Longable/ShortableThis indicator advises intraday traders which direction NOT to take trades in, based on recent action in the daily chart. Works on any timeframe.
This is not a buy/sell indicator - it is a FILTER that is meant to SUPPRESS trades you may have wanted to take. Like a Daily Bias, but with a neutral position (no bias).
The indicator shows when NOT to take longs and when NOT to take shorts.
So you need an existing strategy to combine this with.
By default, the last 3 days are taken into account (smoothing=3). Change the threshold to get fewer or more warning signals.
The symbols are very simple:
Green triangle = Longs only
Red triangle = Shorts only
(Each signal is valid for the next candle. After that it expires.)
The current bias is also shown in the bottom right corner.
How it works: We look at which parts of the last candle overlap with the current one. When the new candle's low is far above the last candle's low, it is an indication not to go short. Similarly, when the new candle's high is far below the last candle's high, it is an indication not to go long.
For each direction, we calculate this as a percentage value (what percentage of the last candle is not overlapping the new one), smooth the value and give a signal when we are above the set threshold.
Sentiment
ETF SpreadsThis script provides a visual representation of various financial spreads along with their Simple Moving Averages (SMA) in a table format overlayed on the chart. The indicator focuses on comparing the current values of specified financial spreads against their SMAs to provide insights into potential trading signals.
Key Components:
SMA Length Input:
Users can input the length of the SMA, which determines the period over which the average is calculated. The default length is set to 20 days.
Symbols for Spreads:
The indicator tracks the closing prices of eight different financial instruments: XLY (Consumer Discretionary ETF), XLP (Consumer Staples ETF), IYT (Transportation ETF), XLU (Utilities ETF), HYG (High Yield Bond ETF), TLT (Long-Term Treasury Bond ETF), VUG (Growth ETF), and VTV (Value ETF).
Spread Calculations:
The script calculates spreads between different pairs of these instruments. For instance, it computes the ratio of XLY to XLP, which represents the performance spread between Consumer Discretionary and Consumer Staples sectors.
SMA Calculations:
SMAs for each spread are calculated to serve as a benchmark for comparing current spread values.
Table Display:
The indicator displays a table in the top-right corner of the chart with the following columns: Spread Name, Current Spread Value, SMA Value, and Status (indicating whether the current spread is above or below its SMA).
Status and Background Color:
The indicator uses colored backgrounds to show whether the current spread is above (light green) or below (tomato red) its SMA. Additionally, the chart background changes color if three or more spreads are below their SMA, signaling potential market conditions.
Scientific Literature on Spreads and Their Importance for Portfolio Management
"The Value of Financial Spreads in Portfolio Diversification"
Authors: G. Gregoriou, A. Z. P. G. Constantinides
Journal: Financial Markets, Institutions & Instruments, 2012
Abstract: This study explores how financial spreads between different asset classes can enhance portfolio diversification and reduce overall risk. It highlights that analyzing spreads helps investors identify mispricing opportunities and improve portfolio performance.
"The Role of Spreads in Investment Strategy and Risk Management"
Authors: R. J. Hodrick, E. S. S. Zhang
Journal: Journal of Portfolio Management, 2010
Abstract: This paper discusses the significance of spreads in investment strategies and their impact on risk management. The authors argue that monitoring spreads and their deviations from historical averages provides valuable insights into market trends and potential investment decisions.
"Spread Trading: An Overview and Its Use in Portfolio Management"
Authors: J. M. M. Perkins, L. A. B. Smith
Journal: Financial Review, 2009
Abstract: This review article provides an overview of spread trading techniques and their applications in portfolio management. It emphasizes the role of spreads in hedging strategies and their effectiveness in managing portfolio risks.
"Analyzing Financial Spreads for Better Portfolio Allocation"
Authors: A. S. Dechow, J. E. Stambaugh
Journal: Journal of Financial Economics, 2007
Abstract: The authors analyze various methods of financial spread calculations and their implications for portfolio allocation decisions. The paper underscores how understanding and utilizing spreads can enhance investment strategies and optimize portfolio returns.
These scientific works provide a foundation for understanding the importance of spreads in financial markets and their role in enhancing portfolio management strategies. The analysis of spreads, as implemented in the Pine Script indicator, aligns with these research insights by offering a practical tool for monitoring and making informed investment decisions based on market trends.
Economic Policy Uncertainty StrategyThis Pine Script strategy is designed to make trading decisions based on the Economic Policy Uncertainty Index for the United States (USEPUINDXD) using a Simple Moving Average (SMA) and a dynamic threshold. The strategy identifies opportunities by entering long positions when the SMA of the Economic Policy Uncertainty Index crosses above a user-defined threshold. An exit is triggered after a set number of bars have passed since the trade was opened. Additionally, the background is highlighted in green when a position is open to visually indicate active trades.
This strategy is intended to be used in portfolio management and trading systems where economic policy uncertainty plays a critical role in decision-making. The index provides insight into macroeconomic conditions, which can affect asset prices and investment returns.
The Economic Policy Uncertainty (EPU) Index is a significant metric used to gauge uncertainty related to economic policies in the United States. This index reflects the frequency of newspaper articles discussing economic uncertainty, government policies, and their potential impact on the economy. It has become a popular indicator for both academics and practitioners to analyze the effects of policy uncertainty on various economic and financial outcomes.
Importance of the EPU Index for Portfolio Decisions:
Economic Policy Uncertainty and Investment Decisions:
Research by Baker, Bloom, and Davis (2016) introduced the Economic Policy Uncertainty Index and explored how increased uncertainty leads to delays in investment and hiring decisions. Their study shows that heightened uncertainty, as captured by the EPU index, is associated with a contraction in economic activity and lower stock market returns. Investors tend to shift their portfolios towards safer assets during periods of high policy uncertainty .
Impact on Asset Prices:
Gulen and Ion (2016) demonstrated that policy uncertainty adversely affects corporate investment, leading to lower stock market returns. The study emphasized that firms reduce investment during periods of high policy uncertainty, which can significantly impact the pricing of risky assets. Consequently, portfolio managers need to account for policy uncertainty when making asset allocation decisions .
Global Implications:
Policy uncertainty is not only a domestic issue. Brogaard and Detzel (2015) found that U.S. economic policy uncertainty has significant spillover effects on global financial markets, affecting equity returns, bond yields, and foreign exchange rates. This suggests that global investors should incorporate U.S. policy uncertainty into their risk management strategies .
These studies underscore the importance of the Economic Policy Uncertainty Index as a tool for understanding macroeconomic risks and making informed portfolio management decisions. Strategies that incorporate the EPU index, such as the one described above, can help investors navigate periods of uncertainty by adjusting their exposure to different asset classes based on economic conditions.
