Landry Light with Moving AverageLandry Light with Moving Average
Overview:
This Pine Script, titled "Landry Light with Moving Average", visualizes the relationship between price action and a chosen moving average (MA) over time. It helps users easily identify periods where the price stays consistently above or below the moving average, which can be a useful indicator of bullish or bearish trends.
Key Features:
Moving Average Type Selection:
The script allows users to choose between two types of moving averages:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
This is done via a user input option, enabling traders to tailor the indicator to their preferred analysis method.
Moving Average Length:
Users can set the length of the moving average (default is 21 periods). This allows customization based on the trader's time frame, whether short-term or long-term analysis.
Dynamic Moving Average Color:
The moving average line changes color based on the relationship between the price and the MA:
Green: Price is consistently above the MA (bullish condition).
Red: Price is consistently below the MA (bearish condition).
Blue: Price is crossing or close to the MA (neutral or indecisive condition).
Cumulative Days Above/Below MA:
The script tracks and displays the number of consecutive days the price remains above or below the moving average:
Cumulative Days Above: Shown as a green histogram above the zero line.
Cumulative Days Below: Shown as a red histogram below the zero line.
This feature helps users identify sustained trends or potential reversals.
Real-time Labels:
The script generates dynamic labels that display the count of cumulative days the price has stayed above or below the moving average.
These labels are positioned near the moving average on the chart, providing an easy reference for traders.
How Users Can Benefit:
Trend Identification:
By visually representing how long the price stays above or below a key moving average, traders can identify strong bullish or bearish trends. This can inform entry and exit points.
Visualizing Market Sentiment:
The colored moving average line and histogram help traders quickly assess market sentiment. A prolonged green MA line suggests a strong uptrend, while a prolonged red line indicates a downtrend.
Adaptability:
With customizable moving average types and lengths, the indicator can be tailored to fit various trading strategies, whether for day trading, swing trading, or long-term investing.
Reversal Signals:
A shift from cumulative days above to cumulative days below (or vice versa) can serve as an early signal of a potential market reversal, allowing traders to adjust their positions accordingly.
Simplified Decision-Making:
The combination of visual cues (colors, histograms, and labels) simplifies decision-making, allowing traders to focus on trend strength rather than complex calculations.
Usage:
To use this script:
Add the Indicator to Your Chart:
Select the desired moving average type and length.
The script will plot the moving average, colored by the trend, and display cumulative days above or below it.
Interpret the Signals:
Use the histogram and labels to gauge the strength of the trend.
Monitor color changes in the moving average for potential trend reversals.
Incorporate into Your Strategy:
Combine this indicator with other tools (e.g., volume analysis, RSI) to confirm signals and refine your trading strategy.
This indicator is particularly useful for traders who follow the "Landry Light" concept, emphasizing the importance of price staying above or below a moving average to determine trend strength.
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Multi Adaptive Moving Average (MAMA)The Multi Adaptive Moving Average (MAMA) indicator is an advanced tool for technical analysis, designed to provide traders with a detailed understanding of market trends and potential future price movements. This indicator utilizes multiple Simple Moving Averages (SMAs) and forecasting techniques to enhance decision-making processes.
Simple Moving Averages (SMAs):
Short MA (20-period): This moving average is highly responsive to price changes, making it ideal for capturing short-term trends. It helps traders identify quick market shifts and potential entry or exit points.
Mid MA (50-period): This average strikes a balance between short- and long-term trends, offering insights into the market's intermediate direction. It aids in confirming the sustainability of short-term trends.
Long MA (100-period): By smoothing out price data over a longer period, this moving average is useful for identifying long-term trends and filtering out short-term volatility.
Very Long MA (200-period): Often considered a critical indicator for determining the overall market trend, this average helps confirm the direction and strength of long-term movements.
Forecasting:
Flat Forecast: This approach assumes that prices will remain constant in the near future, which is particularly useful in markets trading sideways without a clear trend direction.
Linear Regression Forecast: This method uses historical data to project future price movements, offering a dynamic forecast based on existing trends. It helps traders anticipate potential price changes and plan their strategies accordingly.
