Financial Crisis Predictor - Doomsday ClockThe **Financial Crisis Predictor - Doomsday Clock** is a composite indicator that evaluates multiple market conditions to determine financial risk levels. It combines four key metrics: market volatility (via VIX), yield curve spread, stock market momentum, and credit risk (via high-yield spread). Each metric contributes to a weighted "risk score," scaled between 0 and 100, which helps gauge the probability of a financial crisis. Here's a breakdown of how it works:
### 1. **Market Volatility (VIX)**
- **How it's measured:**
- Uses the VIX index, which represents expected market volatility.
- Applies two exponential moving averages (EMAs) to smooth out the data—one fast and one slow.
- Triggers a signal if the fast EMA crosses above the slow EMA and VIX exceeds a defined threshold (default is 30).
- **Weighting:**
- Contributes up to 35% of the total risk score when active.
### 2. **Yield Curve Spread**
- **How it's measured:**
- Takes the difference between the yields of 10-year and 2-year U.S. Treasury bonds (inversion indicates recession risk).
- If the spread drops below a certain threshold (default is 0.2), it signals a potential recession.
- **Weighting:**
- Contributes up to 25% of the risk score.
### 3. **Stock Market Momentum**
- **How it's measured:**
- Analyzes the S&P 500 (SPY) using a 20-day EMA for price momentum.
- Checks for a cross under the 20-day EMA and if the 5-day rate of change (ROC) is less than -2.
- This combination signals bearish market momentum.
- **Weighting:**
- Contributes up to 20% of the risk score.
### 4. **Credit Risk (High Yield Spread)**
- **How it's measured:**
- Assesses high-yield corporate bond spreads using EMAs, similar to the VIX logic.
- A crossover of the fast EMA above the slow EMA combined with spreads exceeding a defined threshold (default is 5.0) indicates increased credit risk.
- **Weighting:**
- Contributes up to 20% of the total risk score.
### 5. **Risk Score Calculation**
- The final **risk score** ranges from 0 to 100 and is calculated using the weighted sum of the four indicators.
- The score is smoothed to minimize false signals and maintain stability.
### 6. **Risk Zones**
- **Extreme Risk:** If the risk score is ≥ 75, indicating a severe crisis warning.
- **High Risk:** If the risk score is between 15 and 75, signaling heightened risk.
- **Moderate Risk:** If the risk score is between 10 and 15, representing potential concerns.
- **Low Risk:** If the risk score is < 10, suggesting stable conditions.
### 7. **Visual & Alerts**
- The indicator plots the risk score on a chart with color-coded backgrounds to indicate risk levels: green (low), yellow (moderate), orange (high), and red (extreme).
- Alert conditions are set for each risk zone, notifying users when the risk level transitions into a higher zone.
This indicator aims to quickly detect potential financial crises by aggregating signals from key market factors, making it a versatile tool for traders, analysts, and risk managers.
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Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
[3Commas] Signal BuilderSignal Builder is a tool designed to help traders create custom buy and sell signals by combining multiple technical indicators. Its flexibility allows traders to set conditions based on their specific strategy, whether they’re into scalping, swing trading, or long-term investing. Additionally, its integration with 3Commas bots makes it a powerful choice for those looking to automate their trades, though it’s also ideal for traders who prefer receiving alerts and making manual decisions.
🔵 How does Signal Builder work?
Signal Builder allows users to define custom conditions using popular technical indicators, which, when met, generate clear buy or sell signals. These signals can be used to trigger TradingView alerts, ensuring that you never miss a market opportunity. Additionally, all conditions are evaluated using "AND" logic, meaning signals are only activated when all user-defined conditions are met. This increases precision and helps avoid false signals.
🔵 Available indicators and recommended settings:
Signal Builder provides access to a wide range of technical indicators, each customizable to popular settings that maximize effectiveness:
RSI (Relative Strength Index): An oscillator that measures the relative strength of price over a specific period. Traders typically configure it with 14 periods, using levels of 30 (oversold) and 70 (overbought) to identify potential reversals.
MACD (Moving Average Convergence Divergence): A key indicator tracking the crossover between two moving averages. Common settings include 12 and 26 periods for the moving averages, with a 9-period signal line to detect trend changes.
Ultimate Oscillator: Combines three different time frames to offer a comprehensive view of buying and selling pressure. Popular settings are 7, 14, and 28 periods.
Bollinger Bands %B: Provides insight into where the price is relative to its upper and lower bands. Standard settings include a 20-period moving average and a standard deviation of 2.
ADX (Average Directional Index): Measures the strength of a trend. Values above 25 typically indicate a strong trend, while values below suggest weak or sideways movement.
Stochastic Oscillator: A momentum indicator comparing the closing price to its range over a defined period. Popular configurations include 14 periods for %K and 3 for %D smoothing.
Parabolic SAR: Ideal for identifying trend reversals and entry/exit points. Commonly configured with a 0.02 step and a 0.2 maximum.
Money Flow Index (MFI): Similar to RSI but incorporates volume into the calculation. Standard settings use 14 periods, with levels of 20 and 80 as oversold and overbought thresholds.