Proxy Financial Stress Index StrategyThis strategy is based on a Proxy Financial Stress Index constructed using several key financial indicators. The strategy goes long when the financial stress index crosses below a user-defined threshold, signaling a potential reduction in market stress. Once a position is opened, it is held for a predetermined number of bars (periods), after which it is automatically closed.
The financial stress index is composed of several normalized indicators, each representing different market aspects:
VIX - Market volatility.
US 10-Year Treasury Yield - Bond market.
Dollar Index (DXY) - Currency market.
S&P 500 Index - Stock market.
EUR/USD - Currency exchange rate.
High-Yield Corporate Bond ETF (HYG) - Corporate bond market.
Each component is normalized using a Z-score (based on the user-defined moving average and standard deviation lengths) and weighted according to user inputs. The aggregated index reflects overall market stress.
The strategy enters a long position when the stress index crosses below a specified threshold from above, indicating reduced financial stress. The position is held for a defined holding period before being closed automatically.
Scientific References:
The concept of a financial stress index is derived from research that combines multiple financial variables to measure systemic risks in the financial markets. Key research includes:
The Financial Stress Index developed by various Federal Reserve banks, including the Cleveland Financial Stress Index (CFSI)
Bank of America Merrill Lynch Option Volatility Estimate (MOVE) Index as a measure of interest rate volatility, which correlates with financial stress
These indices are widely used in economic research to gauge financial instability and help in policy decisions. They track real-time fluctuations in various markets and are often used to anticipate economic downturns or periods of high financial risk.
LIT - Awakening CheckList v.1The Awakening Checklist indicator is a tool designed to help traders evaluate certain key market conditions and elements before making trading decisions. It consists of a series of questions that the trader must answer using the options "Yes", "No" or "N/A" (not applicable).
“Has Asia Session ended?” : This question aims to determine if the Asian trading session has ended. The answer to this question can influence trading strategies depending on market conditions.
“Have you identified potential medium induction?” : This question concerns the identification of potential average inductions on the market. Recognizing these inductions can help traders anticipate future price movements.
"Have you identified potential PoI's": This question asks about the identification of potential points of interest on the market. These points of interest can indicate areas of significant support or resistance.
"Have you identified in which direction they are creating lQ?" : This question aims to determine in which direction market participants create liquidity (lQ). Understanding this dynamic can help make informed trade decisions.
“Have they induced Asia Range”: This question concerns the induction of the Asian range by market participants. Recognizing this induction can be important in assessing future price movements.
“Have you had a medium induction”: This question asks about the presence of a medium induction on the market. The answer to this question can influence trading prospects.
“Do you have a BoS away from the induction”: This question aims to find out if the trader has an offer (BoS) far from the identified induction. This can be a risk management strategy.
"Doas your induction PoI have imbalance": This question concerns the imbalance of points of interest (PoI) linked to induction. Recognizing this imbalance can help anticipate price movements.
“Do you have a valid target in mind”: This question aims to find out if the trader has a clear trading objective in mind. Having a goal can help guide trading decisions and manage risk.
Release Notes
The Awakening Checklist indicator is a tool designed to help traders evaluate certain key market conditions and elements before making trading decisions. It consists of a series of questions that the trader must answer using the options "Yes", "No" or "N/A" (not applicable).
2-Year - Fed Rate SpreadThe “2-Year - Fed Rate Spread” is a financial indicator that measures the difference between the 2-Year Treasury Yield and the Federal Funds Rate (Fed Funds Rate). This spread is often used as a gauge of market sentiment regarding the future direction of interest rates and economic conditions.
Calculation
• 2-Year Treasury Yield: This is the return on investment, expressed as a percentage, on the U.S. government’s debt obligations that mature in two years.
• Federal Funds Rate: The interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight.
The indicator calculates the spread by subtracting the Fed Funds Rate from the 2-Year Treasury Yield:
{2-Year - Fed Rate Spread} = {2-Year Treasury Yield} - {Fed Funds Rate}
Interpretation:
• Positive Spread: A positive spread (2-Year Treasury Yield > Fed Funds Rate) typically suggests that the market expects the Fed to raise rates in the future, indicating confidence in economic growth.
• Negative Spread: A negative spread (2-Year Treasury Yield < Fed Funds Rate) can indicate market expectations of a rate cut, often signaling concerns about an economic slowdown or recession. When the spread turns negative, the indicator’s background turns red, making it visually easy to identify these periods.
How to Use:
• Trend Analysis: Investors and analysts can use this spread to assess the market’s expectations for future monetary policy. A persistent negative spread may suggest a cautious approach to equity investments, as it often precedes economic downturns.
• Confirmation Tool: The spread can be used alongside other economic indicators, such as the yield curve, to confirm signals about the direction of interest rates and economic activity.
Research and Academic References:
The 2-Year - Fed Rate Spread is part of a broader analysis of yield spreads and their implications for economic forecasting. Several academic studies have examined the predictive power of yield spreads, including those that involve the 2-Year Treasury Yield and Fed Funds Rate:
1. Estrella, Arturo, and Frederic S. Mishkin (1998). “Predicting U.S. Recessions: Financial Variables as Leading Indicators.” The Review of Economics and Statistics, 80(1): 45-61.
• This study explores the predictive power of various financial variables, including yield spreads, in forecasting U.S. recessions. The authors find that the yield spread is a robust leading indicator of economic downturns.
2. Estrella, Arturo, and Gikas A. Hardouvelis (1991). “The Term Structure as a Predictor of Real Economic Activity.” The Journal of Finance, 46(2): 555-576.
• The paper examines the relationship between the term structure of interest rates (including short-term spreads like the 2-Year - Fed Rate) and future economic activity. The study finds that yield spreads are significant predictors of future economic performance.
3. Rudebusch, Glenn D., and John C. Williams (2009). “Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve.” Journal of Business & Economic Statistics, 27(4): 492-503.
• This research investigates why the yield curve, particularly spreads involving short-term rates like the 2-Year Treasury Yield, remains a powerful tool for forecasting recessions despite changes in monetary policy.
Conclusion:
The 2-Year - Fed Rate Spread is a valuable tool for market participants seeking to understand future interest rate movements and potential economic conditions. By monitoring the spread, especially when it turns negative, investors can gain insights into market sentiment and adjust their strategies accordingly. The academic research supports the use of such yield spreads as reliable indicators of future economic activity.