Advantages:
Comprehensive Trend Analysis: By incorporating four different SMAs, the indicator provides a layered view of market trends across various timeframes. This enables traders to identify potential trend reversals and continuations with greater accuracy.
Predictive Insights: The forecasting feature offers traders a forward-looking perspective, enabling them to anticipate market movements and adjust their trading strategies proactively. This can be especially advantageous in volatile markets.
Customization: The MAMA indicator is highly customizable, allowing traders to adjust parameters such as the source of price data and the inclusion of the current unclosed candle. This flexibility ensures that the indicator can be tailored to fit different trading styles and market conditions.
Visual Clarity: The use of distinct colors for each SMA and their forecasts enhances visual interpretation, making it easier for traders to quickly assess market conditions and make informed decisions. The inclusion of a legend further aids in distinguishing between the different moving averages and their respective forecasts.
How to Use:
Trend Confirmation: Use the alignment of the SMAs to confirm market trends. For example, when the Short MA crosses above the Mid and Long MAs, it may indicate a bullish trend, while the opposite could suggest a bearish trend.
Entry and Exit Points: Look for crossovers between the SMAs as potential signals for entering or exiting trades. The forecasts can help in timing these decisions by providing an expectation of future price movements.
Risk Management: Utilize the Very Long MA to set stop-loss and take-profit levels, as it reflects the long-term trend and can help in avoiding trades against the prevailing market direction.
The MAMA indicator is intended to support technical analysis and should not be used as the sole basis for making trading decisions. Financial markets are inherently uncertain, and past performance does not guarantee future results. Traders should use this tool in conjunction with other analytical methods and consider their risk tolerance and investment objectives. It is advisable to conduct thorough research and consult with a financial advisor before making significant trading decisions. Always be aware of the risks involved in trading and invest only what you can afford to lose.
HMA Z-Score Probability Indicator by Erika BarkerThis indicator is a modified version of SteverSteves's original work, enhanced by Erika Barker. It visually represents asset price movements in terms of standard deviations from a Hull Moving Average (HMA), commonly known as a Z-Score.
Key Features:
Z-Score Calculation: Measures how many standard deviations the current price is from its HMA.
Hull Moving Average (HMA): This moving average provides a more responsive baseline for Z-Score calculations.
Flexible Display: Offers both area and candlestick visualization options for the Z-Score.
Probability Zones: Color-coded areas showing the statistical likelihood of prices based on their Z-Score.
Dynamic Price Level Labels: Displays actual price levels corresponding to Z-Score values.
Z-Table: An optional table showing the probability of occurrence for different Z-Score ranges.
Standard Deviation Lines: Horizontal lines at each standard deviation level for easy reference.
How It Works:
The indicator calculates the Z-Score by comparing the current price to its HMA and dividing by the standard deviation. This Z-Score is then plotted on a separate pane below the main chart.
Green areas/candles: Indicate prices above the HMA (positive Z-Score)
Red areas/candles: Indicate prices below the HMA (negative Z-Score)
Color-coded zones:
Green: Within 1 standard deviation (high probability)
Yellow: Between 1 and 2 standard deviations (medium probability)
Red: Beyond 2 standard deviations (low probability)
The HMA line (white) shows the trend of the Z-Score itself, offering insight into whether the asset is becoming more or less volatile over time.
Customization Options:
Adjust lookback periods for Z-Score and HMA calculations
Toggle between area and candlestick display
Show/hide probability fills, Z-Table, HMA line, and standard deviation bands
Customize text color and decimal rounding for price levels
Interpretation:
This indicator helps traders identify potential overbought or oversold conditions based on statistical probabilities. Extreme Z-Score values (beyond ±2 or ±3) often suggest a higher likelihood of mean reversion, while consistent Z-Scores in one direction may indicate a strong trend.
By combining the Z-Score with the HMA and probability zones, traders can gain a nuanced understanding of price movements relative to recent trends and their statistical significance.
Day, Week, or Hour Coloring
This is a simple Script that dynamically colors the chart bars based on the day of the week, week of the month, or hour of the day. Users can toggle between these three modes using the Color Mode input, allowing for flexible visual representation of time periods directly on the chart.
Key Features:
Color Modes:
Day Mode: Colors the bars according to the day of the week, with each day assigned a unique color.
