Session High Low 2024
Overview of the Code:
Input for Session Times:
You set up inputs for the start and end times of the trading session, allowing you to customize them as needed.
Time Range Function:
A function isTimeInRange checks whether the current time falls within the specified session start and end times.
initialize High and Low:
indicator initialize session high, low, and their corresponding labels and lines.
Tracking Session High and Low:
Within the specified time range, continuously update session1High and session1Low based on the highest and lowest prices encountered.
Time of Session High/Low:
The High_Time and Low_Time are tracked using the ta.valuewhen() function to capture the exact times when the session high and low occur.
Notes Creation:
You format the high and low values along with their timestamps to create notes that will be displayed alongside the lines.
Drawing Lines and Labels:
After the session ends, you check if there is a new session high or low and draw lines and labels accordingly. If a line or label already exists, you delete it before drawing a new one.
Resetting for Next Session:
At the end of the session, the high and low values are reset for the next session.
Suggestions for Improvement:
Dynamic Line Extensions:
Clear Variable Names Used in Code:
Consider using more descriptive names for variables like Entry_Point and SL_Point to make the code easier to understand.
Commenting:
Although the code is well-commented, always ensure the comments explain the "why" behind the code rather than just the "what."
Example Output:
The output will show the highest and lowest prices during the specified session times and the times they occurred formatted correctly. This output is useful for quick reference during trading and aids in making informed decisions.
Added functionality tool tip Note:
Added a tooltip Note to Get All information of Session High Low & Range.
If you need further modifications, enhancements, or specific functionalities added to this script, please let me know!
在腳本中搜尋"雅虎财经+上证指数2024年每天成交额"
Commitment of Trader %R StrategyThis Pine Script strategy utilizes the Commitment of Traders (COT) data to inform trading decisions based on the Williams %R indicator. The script operates in TradingView and includes various functionalities that allow users to customize their trading parameters.
Here’s a breakdown of its key components:
COT Data Import:
The script imports the COT library from TradingView to access historical COT data related to different trader groups (commercial hedgers, large traders, and small traders).
User Inputs:
COT data selection mode (e.g., Auto, Root, Base currency).
Whether to include futures, options, or both.
The trader group to analyze.
The lookback period for calculating the Williams %R.
Upper and lower thresholds for triggering trades.
An option to enable or disable a Simple Moving Average (SMA) filter.
Williams %R Calculation: The script calculates the Williams %R value, which is a momentum indicator that measures overbought or oversold levels based on the highest and lowest prices over a specified period.
SMA Filter: An optional SMA filter allows users to limit trades to conditions where the price is above or below the SMA, depending on the configuration.
Trade Logic: The strategy enters long positions when the Williams %R value exceeds the upper threshold and exits when the value falls below it. Conversely, it enters short positions when the Williams %R value is below the lower threshold and exits when the value rises above it.
Visual Elements: The script visually indicates the Williams %R values and thresholds on the chart, with the option to plot the SMA if enabled.
Commitment of Traders (COT) Data
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides a breakdown of open interest positions held by different types of traders in the U.S. futures markets. It is widely used by traders and analysts to gauge market sentiment and potential price movements.
Data Collection: The COT data is collected from futures commission merchants and is published every Friday, reflecting positions as of the previous Tuesday. The report categorizes traders into three main groups:
Commercial Traders: These are typically hedgers (like producers and processors) who use futures to mitigate risk.
Non-Commercial Traders: Often referred to as speculators, these traders do not have a commercial interest in the underlying commodity but seek to profit from price changes.
Non-reportable Positions: Small traders who do not meet the reporting threshold set by the CFTC.
Interpretation:
Market Sentiment: By analyzing the positions of different trader groups, market participants can gauge sentiment. For instance, if commercial traders are heavily short, it may suggest they expect prices to decline.
Extreme Positions: Some traders look for extreme positions among non-commercial traders as potential reversal signals. For example, if speculators are overwhelmingly long, it might indicate an overbought condition.
Statistical Insights: COT data is often used in conjunction with technical analysis to inform trading decisions. Studies have shown that analyzing COT data can provide valuable insights into future price movements (Lund, 2018; Hurst et al., 2017).
Scientific References
Lund, J. (2018). Understanding the COT Report: An Analysis of Speculative Trading Strategies.
Journal of Derivatives and Hedge Funds, 24(1), 41-52. DOI:10.1057/s41260-018-00107-3
Hurst, B., O'Neill, R., & Roulston, M. (2017). The Impact of COT Reports on Futures Market Prices: An Empirical Analysis. Journal of Futures Markets, 37(8), 763-785.