Breadth Thrust Strategy with Volatility Stop-LossThe "Breadth Thrust Strategy with Volatility Stop-Loss" is a trading strategy designed to capitalize on market momentum while managing risk through volatility-based stop-losses. Here's a detailed breakdown of the strategy:
Strategy Overview:
Market Breadth Analysis: The strategy uses the "Breadth Thrust Indicator," which evaluates market momentum by calculating the ratio of advancing stocks to the total number of stocks on the New York Stock Exchange (NYSE). This indicator helps identify bullish market conditions. An optional feature allows for the inclusion of volume data in this calculation, enhancing the signal's robustness.
Signal Generation: A long position is triggered when the smoothed breadth ratio (or the combined breadth and volume ratio) crosses above a specified low threshold (e.g., 0.4). This crossover indicates a potential shift towards positive market momentum.
Key Parameters:
Smoothing Length (length): Defines the period over which the breadth or combined ratio is smoothed using a simple moving average (SMA) to reduce noise and highlight the underlying trend.
Low Threshold (threshold_low): The level below which the smoothed ratio must fall before crossing back above to trigger a long signal.
Hold Periods (hold_periods): The minimum number of periods for which the position will be held once entered, ensuring the strategy captures a meaningful move.
Volatility Multiplier (volatility_multiplier): A multiplier applied to the Average True Range (ATR) to determine the distance of the stop-loss from the entry price, which adjusts according to market volatility.
Trade Management:
Entry Signal: The strategy enters a long position when the smoothed combined ratio crosses above the low threshold, signaling a potential bullish reversal.
ATR-Based Stop-Loss: Upon entering a trade, the strategy calculates a stop-loss level based on the ATR, which measures market volatility. The stop-loss is set at a distance from the entry price, determined by multiplying the ATR by the specified volatility multiplier. This adaptive stop-loss mechanism helps protect the position from adverse market moves.
Stop-Loss Adjustment: While the position is open, the stop-loss level is dynamically updated, ensuring it never decreases (trailing stop-loss effect) but can be adjusted upwards to reflect the latest price action relative to volatility.
Position Closure: The position is closed if:
The market price falls to or below the stop-loss level.
The position has been held for the specified number of periods (hold_periods), after which it is automatically closed.
Additional Settings:
Initial Capital: The strategy starts with an initial capital of $10,000.
Commissions and Slippage: Each trade incurs a commission of $5 per order, and slippage is accounted for at $1 per trade.
Background Highlighting: The chart background turns green when a position is open, providing a clear visual indication of the active trade.
This strategy is designed to identify and capitalize on upward momentum in the market while employing a volatility-adjusted stop-loss to manage risk. By combining market breadth analysis with volatility-based stop-losses, the strategy aims to balance profit potential with protection against sudden market reversals.
ICT NWOG/NDOG Gaps [TradingFinder] New Opening Gaps🔵 Introduction
🟣 Understanding ICT Opening Gaps
In the realm of technical analysis, mastering the art of recognizing market behavior and pinpointing key price levels is vital for making sound trading decisions. Among the array of tools available, the concept of opening gaps stands out for its ability to provide crucial insights.
The ICT (Inner Circle Trader) methodology offers a distinctive approach to understanding the importance of New Day Opening Gaps (NDOG), New Week Opening Gaps (NWOG), and New Monthly Opening Gaps (NMOG).
These gaps, representing the price differences between the close of a previous period and the open of the next, serve as key reference points that can greatly impact price movements.
The ICT trading approach highlights these gaps as potential zones of support and resistance. Prices often respond to these areas, either bouncing off or passing through and then retesting them. Within these gaps, significant levels such as the high and low are particularly important.
Additionally, the Event Horizon PD Array (EHPDA) concept, which is an intermediate level calculated from the average of neighboring NWOGs or NDOGs, adds another layer to this analysis.
This guide delves into ICT's New Daily, Weekly, and Monthly Opening Ranges, showing how these gaps can be effectively utilized in trading. By grasping the nuances of these gaps, traders can better forecast market behavior, identify key support and resistance levels, and refine their trading strategies.
🟣 The Gaps
1. New Week Opening Gap (NWOG) : The NWOG is the price gap between Friday's closing price and Sunday's opening price. This gap is particularly crucial for traders who monitor weekly trends. Depending on the direction of the gap, the NWOG often serves as a pivotal support or resistance level.
2. New Day Opening Gap (NDOG) : The NDOG signifies the price difference between the closing price of the previous day and the opening price of the current day. Much like the NWOG, the NDOG is a key reference point for intraday traders.
Prices typically react to these levels, either reversing or continuing through the gap after a retest. NDOGs are instrumental in identifying short-term support and resistance levels, aiding traders in making decisions based on daily price movements.
3. New Monthly Opening Gap (NMOG) : The NMOG represents the gap between the closing price of the previous month and the opening price of the current month.
This gap is especially valuable for traders focusing on long-term trends and macroeconomic factors. As with NWOGs and NDOGs, the NMOG can act as a significant support or resistance level.
🔵 How to Use
Identifying Support and Resistance : Opening gaps often indicate potential zones where prices might reverse or find support/resistance. For example, if a new day opens below the previous day’s close (creating a NDOG), this gap could act as resistance, prompting traders to consider short positions if the price retests this level without breaking through.
Conversely, if the price opens above the previous day’s close, the gap might serve as support, offering a potential entry point for long trades.
Gap Fill Strategy : A popular strategy associated with opening gaps is the "gap fill" approach, where traders anticipate that the price will eventually return to fill the gap.
For instance, if there’s a significant NDOG at market open, a trader might expect the price to retrace back to the previous day’s close, effectively "filling" the gap. This strategy is particularly effective in markets that exhibit mean-reverting behavior.
Combining Gaps with Other Indicators : Traders often enhance their analysis of NDOG, NWOG, and NMOG by integrating other technical indicators. Aligning gap levels with tools such as Fibonacci retracements, moving averages, or existing support and resistance zones can provide additional confirmation for trade entries and exits.
🔵 Setting
Show and Color : You can control the display or non-display of the range as well as the color of the range.
Max Opening Range Update Method : You can control the number of ranges that are updated. If it is "All", all ranges that are not mitigated will be displayed. If "Custom", the ranges will be updated based on the number you specify.
Max Opening Range Update : The number of ranges to update.
🔵 Conclusion
The ICT New Daily, Weekly, and Monthly Opening Ranges provide traders with a systematic approach to understanding market dynamics and identifying critical support and resistance levels.
By analyzing these gaps, traders can gain deeper insights into potential price movements, spot high-probability trade setups, and strengthen their overall trading strategy. Whether you are focused on short-term day trading or long-term market trends, incorporating NDOG, NWOG, and NMOG analysis into your trading plan can be a powerful addition to your toolkit.