Week Mode: Colors the bars based on the week of the month, providing a different color for each week.
Hour Mode: Colors the bars according to the hour of the day, with distinct colors assigned to each hour.
How It Works:
Day Mode:
The script assigns a unique color to each day of the week (e.g., Monday is red, Tuesday is green).
Week Mode:
The script calculates the week of the month by considering the first day of the month and adjusts the day count to determine the correct week.
Each week is assigned a specific color (e.g., Week 1 is red, Week 2 is green).
Hour Mode:
The script assigns a unique color to each hour of the day (e.g., 0:00 is blue, 1:00 is green).
Selected Color Application:
The script evaluates the selected Color Mode and applies the corresponding color to the bars on the chart using the barcolor() function.
This indicator is useful for traders who want to visually distinguish time periods on their charts, aiding in pattern recognition and time-based analysis.
5-9-20-100 Day EMAIndicator Name: "5-9-20-100 Day EMA"
Purpose: This indicator plots four key EMAs (5, 9, 20, and 100-day) on a daily chart, providing a clear visualization of both short-term and long-term trends. The EMAs serve as critical triggers for identifying potential entry and exit points based on price interactions with these moving averages.
Technical Details:
Version: Pine Script v5
EMAs Used:
5-Day EMA (Lime): Captures the most recent price trends, useful for identifying short-term momentum.
9-Day EMA (Yellow): Offers a slightly broader view, often used to confirm the short-term trend.
20-Day EMA (Orange): Represents a medium-term trend, commonly used as a signal for trend reversals.
100-Day EMA (Red): Indicates the long-term trend, often serving as strong support or resistance levels.
Trigger Points:
Crossovers: Price crossing above or below these EMAs can trigger potential buy or sell signals.
Convergence/Divergence: The interaction between the EMAs, such as a faster EMA crossing a slower one, can signal trend reversals or continuations.
Utility: This indicator is ideal for traders who rely on EMA crossovers and the relationship between different EMAs to make informed trading decisions.
MTF AnalysisMTF Analysis - Multi-Timeframe TradingView Script
Overview: The "MTF Analysis" script provides a comprehensive approach to analyzing price trends across daily, weekly, and monthly timeframes using linear regression channels. It helps traders identify strong and weak bullish or bearish conditions based on the relationship between the current price and regression lines derived from multiple timeframes.
Key Features:
User-Defined Inputs:
Regression Lengths: Customize regression lengths for daily, weekly, and monthly timeframes.
Smoothing Length: Apply smoothing to regression lines.
Near-Zero Threshold: Filter out signals near a defined slope threshold for more refined analysis.
Daily Time Frame Filter: Optional filter to consider daily regression slope in signal generation.
Regression Line Calculation:
The script calculates linear regression lines for each timeframe (daily, weekly, monthly) and applies a smoothing function to refine the signals.
Signal Conditions:
Strong Bullish/Bearish: Signals generated when the price is consistently above/below weekly and monthly regression lines, with the option to apply the daily timeframe filter.
Weak Bullish/Bearish: Signals generated when the price is above/below the monthly regression line alone.
Visual Indicators:
The script plots regression lines on the chart with different colors for easy identification.
It also displays arrows on the chart to indicate strong or weak bullish/bearish signals.
Alerts:
Custom alerts for each signal condition help traders stay informed of potential trading opportunities.
This script is highly customizable, allowing traders to tailor it to their specific trading style and preferences.
This summary can be used to introduce the script to other traders or for publication on platforms like TradingView.
Market Internals: VolumeThe indicator plots the total volume of the NYSE and NASDAQ exchanges and identifies periods with significant asymmetry between Up Volume and Down Volume. It can be used as an additional tool to confirm broad market sentiment.
Chart shows Total Volume (TVOL) bars for SPY daily chart. Green bars for UVOL>>DVOL, Red for DVOL>>UVOL. Neutral bars are gray. Blue line shows median TVOL.
Rationale:
Up Volume (UVOL) and Down Volume (DVOL) represent the total volume of stocks that have increased or decreased in price, respectively, compared to the previous session's closing price. The magnitude of the price change is irrelevant.