Commodity Channel Index (CCI): Measures the deviation of price from its average. Traders often use a 20-period setting with levels of +100 and -100 to identify extreme overbought or oversold conditions.
Heikin Ashi Candles: These candles smooth out price fluctuations to show clearer trends. Commonly used in trend-following strategies to filter market noise.
🔵 How to use Signal Builder:
Configure indicators: Select the indicators that best fit your strategy and adjust their settings as needed. You can combine multiple indicators to define precise entry and exit conditions.
Define custom signals: Create buy or sell conditions that trigger when your selected indicators meet the criteria you’ve set. For example, configure a buy signal when RSI crosses above 30 and MACD confirms with a bullish crossover.
TradingView alerts: Set up alerts in TradingView to receive real-time notifications when the conditions you’ve defined are met, allowing you to react quickly to market opportunities without constantly monitoring charts.
Monitor with the panel: Signal Builder includes a visual panel that shows active conditions for each indicator in real time, helping you keep track of signals without manually checking each indicator.
🔵 3Commas integration:
In addition to being a valuable tool for any trader, Signal Builder is optimized to work seamlessly with 3Commas bots through Webhooks. This allows you to automate your trades based on the signals you’ve configured, ensuring that no opportunity is missed when your defined conditions are met. If you prefer automation, Signal Builder can send buy or sell signals to your 3Commas bots, enhancing your trading process and helping you manage multiple trades more efficiently.
🔵 Example of use:
Imagine you trade in volatile markets and want to trigger a sell signal when:
Stochastic Oscillator indicates overbought conditions with the %K value crossing below 80.
Bollinger Bands %B shows the price has surpassed the upper band, suggesting a potential reversal.
ADX is below 20, indicating that the trend is weak and could be about to change.
With Signal Builder , you can configure these conditions to trigger a sell signal only when all are met simultaneously. Then, you can set up a TradingView alert to notify you as soon as the signal is activated, giving you the opportunity to react quickly and adjust your strategy accordingly.
👨🏻💻💭 If this tool helps your trading strategy, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Business Cycle Indicators (Normalized)This script aggregates and normalizes several key economic indicators to provide a comprehensive view of the business cycle and overall market conditions. By combining these indicators into a single, normalized average line, the script helps identify overarching trends and shifts in the economy, aiding in more informed trading and investment decisions.
Included Indicators:
Inverted National Financial Conditions Index (NFCI):
Symbol: FRED:NFCI
Measures financial stress in the markets. An inverted NFCI aligns higher values with positive financial conditions.
Inverted Net Percentage of Banks Tightening Lending Standards (DRTSCIS):
Symbol: FRED:DRTSCIS
Reflects changes in bank lending practices. Inverting this indicator means higher values indicate easing lending standards, which is generally positive for economic growth.
HYG Close Price (iShares High Yield Corporate Bond ETF):
Symbol: AMEX:HYG
Represents the performance of high-yield corporate bonds, providing insight into credit market conditions.
Inverted High-Yield Credit Spread (BAMLH0A0HYM2):
Symbol: FRED:BAMLH0A0HYM2
Measures the spread between high-yield bonds and risk-free securities. A narrower (inverted) spread indicates better market conditions.
Manufacturing/Non-Manufacturing New Orders Ratio:
Symbols: ECONOMICS:USMNO (Manufacturing), ECONOMICS:USNMNO (Non-Manufacturing)
Compares manufacturing to non-manufacturing new orders to gauge shifts in economic activity.
US PMI (Purchasing Managers' Index):
Symbol: ECONOMICS:USBCOI
An indicator of the economic health of the manufacturing sector.
10-Year Inflation Breakeven (T10YIE):
Symbol: FRED:T10YIE
Represents market expectations of inflation over the next ten years.
Inverted 10-Year Real Yield (DFII10):
Symbol: FRED:DFII10
Reflects the real yield on 10-year Treasury Inflation-Protected Securities (TIPS). Inverted to align higher values with positive economic sentiment.
Copper/Gold Ratio:
Symbols: CAPITALCOM:COPPER (Copper), TVC:GOLD (Gold)
Compares the prices of copper and gold, often used as a barometer for global economic activity.
Features:
Normalized Indicators: Each indicator is normalized to a 0-100 scale to facilitate direct comparison, regardless of their original units or scales.
Normalized Average Line: Calculates and plots the average of all available normalized indicators, providing a single line that represents the combined economic signals.
Customizable Display:
Show Individual Indicators: Option to display individual normalized indicators for detailed analysis.
Show Normalized Average Line: Option to display the normalized average line for a consolidated view.
Dynamic Labeling: Displays the latest value of the normalized average directly on the chart for quick reference.
How to Use:
Adding the Script:
Apply the script to a chart in TradingView using a timeframe that aligns with the frequency of the economic data (daily or weekly recommended).
Customization:
Show Normalized Average Line: Enabled by default to display the combined indicator.
Show Individual Indicators: Enable this option in the script settings to display all individual normalized indicators.