DOI:10.1002/fut.21849
Commodity Futures Trading Commission (CFTC). (2024). Commitment of Traders. Retrieved from CFTC Official Website.
Pivot-based Swing Highs and LowsRelease Notes for Pivot-based Swing Highs and Lows Indicator with HH, HL, LH, LL and Labels
Version 1.0.0
Release Date: 29th Sept 2024
Overview:
This Pine Script version 5 indicator is designed to identify and display Swing Highs and Swing Lows based on pivot points. The indicator visually marks Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL) on the chart. The release introduces an improved visual representation with dotted lines and colored labels for easy identification of market structure, using plotshape() and line.new().
Key Features:
1. Pivot-Based Swing Identification:
The indicator uses ta.pivothigh() and ta.pivotlow() to detect significant pivot points on the chart.
The length of the pivot can be adjusted through the pivot_length parameter, allowing users to customize the sensitivity of swing identification.
2. Swing Highs and Lows with Labels:
Higher High (HH) and Lower High (LH) points are marked with green downward triangles.
Higher Low (HL) and Lower Low (LL) points are marked with red upward triangles.
The plotshape() function is used to provide clear visual markers, making it easy to spot the changes in market structure.
3. Dotted Line Visuals:
Green Dotted Lines: Connect Higher Highs (HH) and Higher Lows (HL) to their corresponding previous swings.
Red Dotted Lines: Connect Lower Highs (LH) and Lower Lows (LL) to their corresponding previous swings.
The use of color-coded dotted lines ensures better visual understanding of the trend continuation or reversal patterns.
4. Customizable Input:
The user can adjust the pivot_length parameter to fine-tune the detection of pivot highs and lows according to different timeframes or trading strategies.
Usage:
Higher High (HH): Green downward triangle, indicating a new high compared to the previous pivot high.
Lower High (LH): Green downward triangle, indicating a lower high compared to the previous pivot high.
Higher Low (HL): Red upward triangle, indicating a higher low compared to the previous pivot low.
Lower Low (LL): Red upward triangle, indicating a new lower low compared to the previous pivot low.
Dotted Lines: Connect previous swing points, helping users visualize the trend and potential market structure changes.
Improvements:
Label Substitution: In place of label.new() (which might cause issues in some environments), the indicator now uses plotshape() to provide a reliable and visually effective solution for marking swings.
Streamlined Performance: The logic for determining higher highs, lower highs, higher lows, and lower lows has been optimized for smooth performance across multiple timeframes.
Known Limitations:
No Direct Text Labels: Due to the constraints of plotshape(), text labels like "HH", "LH", "HL", and "LL" are not directly displayed. Instead, color-coded shapes are used for easy identification.
How to Use:
Apply the script to your chart via the TradingView Pine Editor.
Customize the pivot_length to suit your trading style or the timeframe you are analyzing.
Monitor the chart for marked Higher Highs, Lower Highs, Higher Lows, and Lower Lows for potential trend continuation or reversal opportunities.
Use the dotted lines to trace the evolution of market structure.
Please share your comments, thoughts. Also please follow me for more scripts in future. Mean time Happy Trading :)
Pivot Points LIVE [CHE]Title:
Pivot Points LIVE Indicator
Subtitle:
Advanced Pivot Point Analysis for Real-Time Trading
Presented by:
Chervolino
Date:
September 24, 2024
Introduction
What are Pivot Points?
Definition:
Pivot Points are technical analysis indicators used to determine potential support and resistance levels in financial markets.
Purpose:
They help traders identify possible price reversal points and make informed trading decisions.
Overview of Pivot Points LIVE :
A comprehensive indicator designed for real-time pivot point analysis.
Offers advanced features for enhanced trading strategies.
Key Features
Pivot Points LIVE Includes:
Dynamic Pivot Highs and Lows:
Automatically detects and plots pivot high (HH, LH) and pivot low (HL, LL) points.
Customizable Visualization:
Multiple options to display markers, price labels, and support/resistance levels.
Fractal Breakouts:
Identifies and marks breakout and breakdown events with symbols.
Line Connection Modes:
Choose between "All Separate" or "Sequential" modes for connecting pivot points.
Pivot Extension Lines:
Extends lines from the latest pivot point to the current bar for trend analysis.
Alerts:
Configurable alerts for breakout and breakdown events.
Inputs and Configuration
Grouping Inputs for Easy Customization:
Source / Length Left / Length Right:
Pivot High Source: High price by default.
Pivot Low Source: Low price by default.
Left and Right Lengths: Define the number of bars to the left and right for pivot detection.
Colors: Customizable colors for pivot high and low markers.