When UVOL is significantly higher than DVOL, it indicates a prevailing buying sentiment in the broad market. Conversely, when DVOL is higher, it signals prevailing selling sentiment.
Occasionally, the UVOL/DVOL (VOLD) ratio may be misaligned with the movement of the S&P index. The picture below illustrates an example of a day when the S&P declined, yet the UVOL was twice larger than DVOL. Such a divergence can suggest that the S&P was pulled down by a decline in a few large-cap stocks, while the broader market remained positive. In this case, the divergence led to a continuation of the rally.
Thus, VOLD, when combined with volume analysis, can be an effective tool for confirming market trends.
Parameters:
VOLD Ratio – minimum ratio of UVOL/DVOL or DVOL/UVOL. Indicator will color code volume columns when condition is true (“green” means buying; “red” selling).
Median Length – number of periods to calculate median TVOL.
Show Divergencies – indicator marks divergencies between price and volume sentiments on the main chart. Only works for SPY chart.
Users can also choose which exchanges (NASDAQ/NYSE) to use for volume calculation.
Notes:
Volume is shown in millions of contracts
Indicator should be used on the daily or higher timeframes. It won't work properly on the intraday charts
Disclaimer
This indicator should not be used as a standalone tool to make trading decisions but only in conjunction with other technical analysis methods.
Yield Curve InversionThe Yield Curve Inversion indicator is a tool designed to help traders and analysts visualize and interpret the dynamics between the US 10-year and 2-year Treasury yields. This indicator is particularly useful for identifying yield curve inversions, often seen as a precursor to economic recessions.
Features and Interpretations
Display Modes: Choose between "Spread Mode" to visualize the yield spread indicating normal (green) or inverted (red) curves, or "Both Yields Mode" to view both yields.
Yield Spread: A plotted difference between 10-year and 2-year yields, with a zero line marking inversion. A negative spread suggests potential economic downturns.
Color Coding: Green for a normal yield curve (10Y > 2Y) and red for an inverted curve (2Y > 10Y).
Legend: Provides quick reference to yield curve states for easier interpretation.
This indicator is for educational and informational purposes only. It should not be considered financial advice or a recommendation to buy or sell any financial instruments. Users should conduct their own research and consult with a financial advisor before making investment decisions. The creator of this indicator is not responsible for any financial losses incurred through its use.
Next Candle Price Prediction FAJnext candle price prediction
Previous Day Data:
prevHigh, prevLow, and prevClose are calculated to capture the high, low, and close of the previous day. This is used to understand the previous day's price range and sentiment.
ATR Calculation:
The Average True Range (ATR) is a measure of volatility. We use it to estimate how much the price might move up or down from the previous close.
Predicted High and Low:
Using the previous close plus and minus the ATR value gives a range where the price might reach.
Predicted Target Price:
The script calculates a simple midpoint of the previous day's range to predict the target price for the next candle. This midpoint serves as a basic prediction, assuming price might oscillate within the previous day's range.
Plotting:
The script plots the predicted high, low, and target price as well as the previous day's high, low, and close for context.
Prometheus NFP LevelsThis script is a tool to mark the high and low of the most recent first Friday of the month. The significance of that day is that’s when the Bureau of Labor Statistics reports the Non Farm Payrolls (NFP) for the month prior. This number includes how many jobs were added that month, the unemployment rate, and labor force participation rate to name a few.
It is always on the first Friday of the new month, and markets tend to care about it quite a bit.
This script also allows a user to get the high and low of a specific date, the default date is the last Federal Open Market Committee day (FOMC). On this day the Federal Reserve announces the Federal Funds Interest Rate, as well as giving guidance on things like bond buying programs, to name a few.
Markets care about these days a lot, that is why we decided to make this script. Prometheus plans to update the default custom date with the most recent FOMC date as they come around.
Here we see the FOMC level high in blue, and low in yellow as well as the NFP high and low in green and red. The white boxes highlight areas where the market reacted to the levels.
On this chart we see a different asset still has interactions with the levels.
We chose to have the user input the date the way we did, not as a timestamp, for this code:
ts_start = timestamp(event_year, event_month, event_day, 9, 30)
ts_end = timestamp(event_year, event_month, event_day+1, 0, 0)
Adding one to the inputted date gives us a simple way to define the time range.