Interpretation:
Normalized Scale (0-100): Higher values generally indicate stronger economic conditions, while lower values may suggest weakening conditions.
Trend Analysis: Use the normalized average line to identify trends and potential turning points in the business cycle.
Notes:
Data Availability: Ensure you have access to all the data sources used in the script. Some data feeds may require specific TradingView subscriptions.
Indicator Limitations: Economic indicators are subject to revisions and may not reflect real-time market conditions.
No Investment Advice: This script is a tool for analysis and should not be considered as financial advice. Always conduct your own research before making investment decisions.
Statistics plot1. setting the price range
At the beginning of the script, set the price range (interval). Price ranges are used to divide prices into several groups (buckets) and record how many prices have been reached within each group. For example, setting the price range to “10” will divide the price into intervals 0-10, 10-20, 20-30, and so on.
The price range can also be set manually by the user or automatically calculated based on the initial price. This allows for flexibility in adjusting price ranges for different assets and different time frames.
2. aggregate the number of times a price is reached
Record how many times the price reached each price range (e.g., 100-110, 110-120, etc.). This aggregate data is stored in a data structure called an array.
Each element of the array corresponds to a price range, and when a price reaches that range, the corresponding array value is incremented by one. This process is performed in real time, tracking price movements.
3. initializing and extending price ranges
The first bar of the script (when the chart is first loaded) divides the price ranges into several groups and initializes a count of 0 for each range.
When a price reaches a new range, the array is expanded as needed to add the new price range. This allows the script to work with any price movement, even if the price range continues to grow.
4. visualize the number of price arrivals with a histogram
The aggregated number of arrivals per price range is visually displayed in the form of a histogram. This histogram is designed to allow the user to see at a glance which price range is being reached most frequently.
For example, if prices frequently reach the 100-110 range, the histogram bar corresponding to that range will appear higher than the other ranges. This allows you to visually identify price “dwell points” or support and resistance levels.
5. display of moving averages
A moving average (MA) of the number of times a price has been reached is drawn above the histogram. Moving averages are indicators that show a smooth trend for the number of price arrivals and are useful for understanding the overall direction of price movements.
The duration of the moving average (how many data points it is calculated based on) can be set by the user. This allows for flexible analysis of short or long term price trends. 6.
6. price range tracking and labeling
The script keeps track of which price range the current price is located in. Based on this, information related to the current price range is displayed on the chart as labels.
In particular, labels indicate the beginning and end points of the price range, including which range the price was in at the beginning and which range the price reached at the end. These labels are a useful feature to visually identify price ranges on the chart.
7. labeling of current price range
To confirm which price range the current price is in, when a price reaches a specific price range, a label corresponding to that price range is displayed. This label indicates the position of the price in real-time, allowing traders to visually track where the current price is in the area.
8. calculating the start and end points of the range
The script calculates the start and end points of a range with a non-zero number of price arrivals to find the minimum and maximum of the range. This calculation allows you to see where prices are concentrated within a range.
9. out-of-range price processing
When a price reaches outside the range, the script automatically adds the array element corresponding to that price range and inserts the data in the appropriate location for the count. This allows the script to follow the price as it moves unexpectedly.
Normalized ZScoreThe Normalized ZScore Indicator is a dynamic tool designed to help traders identify potential overbought and oversold conditions in the market. It calculates the ZScore of the price movement relative to a moving average, allowing users to track the deviation of price from its average and normalize it within a fixed range for clearer signal generation. The indicator can be used for both trend-following and mean-reversion strategies, offering customizable options for various trading styles.
How It Works
This indicator works by calculating two distinct ZScores:
Standard ZScore: Based on the price deviation from a simple moving average (SMA).
Fast ZScore: Calculated using price deviation from the SMA combined with standard deviation over a shorter period.
The ZScore values are normalized between -100 and 100, allowing for consistent and comparable signal outputs across different assets and timeframes.
Key Features
Customizable MA and Deviation Lengths: Adjust the length of the moving average (MA Length) and deviation (Deviation Length) to suit your trading needs.
Overbought/Oversold Zones: The indicator highlights areas where the market may be overbought or oversold using a user-defined threshold.
Color-Coded Signals: The ZScore plot changes color based on market conditions:
Positive ZScore (overbought) = Customizable Positive Color
Neutral ZScore = Customizable Middle Color
Negative ZScore (oversold) = Customizable Negative Color
Trend Filtering Option: The built-in trend filter helps to enhance signal accuracy by factoring in the overall market trend.
Signal Shapes:
Diamonds: Indicate strong long or short entry signals when ZScore crosses predefined thresholds.
X-Crosses: Indicate weaker long or short entry signals for users preferring caution in their trades.
Inputs
MA Length: Set the length of the moving average used for calculating the ZScore.
Deviation Length: Set the length used for deviation calculations.
OBS Threshold: Set the threshold for defining overbought and oversold zones.
Trend Filter: Enable or disable the trend filter for added signal confidence.
Color Settings: Customize the colors for positive, middle, and negative ZScore values.