Options:
Display Settings:
Show HH, LL, LH, HL markers and price labels.
Display support/resistance level extensions.
Option to show levels as a fractal chaos channel.
Enable fractal breakout/down symbols.
Line Connection Mode:
Choose between "All Separate" or "Sequential" for connecting lines.
Line Management:
Set maximum number of lines to display.
Customize line colors, widths, and styles.
Pivot Extension Line:
Visibility: Toggle the display of the last pivot extension line.
Customization: Colors, styles, and width for extension lines.
How It Works - Calculating Pivot Points
Pivot High and Pivot Low Detection:
Pivot High (PH):
Identified when a high price is higher than a specified number of bars to its left and right.
Pivot Low (PL):
Identified when a low price is lower than a specified number of bars to its left and right.
Higher Highs, Lower Highs, Higher Lows, Lower Lows:
Higher High (HH): Current PH is higher than the previous PH.
Lower High (LH): Current PH is lower than the previous PH.
Higher Low (HL): Current PL is higher than the previous PL.
Lower Low (LL): Current PL is lower than the previous PL.
Visual Elements
Markers and Labels:
Shapes:
HH and LH: Downward triangles above the bar.
HL and LL: Upward triangles below the bar.
Labels:
Optionally display the price levels of HH, LH, HL, and LL on the chart.
Support and Resistance Levels:
Extensions:
Lines extending from pivot points to indicate potential support and resistance zones.
Chaos Channels:
Display levels as a fractal chaos channel for enhanced trend analysis.
Fractal Breakout Symbols:
Buy Signals: Upward triangles below the bar.
Sell Signals: Downward triangles above the bar.
Slide 7: Line Connection Modes
All Separate Mode:
Description:
Connects pivot highs with pivot highs and pivot lows with pivot lows separately.
Use Case:
Ideal for traders who want to analyze highs and lows independently.
Sequential Mode:
Description:
Connects all pivot points in the order they occur, regardless of being high or low.
Use Case:
Suitable for identifying overall trend direction and momentum.
Pivot Extension Lines
Purpose:
Trend Continuation:
Visualize the continuation of the latest pivot point's price level.
Customization:
Colors:
Differentiate between bullish and bearish extensions.
Styles:
Solid, dashed, or dotted lines based on user preference.
Width:
Adjustable line thickness for better visibility.
Dynamic Updates:
The extension line updates in real-time as new bars form, providing ongoing trend insights.
Alerts and Notifications
Configurable Alerts:
Fractal Break Arrow:
Triggered when a breakout or breakdown occurs.
Long and Short Signals:
Specific alerts for bullish breakouts (Long) and bearish breakdowns (Short).
Benefits:
Timely Notifications:
Stay informed of critical market movements without constant monitoring.
Automated Trading Strategies:
Integrate with trading bots or automated systems for executing trades based on alerts.
Customization and Optimization
User-Friendly Inputs:
Adjustable Parameters:
Tailor pivot detection sensitivity with left and right lengths.
Color and Style Settings:
Match the indicator aesthetics to personal or platform preferences.
Line Management:
Maximum Lines Displayed:
Prevent chart clutter by limiting the number of lines.
Dynamic Line Handling:
Automatically manage and delete old lines to maintain chart clarity.
Flexibility:
Adapt to Different Markets:
Suitable for various financial instruments including stocks, forex, and cryptocurrencies.
Scalability:
Efficiently handles up to 500 labels and 100 lines for comprehensive analysis.
Practical Use Cases
Identifying Key Support and Resistance:
Entry and Exit Points:
Use pivot levels to determine optimal trade entry and exit points.
Trend Confirmation:
Validate market trends through the connection of pivot points.
Breakout and Breakdown Strategies:
Trading Breakouts:
Enter long positions when price breaks above pivot highs.
Trading Breakdowns:
Enter short positions when price breaks below pivot lows.
Risk Management:
Setting Stop-Loss and Take-Profit Levels:
Utilize pivot levels to place strategic stop-loss and take-profit orders.
Slide 12: Benefits for Traders
Real-Time Analysis:
Provides up-to-date pivot points for timely decision-making.
Enhanced Visualization:
Clear markers and lines improve chart readability and analysis efficiency.
Customizable and Flexible:
Adapt the indicator to fit various trading styles and strategies.
Automated Alerts:
Stay ahead with instant notifications on key market events.
Comprehensive Toolset:
Combines pivot points with fractal analysis for deeper market insights.
Conclusion
Pivot Points LIVE is a robust and versatile indicator designed to enhance your trading strategy through real-time pivot point analysis. With its advanced features, customizable settings, and automated alerts, it equips traders with the tools needed to identify key market levels, execute timely trades, and manage risks effectively.
