will help your mind interpret the top pivot candle as part of the potential trend reversal for the following candles and could even be used as part of your strategy ruleset.
Pine Script® 인디케이터
supernat10의
Candle Size MonitorCandle Size Monitor – Description Update 27.10.25 Objective Volatility Assessment The Candle Size Monitor helps traders assess actual market movement—regardless of whether candles appear visually large or small on the chart. It supports evaluating whether your planned trade structure (e.g., stop-loss, take-profit) aligns with current volatility. Key Features Volatility Analysis: Calculates the average candle size (difference between high and low) over a user-defined number of candles. Identifies the largest candle in the selected period. Displays results in a compact table on the chart. Exchange Rate Integration (optional): Shows the current USD-EUR exchange rate (formatted with German-style comma and four decimal places). Useful for traders in USD-denominated markets who apply EUR-based risk management rules. Customizable Display: Text Size: Small, medium, or large. Colors: Customizable text and background colors. Table Position: Top/bottom left/right. Number of Candles: User-defined (default: 20). Dynamic Updates: The table updates with each new bar. The exchange rate is fetched in real-time from OANDA:EURUSD. Settings and Translations Settings Anzahl Kerzen → Number of Candles (Number of candles for calculation, default: 20). Textgröße → Text Size (Text size in the table: small, medium, large). Textfarbe → Text Color (Text color, default: white). Hintergrundfarbe → Background Color (Background color of the table, default: black). Position → Position (Table position: Top Left, Top Right, Bottom Left, Bottom Right). Wechselkurs anzeigen (USD → EUR) → Show Exchange Rate (USD → EUR) (Option to display the exchange rate). Table Contents and Translations The table displays the following information (with German formatting): Ø Größe (N): English: "Avg Size (N): " (Average candle size over the last N candles). Example: "Ø Größe (20): 15,3" → "Avg Size (20): 15.3". Größte Kerze: English: "Largest Candle: " (Largest candle size in the selected period). Example: "Größte Kerze: 42,7" → "Largest Candle: 42.7". 1 USD = € (only if enabled) English: "1 USD = EUR" (Current USD-EUR exchange rate, formatted with a comma). Example: "1 USD = 0,9234 €" → "1 USD = 0.9234 EUR".
Pine Script® 인디케이터
kp_eu_de의
HoneG_BJVH 軽量化版v1 ザオプションのワンタッチ取引向けのサブチャート用ツールver1です 仮想通貨のpips換算時、変換式がイレギュラーなので、 ザオプションの現行画面仕様に合わせて作りました このバージョンはテーブルを20列確保して、過去20足の勝敗も表現しています。 This is version 1 of the subchart tool for The Option's One-Touch trading. Since the conversion formula for cryptocurrency pips is irregular, it was created to match The Option's current screen specifications. This version reserves 20 columns in the table and also displays the win/loss results for the past 20 candles.
Pine Script® 인디케이터
TVYAMA의
Dow Jones Trading System with PivotsThis TradingView indicator, tailored for the 30-minute Dow Jones (^DJI) chart, supports DIA options trading with a trend-following approach. It features a 30-period SMA (blue) and a 60-period SMA (red), with an optional 90-period SMA (orange) drawn from rauItrades' Dow SMA outfit. A bullish crossover (30 SMA > 60 SMA) displays a green "BUY" triangle below the bar for potential DIA longs, while a bearish crossunder (30 SMA < 60 SMA) shows a red "SELL" triangle above for shorts or exits. The background turns green (bullish) or red (bearish) to indicate trend bias. Pivot points highlight recent highs (orange circles) and lows (purple circles) for support/resistance, using a 5-bar lookback. Alerts notify for crossovers.
Pine Script® 인디케이터
DarkMoneyMusic의
TI65**TI65 (Trend Intensity 65)** is a technical indicator designed to measure the strength and momentum of a trend over two distinct periods. It compares a short-term 7-period simple moving average (SMA) with a long-term 65-period SMA, producing a ratio that helps traders identify shifts in market momentum and trend direction. - When the **TI65 value is greater than 1**, it indicates that the short-term moving average is above the long-term average, suggesting increasing momentum and a potentially bullish trend. - When the **TI65 value drops below 1**, it signals weakening short-term momentum relative to the longer-term trend, often interpreted as a bearish or consolidating phase. This indicator can be applied to both price and volume data, making it useful for identifying periods of strong volume surges or price movements. By observing changes in the TI65 ratio, traders can pinpoint low-risk entry points for trend-following strategies and quickly recognize periods of market transition. TI65 is commonly used by momentum and breakout traders for screening strong candidates and confirming the sustainability of ongoing trends. It is simple, effective, and easily implemented via custom scripts on popular platforms like TradingView.