Prometheus encourages users to use indicators as tools along with their own discretion. No indicator is 100% accurate. We encourage comments about requested features and criticism.
Daily Bias Engine | PDH/PDL Range This program is designed to track the previous day range and interactions with the mean threshold on the following day.
The bias strategy is simple:
If you create new range highs over a PDH, you will lean towards calls.
If you create new range lows over a PDL, you will learn towards puts.
If neither event happens, no bias can be determined and therefore no trades taken.
If by 12:00pm there still is no bias determined, it will show moderate strength based on the trend.
Remember, use this strategy to outline your bias and find a cheap entry model to take advantage of.
Weighted US Liquidity ROC Indicator with FED RatesThe Weighted US Liquidity ROC Indicator is a technical indicator that measures the Rate of Change (ROC) of a weighted liquidity index. This index aggregates multiple monetary and liquidity measures to provide a comprehensive view of liquidity in the economy. The ROC of the liquidity index indicates the relative change in this index over a specified period, helping to identify trend changes and market movements.
1. Liquidity Components:
The indicator incorporates various monetary and liquidity measures, including M1, M2, the monetary base, total reserves of depository institutions, money market funds, commercial paper, and repurchase agreements (repos). Each of these components is assigned a weight that reflects its relative importance to overall liquidity.
2. ROC Calculation:
The Rate of Change (ROC) of the weighted liquidity index is calculated by finding the difference between the current value of the index and its value from a previous period (ROC period), then dividing this difference by the value from the previous period. This gives the percentage increase or decrease in the index.
3. Visualization:
The ROC value is plotted as a histogram, with positive and negative changes indicated by different colors. The Federal Funds Rate is also plotted separately to show the impact of central bank policy on liquidity.
Discussion of the Relationship Between Liquidity and Stock Market Returns
The relationship between liquidity and stock market returns has been extensively studied in financial economics. Here are some key insights supported by scientific research:
Liquidity and Stock Returns:
Liquidity Premium Theory: One of the primary theories is the liquidity premium theory, which suggests that assets with higher liquidity typically offer lower returns because investors are willing to accept lower yields for more liquid assets. Conversely, assets with lower liquidity may offer higher returns to compensate for the increased risk associated with their illiquidity (Amihud & Mendelson, 1986).
Empirical Evidence: Research by Fama and French (1992) has shown that liquidity is an important factor in explaining stock returns. Their studies suggest that stocks with lower liquidity tend to have higher expected returns, aligning with the liquidity premium theory.
Market Impact of Liquidity Changes:
Liquidity Shocks: Changes in liquidity can impact stock returns significantly. For example, an increase in liquidity is often associated with higher stock prices, as it reduces the cost of trading and enhances market efficiency (Chordia, Roll, & Subrahmanyam, 2000). Conversely, a liquidity shock, such as a sudden decrease in market liquidity, can lead to higher volatility and lower stock prices.
Financial Crises: During financial crises, liquidity tends to dry up, leading to sharp declines in stock market returns. For instance, studies on the 2008 financial crisis illustrate how a reduction in market liquidity exacerbated the decline in stock prices (Brunnermeier & Pedersen, 2009).
Central Bank Policies and Liquidity:
Monetary Policy Impact: Central bank policies, such as changes in the Federal Funds Rate, directly influence market liquidity. Lower interest rates generally increase liquidity by making borrowing cheaper, which can lead to higher stock market returns. On the other hand, higher rates can reduce liquidity and negatively impact stock prices (Bernanke & Gertler, 1999).
Policy Expectations: The anticipation of changes in monetary policy can also affect stock market returns. For example, expectations of rate cuts can lead to a rise in stock prices even before the actual policy change occurs (Kuttner, 2001).
Key References:
Amihud, Y., & Mendelson, H. (1986). "Asset Pricing and the Bid-Ask Spread." Journal of Financial Economics, 17(2), 223-249.
Fama, E. F., & French, K. R. (1992). "The Cross-Section of Expected Stock Returns." Journal of Finance, 47(2), 427-465.
Chordia, T., Roll, R., & Subrahmanyam, A. (2000). "Market Liquidity and Trading Activity." Journal of Finance, 55(2), 265-289.