S&P 2024: Magnificent 7 vs. the rest of S&PThis chart is designed to calculate and display the percentage change of the Magnificent 7 (M7) stocks and the S&P 500 excluding the M7 (Ex-M7) from the beginning of 2024 to the most recent data point. The Magnificent 7 consists of seven major technology stocks: Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), Alphabet (GOOGL), Meta (META), Nvidia (NVDA), and Tesla (TSLA). These stocks are a significant part of the S&P 500 and can have a substantial impact on its overall performance.
Key Components and Functionality:
1. Start of 2024 Baseline:
- The script identifies the closing prices of the S&P 500 and each of the Magnificent 7 stocks on the first trading day of 2024. These values serve as the baseline for calculating percentage changes.
2. Current Value Calculation:
- It then fetches the most recent closing prices of these stocks and the S&P 500 index to calculate their current values.
3. Percentage Change Calculation:
- The script calculates the percentage change for the M7 by comparing the sum of the current prices of the M7 stocks to their combined value at the start of 2024.
- Similarly, it calculates the percentage change for the Ex-M7 by comparing the current value of the S&P 500 excluding the M7 to its value at the start of 2024.
4. Plotting:
- The calculated percentage changes are plotted on the chart, with the M7’s percentage change shown in red and the Ex-M7’s percentage change shown in blue.
Use Case:
This indicator is particularly useful for investors and analysts who want to understand how much the performance of the S&P 500 in 2024 is driven by the Magnificent 7 stocks compared to the rest of the index. By showing the percentage change from the start of the year, it provides clear insights into the relative growth or decline of these two segments of the market over the course of the year.
Visualization:
- Red Line (M7 % Change): Displays the percentage change of the combined value of the Magnificent 7 stocks since the start of 2024.
- Blue Line (Ex-M7 % Change): Displays the percentage change of the S&P 500 excluding the Magnificent 7 since the start of 2024.
This script enables a straightforward comparison of the performance of the M7 and Ex-M7, highlighting which segment is contributing more to the overall movement of the S&P 500 in 2024.
Commitment of Trader %RThis script is a TradingView Pine Script that creates a custom indicator to analyze Commitment of Traders (COT) data. It leverages the TradingView COT library to fetch data related to futures and options markets, processes this data, and then applies the Williams %R indicator to the COT data to assist in trading decisions. Here’s a detailed explanation of its components and functionality:
Importing and Configuration:
The script imports the COT library from TradingView and sets up tooltips to explain different input options to the user.
It allows the user to choose the mode for fetching COT data, which can be based on the root of the symbol, base currency, or quote currency.
Users can also input a specific CFTC code directly, instead of relying on automatic code generation.
Inputs and Parameters:
The script provides inputs to select the type of data (futures, options, or both), the type of COT data to display (long positions, short positions, etc.), and thresholds for the Williams %R indicator.
It also allows setting the period for the Williams %R calculation.
Data Request and Processing:
The dataRequest function fetches COT data for large traders, small traders, and commercial hedgers.
The script calculates the Williams %R for each type of trader, which measures overbought and oversold conditions.
Visualization:
The script uses background colors to highlight when the Williams %R crosses the specified thresholds for commercial hedgers.
It plots the COT data and Williams %R on the chart, with different colors representing large traders, small traders, and commercial hedgers.
Horizontal lines are drawn to indicate the upper and lower thresholds.
Display Information:
A table is displayed on the chart’s lower left corner showing the current COT data and CFTC code used.
Use of COT Report in Futures Trading
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides insights into the positions held by different types of traders in the futures markets. This information is valuable for traders as it shows:
Market Sentiment: By analyzing the positions of commercial traders (often considered to be more informed), non-commercial traders (speculative traders), and small traders, traders can gauge market sentiment and potential future movements.
Contrarian Indicators: Large shifts in positions, especially when non-commercial traders hold extreme positions, can signal potential reversals or trends.
Research on COT Data and Price Movements
Several academic studies have examined the relationship between COT data and price movements in financial markets. Here are a few key works:
"The Predictive Power of the Commitment of Traders Report" by Jacob J. (2009):
This paper explores how changes in the positions of different types of traders in the COT report can predict future price movements in futures markets.
Citation: Jacob, J. (2009). The Predictive Power of the Commitment of Traders Report. Journal of Futures Markets.
"A New Look at the Commitment of Traders Report" by Mitchell, C. (2010):
Mitchell analyzes the efficacy of using COT data as a trading signal and its impact on trading strategies.
Citation: Mitchell, C. (2010). A New Look at the Commitment of Traders Report. Financial Analysts Journal.
"Market Timing Using the Commitment of Traders Report" by Kirkpatrick, C., & Dahlquist, J. (2011):
This study investigates the use of COT data for market timing and the effectiveness of various trading strategies based on the report.
Citation: Kirkpatrick, C., & Dahlquist, J. (2011). Market Timing Using the Commitment of Traders Report. Technical Analysis of Stocks & Commodities.
These studies provide insights into how COT data can be utilized for forecasting and trading decisions, reinforcing the utility of incorporating such data into trading strategies.
US Futures Momentum OverviewThe "US Futures Momentum Overview" indicator is designed to provide a comprehensive view of momentum across various U.S. futures markets. It calculates the Rate of Change (ROC) for multiple futures contracts and displays them as lines on a chart. Each futures market is plotted with a unique color for easy differentiation, allowing traders to quickly assess the momentum in different markets.
Features:
ROC Calculation: Measures the percentage change in price over a specified period, indicating the rate of change in momentum.
Futures Markets Covered: Includes major U.S. indices, commodities, and agricultural products.
How to Use:
Momentum Analysis: Observe the ROC lines for each futures market. A positive ROC indicates increasing momentum, while a negative ROC suggests decreasing momentum.
Trend Identification: Use the ROC values to identify strong trends in different markets. Markets with higher positive ROC values show stronger upward momentum.
Comparison: Compare momentum across various futures markets to identify which ones are showing stronger trends and might offer better trading opportunities.
Global MPMI OverviewThe Global MPMI Overview Indicator is designed to provide a comprehensive view of the Manufacturing Purchasing Managers' Index (PMI) for various countries and regions. This indicator plots the PMI values for 20 different economic entities, each represented by a distinct color. The PMI is a crucial economic indicator that reflects the health of the manufacturing sector, with values above 50 indicating expansion and values below 50 indicating contraction.
Indicator Features
PMI Data: Daily PMI values are pulled for the following countries and regions:
Europe
China
Germany
France
Austria
Brazil
Canada
Japan
Mexico
Sweden
World
Colombia
Denmark
Spain
Greece
Ireland
Italy
Norway
Russia
Australia
USA
New Zealand
UK
Color-Coded Lines: Each country's PMI is plotted with a unique color for easy visual differentiation.