Pine Script® 인디케이터
echanxyz의
Ehlers Even Better Sinewave (EBSW)# EBSW: Ehlers Even Better Sinewave ## Overview and Purpose The Ehlers Even Better Sinewave (EBSW) indicator, developed by John Ehlers, is an advanced cycle analysis tool. This implementation is based on a common interpretation that uses a cascade of filters: first, a High-Pass Filter (HPF) to detrend price data, followed by a Super Smoother Filter (SSF) to isolate the dominant cycle. The resulting filtered wave is then normalized using an Automatic Gain Control (AGC) mechanism, producing a bounded oscillator that fluctuates between approximately +1 and -1. It aims to provide a clear and responsive measure of market cycles. ## Core Concepts * **Detrending (High-Pass Filter):** A 1-pole High-Pass Filter removes the longer-term trend component from the price data, allowing the indicator to focus on cyclical movements. * **Cycle Smoothing (Super Smoother Filter):** Ehlers' Super Smoother Filter is applied to the detrended data to further refine the cycle component, offering effective smoothing with relatively low lag. * **Wave Generation:** The output of the SSF is averaged over a short period (typically 3 bars) to create the primary "wave". * **Automatic Gain Control (AGC):** The wave's amplitude is normalized by dividing it by the square root of its recent power (average of squared values). This keeps the oscillator bounded and responsive to changes in volatility. * **Normalized Oscillator:** The final output is a single sinewave-like oscillator. ## Common Settings and Parameters | Parameter | Default | Function | When to Adjust | | ----------- | ------- | --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- | | Source | close | Price data used for calculation. | Typically `close`, but `hlc3` or `ohlc4` can be used for a more comprehensive price representation. | | HP Length | 40 | Lookback period for the 1-pole High-Pass Filter used for detrending. | Shorter periods make the filter more responsive to shorter cycles; longer periods focus on longer-term cycles. Adjust based on observed cycle characteristics. | | SSF Length | 10 | Lookback period for the Super Smoother Filter used for smoothing the detrended cycle component. | Shorter periods result in a more responsive (but potentially noisier) wave; longer periods provide more smoothing. | **Pro Tip:** The `HP Length` and `SSF Length` parameters should be tuned based on the typical cycle lengths observed in the market and the desired responsiveness of the indicator. ## Calculation and Mathematical Foundation **Simplified explanation:** 1. Remove the trend from the price data using a 1-pole High-Pass Filter. 2. Smooth the detrended data using a Super Smoother Filter to get a clean cycle component. 3. Average the output of the Super Smoother Filter over the last 3 bars to create a "Wave". 4. Calculate the average "Power" of the Super Smoother Filter output over the last 3 bars. 5. Normalize the "Wave" by dividing it by the square root of the "Power" to get the final EBSW value. **Technical formula (conceptual):** 1. **High-Pass Filter (HPF - 1-pole):** `angle_hp = 2 * PI / hpLength` `alpha1_hp = (1 - sin(angle_hp)) / cos(angle_hp)` `HP = (0.5 * (1 + alpha1_hp) * (src - src )) + alpha1_hp * HP ` 2. **Super Smoother Filter (SSF):** `angle_ssf = sqrt(2) * PI / ssfLength` `alpha2_ssf = exp(-angle_ssf)` `beta_ssf = 2 * alpha2_ssf * cos(angle_ssf)` `c2 = beta_ssf` `c3 = -alpha2_ssf^2` `c1 = 1 - c2 - c3` `Filt = c1 * (HP + HP )/2 + c2*Filt + c3*Filt ` 3. **Wave Generation:** `WaveVal = (Filt + Filt + Filt ) / 3` 4. **Power & Automatic Gain Control (AGC):** `Pwr = (Filt^2 + Filt ^2 + Filt ^2) / 3` `EBSW_SineWave = WaveVal / sqrt(Pwr)` (with check for Pwr == 0) > 🔍 **Technical Note:** The combination of HPF and SSF creates a form of band-pass filter. The AGC mechanism ensures the output remains scaled, typically between -1 and +1, making it behave like a normalized oscillator. ## Interpretation Details * **Cycle Identification:** The EBSW wave shows the current phase and strength of the dominant market cycle as filtered by the indicator. Peaks suggest cycle tops, and troughs suggest cycle bottoms. * **Trend Reversals/Momentum Shifts:** When the EBSW wave crosses the zero line, it can indicate a potential shift in the short-term cyclical momentum. * Crossing up through zero: Potential start of a bullish cyclical phase. * Crossing down through zero: Potential start of a bearish cyclical phase. * **Overbought/Oversold Levels:** While normalized, traders often establish subjective or statistically derived overbought/oversold levels (e.g., +0.85 and -0.85, or other values like +0.7, +0.9). * Reaching above the overbought level and turning down may signal a potential cyclical peak. * Falling below the oversold level and turning up may signal a potential cyclical trough. ## Limitations and Considerations * **Parameter Sensitivity:** The indicator's performance depends on tuning `hpLength` and `ssfLength` to prevailing market conditions. * **Non-Stationary Markets:** In strongly trending markets with weak cyclical components, or in very choppy non-cyclical conditions, the EBSW may produce less reliable signals. * **Lag:** All filtering introduces some lag. The Super Smoother Filter is designed to minimize this for its degree of smoothing, but lag is still present. * **Whipsaws:** Rapid oscillations around the zero line can occur in volatile or directionless markets. * **Requires Confirmation:** Signals from EBSW are often best confirmed with other forms of technical analysis (e.g., price action, volume, other non-correlated indicators). ## References * Ehlers, J. F. (2002). *Rocket Science for Traders: Digital Signal Processing Applications*. John Wiley & Sons. * Ehlers, J. F. (2013). *Cycle Analytics for Traders: Advanced Technical Trading Concepts*. John Wiley & Sons.