Brunnermeier, M. K., & Pedersen, L. H. (2009). "Market Liquidity and Funding Liquidity." Review of Financial Studies, 22(6), 2201-2238.
Bernanke, B. S., & Gertler, M. (1999). "Monetary Policy and Asset Prices." NBER Working Paper No. 7559.
Kuttner, K. N. (2001). "Monetary Policy Surprises and Interest Rates: Evidence from the Fed Funds Futures Market." Journal of Monetary Economics, 47(3), 523-544.
These studies collectively highlight how liquidity influences stock market returns and how changes in liquidity conditions, influenced by monetary policy and other factors, can significantly impact stock prices and market stability.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
3-Criteria StrategyThe "3-Criteria Strategy" is a simple yet effective trading strategy based on three criteria:
200-Day Moving Average: The first criterion checks whether the current price is above or below the 200-day moving average (SMA). A price above the 200-day line is considered bullish (thumbs up), while a price below is considered bearish (thumbs down).
5-Day Indicator: The second criterion evaluates the performance of the first five trading days of the year. If the closing price on the fifth trading day is higher than the closing price on the last trading day of the previous year, this is considered bullish (thumbs up). Otherwise, it's bearish (thumbs down).
Year-to-Date (YTD) Effect: The third criterion compares the current price with the closing price at the end of the previous year. A current price above the year-end price is bullish (thumbs up), while a price below is bearish (thumbs down).
Signal Interpretation:
Buy Signal: At least two of the three criteria must give a bullish signal (thumbs up).
Sell Signal: Zero or one bullish signal results in a bearish outlook.
The script provides visual cues with background colors:
Green background: Indicates a buy signal.
Red background: Indicates a sell signal.
Additionally, the script plots the 200-day moving average and the YTD line on the chart for better visualization.
Usage:
Apply the Script: Add the script to your TradingView chart.
Interpret Signals: Monitor the background color and the status label to determine trading actions.
Visual Aids: Use the 200-day line and YTD line plotted on the chart to confirm the criteria visually.
Scientific Research
The concepts used in this script—like the 200-day moving average and Year-to-Date effects—are well-documented in financial literature. However, the combination of these specific criteria as a trading strategy is more of a heuristic approach commonly used by traders rather than a subject of extensive academic research.
200-Day Moving Average: The 200-day moving average is widely regarded as a significant level in technical analysis, often serving as a demarcation between long-term bullish and bearish trends. Research has shown that long-term moving averages can be useful for trend-following strategies.
Reference: Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. Journal of Finance, 47(5), 1731-1764.
Year-to-Date and Calendar Effects: The Year-to-Date effect and early-year performance (such as the January effect) have been studied extensively in the context of seasonal market anomalies.
Reference: Rozeff, M. S., & Kinney, W. R. (1976). Capital Market Seasonality: The Case of Stock Returns. Journal of Financial Economics, 3(4), 379-402.
While these papers don't address the exact combination of criteria used in your strategy, they provide a solid foundation for understanding the underlying concepts.
Buy and Sell Alerts using VWAPThis is my first script, which I hope you'll enjoy.
The script generates alerts for buy and sell trades using VWAP and volume threshold that you select.
Indicators and Moving Averages :
This script allows you to choose which moving averages like VWAP, 9EMA, 10, 20, 50, 100, 200, and 325 SMAs you want to see on your chart.
Volume Threshold :
You can set a volume threshold, which is the minimum required volume required for buy and sell signals to be considered valid. (For example, I like 60,000 on SPY, 5 minute chart.)
Buy and Sell Signals :
The script checks if the stock prices crosses above or below the VWAP and if the trading volume is above the threshold you set.
If the price crosses above the VWAP and the volume is sufficient, a "Buy" signal is generated.
If the price crosses below the VWAP and the volume is sufficient, a "Sell" signal is generated.
This hopefully user-friendly indicator will alert you when certain conditions trading conditions are met, helping to make it a little easier to make informed trading decisions.
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behavior—both the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's state—whether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
Follow the Volumes / Path of Least ResistanceThis indicator tracks price movements following significant volume increases. It identifies volume spikes by comparing recent average volume to a longer-term average. After a spike, it monitors price changes over a specified number of bars.