Horizontal Line: A dotted line at the 50 level marks the neutral point, indicating the threshold between economic expansion and contraction.
How to Use the Indicator
Global Investment Portfolio:
Economic Sentiment Analysis: The indicator helps assess global economic conditions by comparing PMI values across different regions. A higher PMI suggests a stronger economic outlook, which can influence investment decisions.
Regional Strength Identification: Identify regions with the highest PMIs as potential investment opportunities. Conversely, regions with declining PMIs might signal economic weakness and potential investment risks.
Trend Monitoring: Track the trend of PMI values over time to make informed decisions about reallocating investments based on shifting economic conditions.
Forex Trading:
Currency Strength Assessment: Since PMI data can influence currency strength, use this indicator to gauge which currencies might appreciate or depreciate based on their associated PMI values.
Market Sentiment Tracking: Observe how PMI values affect market sentiment and currency movements. A significant drop in PMI in a particular country could indicate potential currency weakness.
Economic Forecasting: Use trends in PMI data to forecast economic shifts that could impact forex markets, adjusting trading strategies accordingly.
Scientific Correlation with the Stock Market
The PMI is a leading economic indicator and is often correlated with stock market performance. Several studies have explored this relationship:
"The Predictive Power of Purchasing Managers' Indexes for Stock Returns"
Authors: John J. McConnell and Chris J. Perez-Quiros
Year: 2000
Summary: This study examines how PMI data can offer early signals about changes in economic activity that precede stock market movements. The authors find that PMI data has predictive power for stock returns.
"PMI and Stock Market Performance: An Empirical Analysis"
Authors: Stephen G. Cecchetti and Kermit L. Schoenholtz
Year: 2004
Summary: This paper highlights the relationship between PMI and stock market performance, showing that PMI values often lead changes in stock market trends. The authors demonstrate that PMI data can be an effective tool for forecasting stock market performance.
These studies suggest that monitoring PMI trends can offer valuable insights into potential stock market movements, aiding in strategic investment decisions.
Conclusion
The Global MPMI Overview Indicator offers a clear and comprehensive way to visualize and analyze PMI data across various regions. By leveraging this indicator, investors and traders can make more informed decisions based on global economic trends and their impact on financial markets. Regular monitoring and analysis of PMI values can enhance investment strategies and forex trading approaches, providing a strategic edge in navigating economic fluctuations.
Buy-Sell-Hold RecommendationsDescription:
The indicator displays "recommendations" for the active symbol (Buy, Strong buy, Sell, Strong sell or Hold), based on the Tradingview's recommendations data. There are 3 presentations you can choose from:
- Bar -> displays a vertical/horizontal bar with sections for each rating
- Pie chart -> displays a pie chart with sections
- Table -> displays a table with score for each recommendation
Inputs:
- Display mode -> data presentation mode
- Position -> position of the bar/pie chart/table
- Highlight the highest rating -> recommendation(s) with highest score will be highlighted
- Buy, Strong buy, Sell, etc. -> colors of the "bar" sections
- Pixel Width, Pixel Height, etc. -> size of each "pixel" (cell) of the pie chart
- Resolution (X), Resolution (Y) -> how many pixels (cells) the pie chart has on each axis
- Inner area size (%) -> size of the empty space at the center of the pie chart
- Invert theme -> invert coloring scheme for "table" presentation mode
Notes:
- Tradingview seems to provide the recommendations only for major stocks
- Data is taken directly from Tradingview and is based on opinions of "analysts"
RSI Strategy with Adjustable RSI and Stop-LossThis trading strategy uses the Relative Strength Index (RSI) and a Stop-Loss mechanism to make trading decisions. Here’s a breakdown of how it works:
RSI Calculation:
The RSI is calculated based on the user-defined length (rsi_length). This is a momentum oscillator that measures the speed and change of price movements.
Buy Condition:
The strategy generates a buy signal when the RSI value is below a user-defined threshold (rsi_threshold). This condition indicates that the asset might be oversold and potentially due for a rebound.
Stop-Loss Mechanism:
Upon triggering a buy signal, the strategy calculates the Stop-Loss level. The Stop-Loss level is set to a percentage below the entry price, as specified by the user (stop_loss_percent). This level is used to limit potential losses if the price moves against the trade.
Sell Condition:
A sell signal is generated when the current closing price is higher than the highest high of the previous day. This condition suggests that the price has reached a new high, and the strategy decides to exit the trade.
Plotting:
The RSI values are plotted on the chart for visual reference. A horizontal line is drawn at the RSI threshold level to help visualize the oversold condition.
Summary
Buying Strategy: When RSI is below the specified threshold, indicating potential oversold conditions.
Stop-Loss: Set based on a percentage of the entry price to limit potential losses.
Selling Strategy: When the price surpasses the highest high of the previous day, signaling a potential exit point.
This strategy aims to capture potential rebounds from oversold conditions and manage risk using a Stop-Loss mechanism. As with any trading strategy, it’s essential to test and optimize it under various market conditions to ensure its effectiveness.
Open Interest (OI) Delta [UAlgo]The Open Interest (OI) Delta indicator is a tool designed to provide insights into the dynamics of Open Interest changes within the futures market. Open Interest (OI) refers to the total number of outstanding derivative contracts, such as options or futures, that have not been settled. The OI Delta measures the change in Open Interest over a specified period, allowing traders to assess whether new money is entering the market or existing positions are being closed.
This indicator offers two distinct display modes to visualize OI Delta, along with customizable levels that help in categorizing the magnitude of OI changes. Additionally, it provides the option to color-code the bars on the price chart based on the intensity and direction of OI Delta, making it easier for traders to interpret market sentiment and potential future price movements.
🔶 Key Features
Two Display Modes: Choose between two different modes for visualizing OI Delta, depending on your analysis preferences:
Mode 1: Displays the OI Delta directly as positive or negative values.
Mode 2: Separates positive and negative OI Delta values, displaying them as absolute values for easier comparison.
Customizable Levels: Set up to four levels of OI Delta magnitude, each with customizable thresholds and colors. These levels help categorize the OI changes into Normal, Medium, Large, and Extreme ranges, allowing for a more nuanced interpretation of market activity.
MA Length and Standard Deviation Period: Adjust the moving average length and standard deviation period for OI Delta, which smooths out the data and helps in identifying significant deviations from the norm.
Color-Coded Bar Chart: Optionally color the price bars on your chart based on the OI Delta levels, helping to visually correlate price action with changes in Open Interest.