Pine Script® 인디케이터
mihakralj의
Bollinger Band Spread (Dunk)Bollinger Band Width measures the distance between the upper and lower Bollinger Bands. It reflects market volatility—wider bands mean higher volatility, narrower bands mean lower volatility. When the width contracts to low levels, it can signal price consolidation and potential breakouts. When the width expands, it indicates active markets or strong trends. Traders use it to spot volatility squeezes, confirm breakouts, and compare relative volatility across assets or timeframes.
Pine Script® 인디케이터
dunk-devs의
Ehlers Phasor Analysis (PHASOR)# PHASOR: Phasor Analysis (Ehlers) ## Overview and Purpose The Phasor Analysis indicator, developed by John Ehlers, represents an advanced cycle analysis tool that identifies the phase of the dominant cycle component in a time series through complex signal processing techniques. This sophisticated indicator uses correlation-based methods to determine the real and imaginary components of the signal, converting them to a continuous phase angle that reveals market cycle progression. Unlike traditional oscillators, the Phasor provides unwrapped phase measurements that accumulate continuously, offering unique insights into market timing and cycle behavior. ## Core Concepts * **Complex Signal Analysis** — Uses real and imaginary components to determine cycle phase * **Correlation-Based Detection** — Employs Ehlers' correlation method for robust phase estimation * **Unwrapped Phase Tracking** — Provides continuous phase accumulation without discontinuities * **Anti-Regression Logic** — Prevents phase angle from moving backward under specific conditions Market Applications: * **Cycle Timing** — Precise identification of cycle peaks and troughs * **Market Regime Analysis** — Distinguishes between trending and cycling market conditions * **Turning Point Detection** — Advanced warning system for potential market reversals ## Common Settings and Parameters | Parameter | Default | Function | When to Adjust | |-----------|---------|----------|----------------| | Period | 28 | Fixed cycle period for correlation analysis | Match to expected dominant cycle length | | Source | Close | Price series for phase calculation | Use typical price or other smoothed series | | Show Derived Period | false | Display calculated period from phase rate | Enable for adaptive period analysis | | Show Trend State | false | Display trend/cycle state variable | Enable for regime identification | ## Calculation and Mathematical Foundation **Technical Formula:** **Stage 1: Correlation Analysis** For period $n$ and source $x_t$: Real component correlation with cosine wave: $$R = \frac{n \sum x_t \cos\left(\frac{2\pi t}{n}\right) - \sum x_t \sum \cos\left(\frac{2\pi t}{n}\right)}{\sqrt{D_{cos}}}$$ Imaginary component correlation with negative sine wave: $$I = \frac{n \sum x_t \left(-\sin\left(\frac{2\pi t}{n}\right)\right) - \sum x_t \sum \left(-\sin\left(\frac{2\pi t}{n}\right)\right)}{\sqrt{D_{sin}}}$$ where $D_{cos}$ and $D_{sin}$ are normalization denominators. **Stage 2: Phase Angle Conversion** $$\theta_{raw} = \begin{cases} 90° - \arctan\left(\frac{I}{R}\right) \cdot \frac{180°}{\pi} & \text{if } R eq 0 \\ 0° & \text{if } R = 0, I > 0 \\ 180° & \text{if } R = 0, I \leq 0 \end{cases}$$ **Stage 3: Phase Unwrapping** $$\theta_{unwrapped}(t) = \theta_{unwrapped}(t-1) + \Delta\theta$$ where $\Delta\theta$ is the normalized phase difference. **Stage 4: Ehlers' Anti-Regression Condition** $$\theta_{final}(t) = \begin{cases} \theta_{final}(t-1) & \text{if regression conditions met} \\ \theta_{unwrapped}(t) & \text{otherwise} \end{cases}$$ **Derived Calculations:** Derived Period: $P_{derived} = \frac{360°}{\Delta\theta_{final}}$ (clamped to ) Trend State: $$S_{trend} = \begin{cases} 1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| \geq 90° \\ -1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| < 90° \\ 0 & \text{if } \Delta\theta > 6° \end{cases}$$ > 🔍 **Technical Note:** The correlation-based approach provides robust phase estimation even in noisy market conditions, while the unwrapping mechanism ensures continuous phase tracking across cycle boundaries. ## Interpretation Details * **Phasor Angle (Primary Output):** - **+90°**: Potential cycle peak region - **0°**: Mid-cycle ascending phase - **-90°**: Potential cycle trough region - **±180°**: Mid-cycle descending phase * **Phase