Visual Features
ZScore Plot: A smooth and color-coded line plot to visualize the ZScore in real-time.
Overbought/Oversold Zones: Visualized with horizontal lines and fill colors to highlight extremes.
Bar Coloring: Bars change colors when ZScore exceeds overbought/oversold zones, enhancing visual clarity.
Signal Markers: Diamond or X-shaped markers appear on the chart to indicate potential trade signals.
How to Use
Entry Points: Look for the ZScore to cross into overbought/oversold regions for potential reversal trades. Use the diamonds and X-crosses for long and short entries.
Trend Filter: Enable the trend filter to avoid taking trades against the overall market trend.
Customize Settings: Adjust the lengths and colors to match your specific trading strategy and timeframe.
Volume to Shares Outstanding Ratio IndicatorDescription:
This indicator shows the ratio of trading volume to the total number of shares outstanding.
Formula:
Volume to Shares Outstanding Ratio = (Trading Volume / Shares Outstanding) * 100
説明:
このインジケーターは、出来高を発行済株式数で割った比率を表示します。
式:
出来高の割合 = (出来高 / 発行済株式数) × 100
Open-Close Absolute Difference with Threshold CountsThe Open-Close Absolute Difference with Threshold Counts indicator is a versatile tool designed to help traders analyze the volatility and price movements within any given timeframe on their charts. This indicator calculates the absolute difference between the open and close prices for each bar, providing a clear visualization through a color-coded histogram.
Key features include:
• Timeframe Flexibility: Utilizes the current chart’s timeframe, whether it’s a 5-minute, hourly, or daily chart.
• Custom Thresholds: Allows you to set up to four custom threshold levels (Thresholds A, B, C, and D) with default values of 10, 15, 25, and 35, respectively.
• Period Customization: Enables you to define the number of bars (N) over which the indicator calculates the counts, with a default of 100 bars.
• Visual Threshold Lines: Plots horizontal dashed lines on the histogram representing each threshold for easy visual reference.
• Dynamic Counting: Counts and displays the number of times the absolute difference is less than or greater than each threshold within the specified period.
• Customizable Table Position: Offers the flexibility to position the results table anywhere on the chart (e.g., Top Right, Bottom Left).
How It Works:
1. Absolute Difference Calculation:
• For each bar on the chart, the indicator calculates the absolute difference between the open and close prices.
• This difference is plotted as a histogram:
• Green Bars: Close price is higher than the open price.
• Red Bars: Close price is lower than the open price.
2. Threshold Comparison and Counting:
• Compares the absolute difference to each of the four thresholds.
• Determines whether the difference is less than or greater than each threshold.
• Utilizes the ta.sum() function to count occurrences over the specified number of bars (N).
3. Results Table:
• Displays a table with three columns:
• Left Column: Counts where the absolute difference is less than the threshold.
• Middle Column: The threshold value.
• Right Column: Counts where the absolute difference is greater than the threshold.
• The table updates dynamically and can be positioned anywhere on the chart according to your preference.
4. Threshold Lines on Histogram:
• Plots horizontal dashed lines at each threshold level.
• Each line is color-coded for distinction:
• Threshold A: Yellow
• Threshold B: Orange
• Threshold C: Purple
• Threshold D: Blue
How to Use:
1. Add the Indicator to Your Chart:
• Open the Pine Editor on TradingView.
• Copy and paste the provided code into the editor.
• Click “Add to Chart.”
2. Configure Settings:
• Number of Bars (N):
• Set the period over which you want to calculate the counts (default is 100).
• Thresholds A, B, C, D:
• Input your desired threshold values (defaults are 10, 15, 25, 35).
• Table Position:
• Choose where you want the results table to appear on the chart:
• Options include “Top Left,” “Top Center,” “Top Right,” “Bottom Left,” “Bottom Center,” “Bottom Right.”
3. Interpret the Histogram:
• Observe the absolute differences plotted as a histogram.
• Use the color-coded bars to quickly assess whether the close price was higher or lower than the open price.
4. Analyze the Counts Table:
• Review the counts of occurrences where the absolute difference was less than or greater than each threshold.
• Use this data to gauge volatility and price movement intensity over the specified period.
5. Visual Reference with Threshold Lines:
• Refer to the horizontal dashed lines on the histogram to see how the absolute differences align with your thresholds.
Example Use Case:
Suppose you’re analyzing a 5-minute chart for a particular stock and want to understand its short-term volatility:
• Set the Number of Bars (N) to 50 to analyze the recent 50 bars.
• Adjust Thresholds based on the typical price movements of the stock, e.g., Threshold A: 0.5, Threshold B: 1.0, Threshold C: 1.5, Threshold D: 2.0.
• Position the Table at the “Top Right” for easy viewing.
By doing so, you can:
• Quickly see how often the stock experiences significant price movements within 5-minute intervals.
• Make informed decisions about entry and exit points based on the volatility patterns.
• Customize the thresholds and periods as market conditions change.
Benefits:
• Customizable Analysis: Tailor the indicator to fit various trading styles and timeframes.