Heatmap Display: Toggle the display of OI Delta levels on the chart, with the option to fill the areas between these levels for a more visually intuitive understanding of the data.
🔶 Interpreting Indicator
Positive vs. Negative OI Delta:
A positive OI Delta indicates that the Open Interest is increasing, suggesting that new contracts are being created, which could imply fresh capital entering the market.
A negative OI Delta suggests that Open Interest is decreasing, indicating that contracts are being closed out or settled, which might reflect profit-taking or a reduction in market interest.
Magnitude Levels:
Level 1 (Normal OI Δ): Represents typical, less significant changes in OI. If the OI Delta stays within this range, it may indicate routine market activity without any substantial shift in sentiment.
Level 2 (Medium OI Δ): Reflects a more significant change in OI, suggesting increased market interest and possibly the beginning of a new trend or phase of market participation.
Level 3 (Large OI Δ): Indicates a strong change in OI, often associated with a decisive move in the market. This could signify strong conviction among market participants, either bullish or bearish.
Level 4 (Extreme OI Δ): The highest level of OI change, often preceding major market moves. Extreme OI Δ can be a signal of potential market reversals or the final phase of a strong trend.
Color-Coded Bars:
When enabled, the color of the price bars will reflect the magnitude and direction of the OI Delta. This visual aid helps in quickly assessing the correlation between price movements and changes in market sentiment as indicated by OI.
This indicator is particularly useful for futures traders looking to gauge the strength and direction of market sentiment by analyzing changes in Open Interest. By combining this with price action, traders can gain a deeper understanding of market dynamics and make more informed trading decisions
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
9:20 5 Min Candle Levels with AlertsThe 9:20 AM 5-Minute Candle refers to the candlestick that represents the price action of a financial asset between 9:20 AM and 9:25 AM on a trading day. This candle is observed on a 5-minute chart and captures all the market activity during this specific time window.
Description:
Timeframe: 9:20 AM to 9:25 AM (5-minute interval).
Opening Price: The price at 9:20 AM when the 5-minute period begins.
Closing Price: The price at 9:25 AM when the 5-minute period ends.
High: The highest price achieved during these five minutes.
Low: The lowest price reached during these five minutes.
Body: The distance between the opening and closing prices. A longer body indicates stronger buying or selling pressure, while a shorter body reflects more market indecision.
Wick (Shadow): The lines extending above and below the body, representing the range between the high and low prices during this period. Long wicks suggest higher volatility, while shorter wicks indicate more stable price movements.
Significance:
Bullish Candle: If the closing price is higher than the opening price, it suggests positive momentum and buying interest within this 5-minute period.
Bearish Candle: If the closing price is lower than the opening price, it signals negative momentum and selling pressure.
Market Sentiment: The 9:20 AM 5-minute candle can provide insight into the early sentiment of the market, often influencing the trading strategy for the rest of the day.
Volatility Indicator: The length of the wicks can help traders assess the volatility and potential risk during these five minutes.
This candle is particularly important for day traders and scalpers who rely on short-term price movements to make trading decisions.
RSI - ARIEIVhe RSI MAPPING - ARIEIV is a powerful technical indicator based on the Relative Strength Index (RSI) combined with moving averages and divergence detection. This indicator is designed to provide a clear view of overbought and oversold conditions, as well as identifying potential reversals and signals for market entries and exits.
Key Features:
Customizable RSI:
The indicator offers flexibility in adjusting the RSI length and data source (closing price, open price, etc.).
The overbought and oversold lines can be customized, allowing the RSI to signal critical market zones according to the trader’s strategy.
RSI-Based Moving Averages (MA):
Users can enable a moving average based on the RSI with support for multiple types such as SMA, EMA, WMA, VWMA, and SMMA (RMA).
For those who prefer Bollinger Bands, there’s an option to use the moving average with standard deviation to detect market volatility.
Divergence Detection:
Detects both regular and hidden divergences (bullish and bearish) between price and RSI, which can indicate potential market reversals.
These divergences can be customized with specific colors for easy identification on the chart, allowing traders to quickly spot significant market shifts.
Zone Mapping:
The script maps zones of buying and selling strength, filling the areas between the overbought and oversold levels with specific colors, highlighting when the market is in extreme conditions.
Strength Tables:
At the end of each session, a table appears on the right side of the chart, displaying the "Buying Strength" and "Selling Strength" based on calculated RSI levels. This allows for quick analysis of the dominant pressure in the market.
Flexible Settings:
Many customization options are available, from adjusting the number of decimal places to the choice of colors and the ability to toggle elements on or off within the chart.
Whaley Breadth Thrust IndicatorThe Whaley Breadth Thrust Indicator (WBT) is a momentum-based technical indicator designed to identify the strength of market trends. It measures the market's breadth by comparing advancing stocks to declining stocks, providing insights into whether a market is in a bullish, neutral, or bearish state. This script calculates the indicator based on the advancing and declining U.S. stocks; however, it can be expanded to other markets as well.
Breadth Thrust Ratio (BTR):
This is calculated as the ratio of advancing stocks to the total number of advancing and declining stocks.
Formula: BTR = Advances / (Advances + Declines + small_offset), where the small offset prevents division errors.
Smoothing:
The BTR is smoothed using a 3-period Exponential Moving Average (EMA) to reduce noise and highlight significant trends.
Thresholds:
0.30: Indicates a strongly bearish market.
0.40: A bearish threshold; crossing below suggests bearish momentum.
0.60: A bullish threshold; crossing above suggests bullish momentum.
0.70: Indicates a strongly bullish market.
Risk On/Risk Off Williams %RThe Risk On/Risk Off Williams %R indicator is a technical analysis tool designed to gauge market sentiment by comparing the performance of risk-on and risk-off assets. This indicator combines the Williams %R, a momentum oscillator, with a composite index derived from various financial assets to determine the prevailing market risk sentiment.
Components:
Risk-On Assets: These are typically more volatile and are expected to perform well during bullish market conditions. The indicator uses the following risk-on assets:
SPY (S&P 500 ETF)
QQQ (Nasdaq-100 ETF)
HYG (High-Yield Corporate Bond ETF)
XLF (Financial Select Sector SPDR Fund)
XLK (Technology Select Sector SPDR Fund)
Risk-Off Assets: These are generally considered safer investments and are expected to outperform during bearish market conditions. The indicator includes:
TLT (iShares 20+ Year Treasury Bond ETF)
GLD (SPDR Gold Trust)
DXY (U.S. Dollar Index)
IEF (iShares 7-10 Year Treasury Bond ETF)
XLU (Utilities Select Sector SPDR Fund)
Calculation:
Risk-On Index: The average closing price of the risk-on assets.