Progression:** - Continuous upward movement → Normal cycle progression - Phase stalling → Potential cycle extension or trend development - Rapid phase changes → Cycle compression or volatility spike * **Derived Period Analysis:** - Period < 10 → High-frequency cycle dominance - Period 15-40 → Typical swing trading cycles - Period > 50 → Trending market conditions * **Trend State Variable:** - **+1**: Long trend conditions (slow phase change in extreme zones) - **-1**: Short trend or consolidation (slow phase change in neutral zones) - **0**: Active cycling (normal phase change rate) ## Applications * **Cycle-Based Trading:** - Enter long positions near -90° crossings (cycle troughs) - Enter short positions near +90° crossings (cycle peaks) - Exit positions during mid-cycle phases (0°, ±180°) * **Market Timing:** - Use phase acceleration for early trend detection - Monitor derived period for cycle length changes - Combine with trend state for regime-appropriate strategies * **Risk Management:** - Adjust position sizes based on cycle clarity (derived period stability) - Implement different risk parameters for trending vs. cycling regimes - Use phase velocity for stop-loss placement timing ## Limitations and Considerations * **Parameter Sensitivity:** - Fixed period assumption may not match actual market cycles - Requires cycle period optimization for different markets and timeframes - Performance degrades when multiple cycles interfere * **Computational Complexity:** - Correlation calculations over full period windows - Multiple mathematical transformations increase processing requirements - Real-time implementation requires efficient algorithms * **Market Conditions:** - Most effective in markets with clear cyclical behavior - May provide false signals during strong trending periods - Requires sufficient historical data for correlation analysis Complementary Indicators: * MESA Adaptive Moving Average (cycle-based smoothing) * Dominant Cycle Period indicators * Detrended Price Oscillator (cycle identification) ## References 1. Ehlers, J.F. "Cycle Analytics for Traders." Wiley, 2013. 2. Ehlers, J.F. "Cybernetic Analysis for Stocks and Futures." Wiley, 2004.
Pine Script® 인디케이터
mihakralj의
COT Index Indicator 1) One‑liner My version of the OTC COT Index indicator: a 0–120 oscillator built from CFTC COT data that shows where Commercial, Noncommercial, and Nonreportable net positions sit relative to recent extremes. 2) Short paragraph This is my version of the OTC COT Index indicator. It converts CFTC Commitments of Traders (COT) net positions into a normalized 0–120 oscillator for each trader group—Commercials, Noncommercials, and Nonreportables—so you can quickly see when positioning is near recent highs or lows. Data comes from TradingView’s official COT library and supports both “Futures Only” and “Futures and Options” reports. 3) Compact bullets What: My version of the OTC COT Index indicator Why: Quickly spot when trader groups are near positioning extremes Data: CFTC COT via TradingView/LibraryCOT/2; Futures Only or Futures & Options How: Index = 120 × (Current − Min) ÷ (Max − Min) over a configurable lookback Plots: Commercials (blue), Noncommercials (orange), Nonreportables (red) Lines: Overbought, Midline, Oversold, optional 0/100, upper/lower bounds Note: Values are relative to the chosen window; not trading advice 4) Publication‑ready (sections) Overview My version of the OTC COT Index indicator. It turns CFTC COT positioning into a 0–120 oscillator per trader group (Commercials, Noncommercials, Nonreportables) to highlight relative extremes. Data source CFTC Commitments of Traders via TradingView’s official library (TradingView/LibraryCOT/2). Supports “Futures Only” and “Futures and Options.” Method Net positions = Longs − Shorts. Index = 120 × (Current Net − Min(Net, Lookback)) ÷ (Max(Net, Lookback) − Min(Net, Lookback)). Inputs Weeks Look Back (normalization window) Weeks Look Back for Historical Hi/Los (longer reference) Report Type selection Visuals Three indexes by trader group, plus reference levels (OB/OS, Midline, optional 0/100). Notes Some symbols map to specific CFTC codes for reliability. If no relevant COT data exists for the symbol, the script reports it clearly. If you want this adapted to a specific platform’s character limits (e.g., TradingView’s publish dialog), tell me the target length and I’ll trim it to fit.
Pine Script® 인디케이터
dragos_cocos_dev의