• Quick Visualization: Instantly assess market volatility and price movement direction.
• Enhanced Decision-Making: Use the counts and visual cues to make more informed trading decisions.
• User-Friendly Interface: Simple configuration and clear display of information.
Note: Always test the indicator with different settings to find the configuration that best suits your trading strategy. This indicator should be used as part of a comprehensive analysis and not as the sole basis for trading decisions.
Volume-Weighted Trend Strength indexVolume-Weighted Trend Strength index (VWTSI)
Introduction
The VWTSI is a custom indicator designed to combine trend strength, volume, and volatility to give traders a comprehensive view of market dynamics. It provides flexibility by allowing you to visualize the indicator as either an oscillator or a moving average.
Features
Dual Visualization: Can be displayed either as an oscillator or as a moving average on the chart.
Volume-Weighted: Adjusts trend strength based on current volume compared to its average.
Volatility-Adjusted: Incorporates market volatility into the trend strength calculation.
Customizable: Various parameters can be fine-tuned to suit different trading environments.
How It Works
1. Trend Strength Calculation
The difference between the fast (10-period) and slow (30-period) EMAs is used to calculate trend strength, which gives a percentage-based indication of the trend's strength
2. Volatility Adjustment
The ATR-based volatility is calculated and used to amplify or reduce the trend strength based on the current market conditions
3. Volume Adjustment
The ratio of current volume to the volume SMA adds another layer of adjustment to the final VWTSI value
4. Final VWTSI Calculation
The VWTSI value is the product of trend strength, volatility factor, and volume ratio
5. Normalization
The final VWTSI is normalized to fit within a range of -100 to 100 for better visualization in oscillator mode
Customization Inputs
Fast EMA Length: Default is 10.
Slow EMA Length: Default is 30.
Volume Length: Default is 14.
Volatility Length (ATR): Default is 20.
Oscillator or MA Mode: Toggle between displaying the indicator as an oscillator or moving average.
EMA GridThe EMA Grid indicator is a powerful tool that calculates the overall market sentiment by comparing the order of 20 different Exponential Moving Averages (EMAs) over various lengths. The indicator assigns a rating based on how well-ordered the EMAs are relative to each other, representing the strength and direction of the market trend. It also smooths out the macro movements using cumulative calculations and visually represents the market sentiment through color-coded bands.
EMA Calculation:
The indicator uses a series of EMAs with different lengths, starting from 5 and going up to 100. Each EMA is calculated either using the exponential moving averages.
The EMAs form the grid that the indicator uses to measure the order and distance between them.
Rating Calculation:
The indicator computes the relative distance between consecutive EMAs and sums these differences.
The cumulative sum is further smoothed using multiple EMAs with different lengths (from 3 to 21). This smooths out short-term fluctuations and helps identify broader trends.
Market Sentiment Rating:
The overall sentiment is calculated by comparing the values of these smoothing EMAs. If the shorter-term EMA is above the longer-term EMA, it contributes positively to the sentiment; otherwise, it contributes negatively.
The final rating is a normalized value based on the relationship between these EMAs, producing a sentiment score between 1 (bullish) and -1 (bearish).
Color Coding and Bands:
The indicator uses the sentiment rating to color the space between the 100 EMA and 200 EMA, representing the strength of the trend.
If the sentiment is bullish (rating > 0), the band is shaded green. If the sentiment is bearish (rating < 0), the band is shaded red.
The intensity of the color is based on the strength of the sentiment, with stronger trends resulting in more saturated colors.
Utility for Traders:
The EMA Grid is ideal for traders looking to gauge the broader market trend by analyzing the structure and alignment of multiple EMAs. The color-coded band between the 100 and 200 EMAs provides an at-a-glance view of market momentum, helping traders make informed decisions based on the trend's strength and direction.
This indicator can be used to identify bullish or bearish conditions and offers a smoothed perspective on market trends, reducing noise and highlighting significant trend shifts.
Candle Closing Strength Indicator (CCS)This indicator measures and displays the closing strength of each candle relative to its range.
It assigns a value from 0 to 100, where
- 0 indicates a close at the candle's low,
- 100 indicates a close at the high, and
- 50 represents a close at the midpoint.
The strength is shown as a number on each candle, color-coded green for values 50 and above (bullish) and red for values below 50 (bearish). This visual representation helps traders quickly assess the strength and direction of price movements across different timeframes.
This is only the price action strength. Further strength can be verified with volume.
Relative Strength and MomentumRelative Strength and Momentum Indicator
Unlock deeper market insights with the Relative Strength and Momentum Indicator—a powerful tool designed to help traders and investors identify the strongest stocks and sectors based on relative performance. This custom indicator displays essential information on relative strength and momentum for up to 15 different symbols, compared against a benchmark index, all within a clear and organized table format.
Key Features:
1. Customizable Inputs: Choose up to 15 symbols to compare, along with a benchmark index, allowing you to tailor the indicator to your trading strategy. The 'Lookback Period' input defines how many weeks of data are analyzed for relative strength and momentum.