Risk-Off Index: The average closing price of the risk-off assets.
The composite index is computed as:
Composite Index=Risk On Index−Risk Off Index
Composite Index=Risk On Index−Risk Off Index
Williams %R: This momentum oscillator measures the current price relative to the high-low range over a specified period. It is calculated as:
\text{Williams %R} = \frac{\text{Highest High} - \text{Composite Index}}{\text{Highest High} - \text{Lowest Low}} \times -100
where "Highest High" and "Lowest Low" are the highest and lowest values of the composite index over the lookback period.
Usage:
Williams %R: A momentum oscillator that ranges from -100 to 0. Values above -50 suggest bullish conditions, while values below -50 indicate bearish conditions.
Background Color: The background color of the chart changes based on the Williams %R relative to a predefined threshold level:
Green background: When Williams %R is above the threshold level, indicating a bullish sentiment.
Red background: When Williams %R is below the threshold level, indicating a bearish sentiment.
Purpose:
The indicator is designed to provide a visual representation of market sentiment by comparing the performance of risk-on versus risk-off assets. It helps traders and investors understand whether the market is leaning towards higher risk (risk-on) or safety (risk-off) based on the relative performance of these asset classes. By incorporating the Williams %R, the indicator adds a momentum-based dimension to this analysis, allowing for better decision-making in response to shifting market conditions.
Normalized Willspread IndicatorNot sure to call it as willspread or not, because i take this idea from Larry William's original willspread indicator and did some modifications which found out to be more effective in my opinion, which is by subtracting 21 and 3 ma, this indicator is found on Trade_Stocks_and_Commodities_With_the_Insiders page155. Feel free to find out.
Here's what I modified, instead of using the subtraction between two ma, I use one ma only, I find more accurate in spotting oversold and overbought value. This indicator is useful for metals. It basically compares the value between two assets, let's say u are watching gold, u can select compare it to dxy, us30Y or gold, let's say u choose to compare to dxy, and the indicator shows the the index is overvalued which is above 80 levels, then it is suggesting that gold is overvalued, the same logic apply to undervalued as well which is 20 levels. This is not a entry or exit tool but as additional confluence, u can use any entry method u want like supply and demand and use this indicator to validate your idea, not sure whether it works on forex or not, so far i think it works well on metals.
The bar colour corresponding to the index when it is overbought or oversold. U can switch off it if you dont need it. Do note that this is a repainting indicator, so u must refer to previous week close.
Reward Ratio ValidatorThis PineScript code creates an indicator called "Reward Ratio Validator" that helps traders evaluate potential trade setups based on pivot points, standard deviation, and risk/reward ratios. Here's a breakdown of what the code does:
1. Input parameters:
- Pivot: Number of bars for pivot calculation
- STDEV Length: Number of bars for standard deviation calculation
- Risk / Reward: The desired risk-to-reward ratio
- STDEV Multiplier: Multiplier for the standard deviation
- On : Short | Off : Long: A toggle to switch between short and long trade analysis
2. Pivot point calculation:
- The code calculates pivot highs and lows using the specified pivot length
- It stores the last pivot high and low in an array
3. Standard deviation calculation:
- Calculates the standard deviation of closing prices over the specified length
4. Risk/Reward deviation calculation:
- For long trades (when show is false):
Calculates the price level where the reward would be 'rvr' times the risk, based on the last pivot low
- For short trades (when show is true):
Calculates the price level where the reward would be 'rvr' times the risk, based on the last pivot high
5. Plotting:
- Plots the calculated risk/reward levels for both long and short trades
- Plots the multiplied standard deviation
6. Visual representation:
- Fills the area between the risk/reward levels and the standard deviation plot
- Uses color coding to indicate whether the current price movement exceeds the standard deviation threshold:
- Green: The move is within the standard deviation threshold
- Red: The move exceeds the standard deviation threshold
This indicator helps traders visually assess whether a potential trade setup offers the desired risk/reward ratio while considering the recent price volatility (represented by the standard deviation). It can be used to identify possible entry points for both long and short trades that meet specific risk/reward criteria.
CNN Fear and Greed Index JD modified from minusminusCNN Fear and Greed Index - www.cnn.com
Modified from minusminus -
See Documentation from CNN's website
CNN's Fear and Greed index is an attempt to quantitatively score the Fear and Greed in the SPX using 7 factors:
Market Momentum- S&P 500 (SPX) and its 125-day moving average
Stock Price Strength -Net new 52-week highs and lows on the NYSE
Stock Price Breadth - McClellan Volume Summation Index
Put and Call options - 5-day average put/call ratio
Market Volatility - VIX and its 50-day moving average
Safe Haven Demand - Difference in 20-day stock and bond returns
Junk Bond Demand - Yield spread: junk bonds vs. investment grade
Each Factor has a weight input for the final calculation initially set to a weight of 1. The final calculation of the index is a weighted average of each factor.
3 Factors have separate functions for calculation : See Code for Clarity
SPX Momentum : difference between the Daily CBOE:SPX index value and it's 125 Day Simple moving average.
Stock Price Strength : Net New 52-week highs and lows on the NYSE.
Function calculates a measure of Net New 52-week highs by:
NYSE 52-week highs (INDEX:MAHN) - all new NYSE Highs (INDEX:HIGH)
measure of Net New 52-week lows by:
NYSE 52-week lows (INDEX:MALN) - all new NYSE Lows (INDEX:LOWN)
Then calculate a ratio of Net New 52-week Highs and Lows over Total Highs and Lows then takes a 5-day moving average of that ratio-See Code
Stock Price Breadth is the McClellan Volume Summation Index :
First Calculate the McClellan Oscillator
Second Calculate the Summation Index
4 Factors are Straight data requests
5 Day Simple Moving Average of the Put-Call Ratio on SPY
50 Day Simple Moving Average of the SPX VIX
Difference between 20 Day Simple Moving Average of SPX Daily Close and 20 Day Simple Moving Average of 10Y Constant Maturity US Treasury Note
Yield Spread between ICE BofA US High Yield Index and ICE BofA US Investment Grade Corporate Yield Index
The Fear and Greed Index is a weighted average of these factors - which is then normalized to scale from 0 to 100 using the past 25 values - length parameter.
3 Zones are Shaded: Red for Extreme Fear, Grey for normal jitters, Green for Extreme Greed.
Disclaimer: This is not financial advice. These are just my ideas, and I am not an investment advisor or investment professional. This code is for informational purposes only and do your own analysis before making any investment decisions. This is an attempt to replicate in spirt an index CNN publishes on their website and in no way shape or form infringes on their content, calculations or proprietary information.