In plain English, the point of this is to “let the market show it’s hand”, vs. other common and preemptive methods of execution.
You can think of it as a better version of a volume up/down indicator which only uses opening and closing prices to identify "bullish" or "bearish" behavior.
To optimize this, I used a very small range chart, hence the small values. You will need to experiment with other values, ESPECIALLY the % change. If you do not do this, the indicator will generate a lot of noise.
The indicator has three main conditions:
1. Significant price increase, bullish: A green triangle appears below the bar.
2. Significant price decrease, bearish: A red triangle appears above the bar.
3. Price change within thresholds: A fuschia triangle appears, pointing up or down based on the overall (short-term) trend. This is common behavior during trends. A spike in volume will appear, and price simply does not budge. Volume/price is essentially declaring a new found value, in which case prices tend to follow the impulse movement (see market profile theory).
The color scheme is intuitive: green for positive moves, red for negative, and fuschia for subtle changes following the existing trend. Blue circles mark volume spikes for reference, which I recommend using only for reference, and disabling to remove unneeded noise.
Because this indicator "lags" in the sense of waiting for the market to show its hand, best opportunities are typically found on retests of the volume spikes themselves. On drives, however, the market will unlikely pullback, which (in my view) is one of its best use cases.
Bottom line, you will need to adjust the parameters to the instrument. This is not a plug and play solution, but far more accurate than those which are.
Settings, and what they mean:
Volume spike average bars: length for identification of high volumes. On smaller timeframes, such as my optimization period, you’ll want several bars. But on something such as a 5 minute or higher, only 1.
Lookback period: for identification of high volumes.
Volume Increase Threshold (%): % which constitutes a jump in volume
Bars After Spike: How long to wait for ensuing price movement. Also sensitive to the timeframe you are using. 1-2 recommended for 5m+, more for smaller range-based.
Negative Price Change Threshold (%): For red arrows (Volume + Price Movement)
Positive Price Change Threshold (%): Inverse of above
WMA Period for Stability Function: When price spikes on high volumes but does not move (price is “trapped” between negative and positive price change thresholds) the indicator marks direction (in fuchsia) in the direction of the underlying trend. This short-term MA identifies that trend.
Finally, because this indicator is volume-based, I recommend using primary instruments only and discourage its use on CFDs or other firm-generated instruments. Just use the primary. I would ignore signals off the open, which is subject to erroneous behavior. Other methods are far more effective for that.
This script is purposely uncomplicated. Feel free to play with settings and change code to suit your needs.
Midpoint Candle and BodyThis script provides the options to mark the:
1. Midpoint of the candle body and/or
2. Midpoint of the full candle (including the wicks)
Works on all timeframes. This indicator can be used to help determine the mean (midpoint) reversion of price.
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MM Market Range MapWhat this script does:
The purpose of this script is to help traders identify when the major sectors of the market are moving in one direction - also known as a "market trend day".
How this script works:
The indicator uses QQQ, SMH and NVDA to represent the technology side of the market, and XLF, XLV & IWM to represent everything else. It tracks where price is within the day's range for each of those symbols, and presents that data in a table and in also in a dot-based "map".
How to use this script:
Using the dot-based map, you can see if all symbols were ever at the highs or lows of their range together. You can use this information to decide which direction you should be trading (ie. with trend). For example, in order for there to be healthy bullish moves in the market, you would want this indicator to show you that all sectors are at the highs or trending in that direction.
What makes this script original:
Most indicators and even the TradingView watchlist measure the percent changed on the day from the closing price of a stock on the prior trading day, essentially telling you what sentiment is since yesterday. This script tells you the sentiment today since it is priced from the opening print. It also provides the map so you can see if they were ever at the highs or lows together throughout the day, which can be an early indicator that the market will trend.
Sticky Moving AverageThe Sticky Moving Average is a custom indicator designed to provide a unique smoothing effect by combining different moving averages derived from a single base period. This indicator creates a single line on the chart, representing the average of the following three moving averages:
1. X-period Simple Moving Average (SMA): A traditional moving average that smooths the price data over the full period.
2. X/2-period Simple Moving Average (SMA): A faster-moving average that smooths the price data over half of the base period.