2. Relative Strength Calculation: For each selected symbol, the indicator calculates the Relative Strength (RS) against the chosen benchmark. This RS is further refined using an exponential moving average (EMA) to smooth the results, providing a more stable trend overview.
3. Momentum Analysis: Momentum is determined by analyzing the rate of change in relative strength. The indicator calculates a momentum rank for each symbol, based on its relative strength’s improvement or deterioration.
4. Percentile Ranking System: Each symbol is assigned a percentile rank (from 1 to 100) based on its relative strength compared to the others. Similarly, momentum rankings are also assigned from 1 to 100, offering a clear understanding of which assets are outperforming or underperforming.
5. Visual Indicators:
a. Green: Signals improving or stable relative strength and momentum.
b. Red: Indicates declining relative strength or momentum.
c. Aqua: Highlights symbols performing well on both relative strength and momentum—ideal candidates for further analysis.
6. Two Clear Tables:
a. Relative Strength Rank Table: Displays weekly rankings of relative strength for each symbol.
b. Momentum Table: Shows momentum trends, helping you identify which symbols are gaining or losing strength.
7. Color-Coded for Easy Analysis: The tables are color-coded to make analysis quick and straightforward. A green color means the symbol is performing well in terms of relative strength or momentum, while red indicates weaker performance. Aqua marks symbols that are excelling in both areas.
Use Case:
a. Sector Comparison: Identify which sectors or indexes are showing both relative strength and momentum to pick high-potential stocks. This allows you to align with broader market trends for improved trade entries.
b. Stock Selection: Quickly compare symbols within the same sector to find the stronger performers.
Relative Rating Index (RRI)The technical rating is one of the most perfect indicators. The reason is that this indicator is based on a majority vote of multiple indicators. It is logical that the judgment based on a majority vote of multiple indicators would not be inferior to the judgment made using only a single indicator. However, just as any indicator has its shortcomings, the technical rating also has weaknesses. The most significant issue is that it primarily provides only a momentary evaluation of the current situation.
Let's consider this in more detail. In the technical rating, an evaluation of 1.0 by the majority vote of indicators is considered a strong buy. However, in the market, there are naturally varying levels of strength. For example, would a market that only once reached an evaluation of 1.0 within a given period be considered the same as a market that consistently maintains an evaluation of 1.0? The latter clearly shows a stronger trend, but the technical rating does not provide an objective criterion for such differentiation. While it is possible to check the histogram to see how long the buy or sell rating has continued, there is no objective standard for judgment.
The indicator I have created this time compensates for this weakness by using the concept of RSI. As is well known, RSI is an indicator that shows the momentum of the market. RSI typically calculates the strength of the price increase during a 14-period by dividing the total upward movement by the total movement range. Similarly, I thought that if we divide the positive evaluations of the technical rating during a given period by the total evaluations, we could calculate the "momentum of the technical rating," which shows how often positive ratings have appeared during that period.
Below is the calculation formula.
1. Setting the Evaluation Period
Decide the period to calculate (e.g., 14 periods). This is denoted as `n`.
2. Total Positive Ratings of the Technical Rating
Calculate the total number of times the technical rating is evaluated as "strong buy" or "buy" during each period. This is called `positive_sum`.
3. Total Ratings
Count the total number of ratings (including buy, sell, and neutral) during the period. This is called `total_sum`.
4. Calculating the Upward Strength
Divide `positive_sum` by `total_sum` to calculate the ratio of positive ratings in the technical rating. This is called the "ratio of positive ratings."
The ratio of positive ratings, denoted as `P`, is calculated as follows:
P = positive_sum / total_sum
5. Calculating RRI
Following the calculation method of RSI, RRI is calculated by the following formula:
RRI = 100 - (100 / (1 + (P / (1 - P))))
As you can see, the calculation method is similar to that of RSI. Therefore, initially, I intended to name this indicator the Technical Rating RSI. However, RSI calculates based on the difference between the previous bar's price and the current bar's price, whereas this indicator calculates by summing the values of the technical ratings themselves. In the case of prices, if the difference between bars is zero, it indicates a flat market, but in the case of technical rating values, if 1.0 continues for two consecutive periods, it signifies an extremely strong buy rather than a flat market. For this reason, I decided that the calculation method could no longer be considered the same as the traditional RSI, and to avoid confusion, I chose to give this new indicator the name "Relative Rating Index" (RRI), as it provides a new type of numerical evaluation.
The information provided by this indicator is simple. When RRI exceeds 50, it means that more than 50% of the technical rating evaluations during the set period (I recommend 50 periods, but please determine the optimal value based on your timeframe) are buy evaluations. However, since there may be many false signals around exactly 50, I define it as buy-dominant when the value exceeds 60 and sell-dominant when it falls below 40. Additionally, if the graph itself is rising, it indicates that the buying momentum is strengthening, and if it is falling, it indicates that the selling momentum is increasing.