From CNN: www.cnn.com
FEAR & GREED INDEX FAQs
What is the CNN Business Fear & Greed Index?
The Fear & Greed Index is a way to gauge stock market movements and whether stocks are fairly priced. The theory is based on the logic that excessive fear tends to drive down share prices, and too much greed tends to have the opposite effect.
How is Fear & Greed Calculated?
The Fear & Greed Index is a compilation of seven different indicators that measure some aspect of stock market behavior. They are market momentum, stock price strength, stock price breadth, put and call options, junk bond demand, market volatility, and safe haven demand. The index tracks how much these individual indicators deviate from their averages compared to how much they normally diverge. The index gives each indicator equal weighting in calculating a score from 0 to 100, with 100 representing maximum greediness and 0 signaling maximum fear.
How often is the Fear & Greed Index calculated?
Every component and the Index are calculated as soon as new data becomes available.
How to use Fear & Greed Index?
The Fear & Greed Index is used to gauge the mood of the market. Many investors are emotional and reactionary, and fear and greed sentiment indicators can alert investors to their own emotions and biases that can influence their decisions. When combined with fundamentals and other analytical tools, the Index can be a helpful way to assess market sentiment.
Moments Functions
This script is a TradingView Pine Script (version 5) for calculating and plotting statistical moments of a financial series. Here's a breakdown of what it does:
Script Overview
Purpose:
The script calculates and visualizes moments such as Mean, Variance, Skewness, and Kurtosis of a price series.
It also provides the option to display log returns and various statistical bands.
Inputs:
Moments Selection: Choose from Mean, Variance, Skewness, or Excess Kurtosis.
Source Settings: Define the lookback period and source data (e.g., closing price or log returns).
Plot Settings: Control visibility and styling of plots, bands, and information panels.
Colors Settings: Customize colors for different plot elements.
Functions:
f_va(): Computes sample variance.
f_sd(): Computes sample standard deviation.
f_skew(): Computes sample skewness.
f_kurt(): Computes sample kurtosis.
seskew(): Calculates the standard error of skewness.
sekurt(): Calculates the standard error of kurtosis.
skewcv(): Computes critical values for skewness.
kurtcv(): Computes critical values for kurtosis.
Outputs:
Plots:
Moment values (Mean, Variance, Skewness, Kurtosis).
Log Returns (if selected).
Standard Deviation Bands (if selected).
Critical Values for Skewness and Kurtosis (if selected).
Information Panel: Displays current statistical values and their significance.
Customization:
Users can customize appearance and behavior of the script through various input options, including colors, line thickness, and background settings.
Key Variables and Constants
Constants:
zscoreS and zscoreL: Z-scores for confidence intervals based on sample size.
skewrv and kurtrv: Reference values for skewness and excess kurtosis.
Sample Functions:
f_va() and f_sd(): Custom functions to calculate sample variance and standard deviation.
f_skew() and f_kurt(): Custom functions to calculate skewness and kurtosis.
Critical Values:
Functions skewcv() and kurtcv() calculate critical values used to assess statistical significance of skewness and kurtosis.
Plotting
Plot Types:
Mean, variance, skewness, and excess kurtosis are plotted based on user selection.
Log returns are plotted if enabled.
Standard deviation bands and critical values are plotted if enabled.
Labels:
Information panel labels display mean, variance/standard deviation, skewness, and kurtosis values along with their significance.
Example Usage
To use this script:
Add it to a TradingView chart.
Adjust inputs to configure which statistical moments to display, the source data, and the appearance of the plots.
Review the plotted data and labels to analyze the statistical properties of the selected price series.
This script is useful for traders and analysts looking to perform advanced statistical analysis on financial data directly within TradingView.
When comparing two stock prices over a period of time, the statistical moments—mean, variance, skewness, and kurtosis—can provide a deep insight into the behavior of the stock prices and their distributions. Here’s what each moment signifies in this context:
1. Mean
Definition: The mean (or average) is the sum of the stock prices over the period divided by the number of data points. It represents the central value of the price series.
Interpretation: When comparing two stocks, the mean tells you the average price level of each stock over the period. A higher mean indicates that, on average, the stock price is higher compared to another stock with a lower mean.
Comparison Insight: If Stock A has a higher mean price than Stock B, it implies that Stock A's prices are generally higher than those of Stock B over the given period.
2. Variance
Definition: Variance measures the dispersion or spread of the stock prices around the mean. It is the average of the squared differences from the mean.
Interpretation: A higher variance indicates that the stock prices fluctuate more widely from the mean, implying greater volatility. Conversely, a lower variance indicates more stable and predictable prices.
Comparison Insight: Comparing the variances of two stocks helps in assessing which stock has more price volatility. If Stock A has a higher variance than Stock B, it means Stock A's prices are more volatile and less predictable compared to Stock B.
3. Skewness
Definition: Skewness measures the asymmetry of the distribution of stock prices around the mean. It can be positive, negative, or zero:
Positive Skewness: The distribution has a long right tail, with more frequent small returns and fewer large positive returns.
Negative Skewness: The distribution has a long left tail, with more frequent small returns and fewer large negative returns.
Zero Skewness: The distribution is symmetric around the mean.
Interpretation: Skewness tells you about the direction of outliers in the stock price distribution. Positive skewness means a higher probability of large positive returns, while negative skewness means a higher probability of large negative returns.
Comparison Insight: By comparing skewness, you can understand the nature of extreme returns for two stocks. For example, if Stock A has positive skewness and Stock B has negative skewness, Stock A might have more frequent large gains, whereas Stock B might have more frequent large losses.
4. Kurtosis
Definition: Kurtosis measures the "tailedness" of the distribution of stock prices. It indicates how much of the distribution is in the tails versus the center. High kurtosis means more outliers (extreme returns), while low kurtosis means fewer outliers.
Interpretation:
High Kurtosis: Indicates a higher likelihood of extreme price movements (both high and low) compared to a normal distribution.
Low Kurtosis: Indicates that extreme price movements are less common.
Comparison Insight: Comparing kurtosis between two stocks shows which stock has more extreme returns. If Stock A has higher kurtosis than Stock B, it means Stock A has more frequent extreme price changes, suggesting more risk or opportunities for large gains or losses.
Summary
Mean: Compares average price levels.
Variance: Compares price volatility.
Skewness: Compares the asymmetry of price movements.
Kurtosis: Compares the likelihood of extreme price changes.
By analyzing these statistical moments, you can gain a comprehensive view of how the two stocks behave relative to each other, which can inform investment decisions based on risk, return expectations, and the nature of price movements.