3. X/4-period Exponential Moving Average (EMA): An exponential moving average that gives more weight to recent prices, calculated over one-fourth of the base period.
The result is a moving average that "sticks" to price action by considering both short-term and long-term trends, offering a balanced view of market momentum.
This indicator is ideal for traders looking to gain a nuanced understanding of price movements by incorporating multiple smoothing periods into a single, easy-to-use line. Adjust the `X` value to suit your trading strategy and enjoy the clarity this composite moving average can bring to your charts.
Monte Carlo (Polyline Traceback) [Kioseff Trading]Hello!
This script "Monte Carlo (Polyline Traceback) " performs a Monte Carlo simulation using polylines!
By using polylines, and tracing back the initial simulation to its origin point, we can better replicate the ideal output of a Monte Carlo simulation!
Such as:
The image above shows the output of a simulation (image sourced outside TV).
With this script, and polyline capabilities, we can come quite close on TradingView.
The image above shows the indicator in action! Not bad considering the ideal output.
Of course, the script is quite heavy and tries its best to circumvent limitations :D
You might run into load time errors, in which case you might try applying the built-in setting "Force Script Load". This setting will cut-off the visuals for some simulations, but has a higher chance of passing load-time limitations!
As shown in the image above, you can select to only show worst-case and best-case simulations. Using this option will reduce chart lag and improve load times.
Features
Monte Carlo Simulation: Performs Monte Carlo simulation to generate multiple future paths.
Asset Price: Can simulate future asset prices based on historical log returns.
Statistical Methods: Offers two simulation methods—Gaussian (Normal) distribution and Bootstrapping.
Adjustable Parameters: Offers numerous user-adjustable settings like number of simulations, forecast length, and more.
Historical Data Points: Option to specify the amount of historical data to be used in the simulation (price).
Best/Worst Case: Allows you to show only the best case / worst case outcome (range) for all simulations!
Thank you!
Market Internal Pivots by SyntaxGeekThis indicator combines simple pivot detection with market breadth ratios.
The thought was to show market breadth strength or weakness where price was making potential pivots.
Lookback can be adjusted and currently it supports NYSE and NASDAQ market breadth.
Configuration is limited given the simplicity but live breadth printout can be displayed at current candle.
Max label count is at 500 but the indicator makes use of the visible chart library and will redraw old pivot labels when scrolling back, up to 500.
Considering that market breadth data is only available during RTH, do not expect data during ETH sessions. I've only tested this up to 1hr timeframe so I can't guarantee higher timeframes will present correctly.
Feel free to leave feedback, happy trading!
VIX Futures Basis StrategyVIX Futures Basis Strategy
The VIX Futures Basis Strategy is a trading approach that takes advantage of the unique characteristics of the VIX index and its futures market. The VIX, often referred to as the "fear index," measures market expectations of near-term volatility. This strategy focuses on how the VIX futures contracts behave in relation to the spot VIX index and seeks to capitalize on the market's contango and backwardation phases.
Key Concepts:
VIX Index and VIX Futures:
The VIX index reflects the market's expectation of volatility over the next 30 days.
VIX futures allow traders to speculate on the future value of the VIX index.
Contango and Backwardation:
Contango occurs when the futures price is higher than the spot price, often indicating that the market expects volatility to rise in the future.
Backwardation is when the futures price is lower than the spot price, suggesting that the market expects a decrease in volatility.
Basis:
The basis is the difference between the futures price and the spot price. This strategy examines the basis for two consecutive VIX futures contracts.
Strategy Overview:
The VIX Futures Basis Strategy uses the relationship between the VIX index and its futures contracts to generate trading signals:
Long Position on Contango:
When both the front month and the second month VIX futures contracts are in contango (their prices are above the spot VIX index by a specified threshold), the strategy takes a long position.
This implies an expectation that the market will move from a state of expected higher future volatility to a more stable state, allowing profits to be made as the futures prices converge toward the spot price.
Closing Position on Backwardation:
If the basis for both futures contracts indicates backwardation (their prices are below the spot VIX index by a threshold), the strategy closes any long positions.
This condition suggests that the market anticipates decreasing volatility, and closing positions helps to avoid potential losses.