Furthermore, there are lines drawn at 90 and 10, but please note that unlike RSI, these do not indicate overbought or oversold conditions. When RRI exceeds 90, it means that over 90% of the technical rating evaluations during the specified period are buy evaluations, indicating an ongoing extremely strong buy trend. Until the RRI graph turns downward and falls below 90, it should rather be considered a buying opportunity.
With this new indicator, the technical rating becomes an indicator with depth, providing evaluations not only for the moment but over a specified period. I hope you find it helpful in your market analysis.
True Strength Index with Buy/Sell Signals and AlertsThe True Strength Index (TSI) is a momentum oscillator that helps traders identify trends and potential reversal points in the market. Here’s how it works:
1. **Price Change Calculation**:
- **`pc = ta.change(price)`**: This calculates the change in price (current price minus the previous price).
2. **Double Smoothing**:
- **`double_smooth(src, long, short)`**: This function smooths the price change data twice using two Exponential Moving Averages (EMAs):
- The first EMA smooths the raw data.
- The second EMA smooths the result of the first EMA.
- **`double_smoothed_pc`**: The double-smoothed price change.
- **`double_smoothed_abs_pc`**: The double-smoothed absolute price change, which helps normalize the TSI value.
3. **TSI Calculation**:
- **`tsi_value = 100 * (double_smoothed_pc / double_smoothed_abs_pc)`**: This calculates the TSI by dividing the double-smoothed price change by the double-smoothed absolute price change, then multiplying by 100 to scale the value.
- The TSI oscillates around the zero line, indicating momentum. Positive values suggest bullish momentum, while negative values suggest bearish momentum.
4. **Signal Line**:
- **`signal_line = ta.ema(tsi_value, signal)`**: This creates a signal line by applying another EMA to the TSI value. The signal line is typically used to identify entry and exit points.
5. **Buy and Sell Signals**:
- **Buy Signal**: Occurs when the TSI crosses above the signal line (`ta.crossover(tsi_value, signal_line)`), indicating that bullish momentum is strengthening, which might suggest a buying opportunity.
- **Sell Signal**: Occurs when the TSI crosses below the signal line (`ta.crossunder(tsi_value, signal_line)`), indicating that bearish momentum is strengthening, which might suggest a selling opportunity.
6. **Visual Representation**:
- The TSI line and the signal line are plotted on the chart.
- Buy signals are marked with green "BUY" labels below the bars, and sell signals are marked with red "SELL" labels above the bars.
**How to Use It**:
- **Trend Identification**: When the TSI is above zero, it suggests an uptrend; when it's below zero, it suggests a downtrend.
- **Buy/Sell Signals**: Traders often enter a buy trade when the TSI crosses above the signal line and enter a sell trade when the TSI crosses below the signal line.
- **Divergences**: TSI can also be used to spot divergences between the indicator and price action, which can signal potential reversals.
The TSI is particularly useful in identifying the strength of a trend and the potential turning points, making it valuable for trend-following and swing trading strategies.
Sniper Signal- Description
The Sniper Signal is a sophisticated technical indicator designed for traders seeking to maximize accuracy in identifying key turning points within a market. This indicator is built on a dual approach, combining the power of the Wave Trend Momentum Oscillator (WTMO) with the robustness of a long-term Simple Moving Average (SMA), making it an ideal tool for trading in dynamic and trending market environments.
The WTMO is known for its ability to capture momentum and underlying price direction, providing early signals of trend changes. By smoothing price movements using an exponential moving average (EMA), the WTMO accurately identifies when price is overextending in one direction, which may precede a reversal.
The 100-period SMA acts as a critical trend filter, ensuring that trades are only made in the direction of the prevailing market flow. This approach ensures that signals generated by the WTMO align with the long-term trend, filtering out false signals that can appear in sideways or low volatility markets.
The Sniper Signal is not just an indicator that marks entries and exits; it is a complete strategy in itself, designed for traders who understand the importance of trading in the direction of the prevailing trend. Buy signals are generated only when momentum is at its lowest point (WT1 < -5) and the price is supported by a confirmed uptrend (price above the SMA). Conversely, sell signals are only triggered when momentum is at extremely high levels (WT1 > 5) and the market shows clear signs of weakness (price below the SMA).
This combination of momentum and trend analysis creates a balanced approach that allows traders to capture significant moves in the market, while minimizing exposure to unnecessary risk. The Sniper Signal is particularly effective in markets with well-defined trends, where the key to success lies in entering the market at optimal points and exiting before a significant reversal occurs.
In summary, the Sniper Signal is an advanced tool designed for serious traders looking to take advantage of the combination of momentum and trend to execute high probability trades in moving markets.
- How to use the script?
The Sniper Signal indicator code is written in Pine Script, the native programming language of TradingView. To use this indicator, users must copy the code and paste it into the Pine Script editor within the TradingView platform. Once they have done this, they can save and add the script to their chart to begin displaying buy and sell signals directly on their price charts.
When using the Sniper Signal, traders should pay attention to the signals represented by the triangles on the chart: an upward-facing blue triangle indicates a possible buying opportunity, while a downward-facing red triangle suggests a possible selling opportunity. It is crucial that users also watch the 100-period Simple Moving Average (SMA), shown as a gray line on the chart, to ensure that trades align with the overall market trend. This helps filter out less reliable signals and improves the accuracy of trading decisions.
- Open-source reuse
The indicator code is based on common and widely used concepts in technical analysis, such as the Wave Trend Momentum Oscillator (WTMO) and the Simple Moving Average (SMA). These components are not proprietary and are part of the general knowledge in the trading community, which means that many developers can create their own versions based on these same principles.
RSI Trend Following StrategyOverview
The RSI Trend Following Strategy utilizes Relative Strength Index (RSI) to enter the trade for the potential trend continuation. It uses Stochastic indicator to check is the price is not in overbought territory and the MACD to measure the current price momentum. Moreover, it uses the 200-period EMA to filter the counter trend trades with the higher probability. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Two layers trade filtering system: Strategy utilizes MACD and Stochastic indicators measure the current momentum and overbought condition and use 200-period EMA to filter trades against major trend.
Trailing take profit level: After reaching the trailing profit activation level script activates the trailing of long trade using EMA. More information in methodology.
Wide opportunities for strategy optimization: Flexible strategy settings allows users to optimize the strategy entries and exits for chosen trading pair and time frame.
Methodology
The strategy opens long trade when the following price met the conditions:
RSI is above 50 level.
MACD line shall be above the signal line
Both lines of Stochastic shall be not higher than 80 (overbought territory)
Candle’s low shall be above the 200 period EMA
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with trailing EMA(by default = 20 period). If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
MACD Fast Length (by default = 12, period of averaging fast MACD line)
MACD Fast Length (by default = 26, period of averaging slow MACD line)
MACD Signal Smoothing (by default = 9, period of smoothing MACD signal line)
Oscillator MA Type (by default = EMA, available options: SMA, EMA)
Signal Line MA Type (by default = EMA, available options: SMA, EMA)
RSI Length (by default = 14, period for RSI calculation)
Trailing EMA Length (by default = 20, period for EMA, which shall be broken close the trade after trailing profit activation)
Justification of Methodology
This trading strategy is designed to leverage a combination of technical indicators—Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Stochastic Oscillator, and the 200-period Exponential Moving Average (EMA)—to determine optimal entry points for long trades. Additionally, the strategy uses the Average True Range (ATR) for dynamic risk management to adapt to varying market conditions. Let's look in details for which purpose each indicator is used for and why it is used in this combination.
Relative Strength Index (RSI) is a momentum indicator used in technical analysis to measure the speed and change of price movements in a financial market. It helps traders identify whether an asset is potentially overbought (overvalued) or oversold (undervalued), which can indicate a potential reversal or continuation of the current trend.
How RSI Works? RSI tracks the strength of recent price changes. It compares the average gains and losses over a specific period (usually 14 periods) to assess the momentum of an asset. Average gain is the average of all positive price changes over the chosen period. It reflects how much the price has typically increased during upward movements. Average loss is the average of all negative price changes over the same period. It reflects how much the price has typically decreased during downward movements.
RSI calculates these average gains and losses and compares them to create a value between 0 and 100. If the RSI value is above 70, the asset is generally considered overbought, meaning it might be due for a price correction or reversal downward. Conversely, if the RSI value is below 30, the asset is considered oversold, suggesting it could be poised for an upward reversal or recovery. RSI is a useful tool for traders to determine market conditions and make informed decisions about entering or exiting trades based on the perceived strength or weakness of an asset's price movements.
This strategy uses RSI as a short-term trend approximation. If RSI crosses over 50 it means that there is a high probability of short-term trend change from downtrend to uptrend. Therefore RSI above 50 is our first trend filter to look for a long position.
The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in an asset's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line = 12 period EMA − 26 period EMA
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
This strategy uses MACD as a second short-term trend filter. When MACD line crossed over the signal line there is a high probability that uptrend has been started. Therefore MACD line above signal line is our additional short-term trend filter. In conjunction with RSI it decreases probability of following false trend change signals.
The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
This strategy uses stochastic to define the overbought conditions. The logic here is the following: we want to avoid long trades in the overbought territory, because when indicator reaches it there is a high probability that the potential move is gonna be restricted.
The 200-period EMA is a widely recognized indicator for identifying the long-term trend direction. The strategy only trades in the direction of this primary trend to increase the probability of successful trades. For instance, when the price is above the 200 EMA, only long trades are considered, aligning with the overarching trend direction.
Therefore, strategy uses combination of RSI and MACD to increase the probability that price now is in short-term uptrend, Stochastic helps to avoid the trades in the overbought (>80) territory. To increase the probability of opening long trades in the direction of a main trend and avoid local bounces we use 200 period EMA.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.94%
Maximum Single Profit: +15.78%
Net Profit: +1359.21 USDT (+13.59%)
Total Trades: 111 (36.04% win rate)
Profit Factor: 1.413
Maximum Accumulated Loss: 625.02 USDT (-5.85%)
Average Profit per Trade: 12.25 USDT (+0.40%)
Average Trade Duration: 40 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