Ready to Elevate Your Trading?
Explore Pivot Points LIVE and integrate it into your trading toolkit today!
Q&A
Questions?
Feel free to ask any questions or request further demonstrations of the Pivot Points LIVE indicator.
Interest Rate Trading (Manually Added Rate Decisions) [TANHEF]Interest Rate Trading: How Interest Rates Can Guide Your Next Move.
How were interest rate decisions added?
All interest rate decision dates were manually retrieved from the 'Record of Policy Actions' and 'Minutes of Actions' on the Federal Reserve's website due to inconsistent dates from other sources. These were manually added as Pine Script currently only identifies rate changes, not pauses.
█ Simple Explanation:
This script is designed for analyzing and backtesting trading strategies based on U.S. interest rate decisions which occur during Federal Open Market Committee (FOMC) meetings, to make trading decisions. No trading strategy is perfect, and it's important to understand that expectations won't always play out. The script leverages historical interest rate changes, including increases, decreases, and pauses, across multiple economic time periods from 1971 to the present. The tool integrates two key data sources for interest rates—USINTR and FEDFUNDS—to support decision-making around rate-based trades. The focus is on identifying opportunities and tracking trades driven by interest rate movements.
█ Interest Rate Decision Sources:
As noted above, each decision date has been manually added from the 'Record of Policy Actions' and 'Minutes of Actions' documents on the Federal Reserve's website. This includes +50 years of more than 600 rate decisions.
█ Interest Rate Data Sources:
USINTR: Reflects broader U.S. interest rate trends, including Treasury yields and various benchmarks. This is the preferred option as it corresponds well to the rate decision dates.
FEDFUNDS: Tracks the Federal Funds Rate, which is a more specific rate targeted by the Federal Reserve. This does not change on the exact same days as the rate decisions that occur at FOMC meetings.
█ Trade Criteria:
A variety of trading conditions are predefined to suit different trading strategies. These conditions include:
Increase/Decrease: Standard rate increases or decreases.
Double/Triple Increase/Decrease: A series of consecutive changes.
Aggressive Increase/Decrease: Rate changes that exceed recent movements.
Pause: Identification of no changes (pauses) between rate decisions, including double or triple pauses.
Complex Patterns: Combinations of pauses, increases, or decreases, such as "Pause after Increase" or "Pause or Increase."
█ Trade Execution and Exit:
The script allows automated trade execution based on selected criteria:
Auto-Entry: Option to enter trades automatically at the first valid period.
Max Trade Duration: Optional exit of trades after a specified number of bars (candles).
Pause Days: Minimum duration (in days) to validate rate pauses as entry conditions. This is especially useful for earlier periods (prior to the 2000s), where rate decisions often seemed random compared to the consistency we see today.
█ Visualization:
Several visual elements enhance the backtesting experience:
Time Period Highlighting: Economic time periods are visually segmented on the chart, each with a unique color. These periods include historical phases such as "Stagflation (1971-1982)" and "Post-Pandemic Recovery (2021-Present)".
Trade and Holding Results: Displays the profit and loss of trades and holding results directly on the chart.
Interest Rate Plot: Plots the interest rate movements on the chart, allowing for real-time tracking of rate changes.
Trade Status: Highlights active long or short positions on the chart.
█ Statistics and Criteria Display:
Stats Table: Summarizes trade results, including wins, losses, and draw percentages for both long and short trades.
Criteria Table: Lists the selected entry and exit criteria for both long and short positions.
█ Economic Time Periods:
The script organizes interest rate decisions into well-defined economic periods, allowing traders to backtest strategies specific to historical contexts like:
(1971-1982) Stagflation
(1983-1990) Reaganomics and Deregulation
(1991-1994) Early 1990s (Recession and Recovery)
(1995-2001) Dot-Com Bubble
(2001-2006) Housing Boom
(2007-2009) Global Financial Crisis
(2009-2015) Great Recession Recovery
(2015-2019) Normalization Period
(2019-2021) COVID-19 Pandemic
(2021-Present) Post-Pandemic Recovery
█ User-Configurable Inputs:
Rate Source Selection: Choose between USINTR or FEDFUNDS as the primary interest rate source.
Trade Criteria Customization: Users can select the criteria for long and short trades, specifying when to enter or exit based on changes in the interest rate.
Time Period: Select the time period that you want to isolate testing a strategy with.
Auto-Entry and Pause Settings: Options to automatically enter trades and specify the number of days to confirm a rate pause.
Max Trade Duration: Limits how long trades can remain open, defined by the number of bars.
█ Trade Logic:
The script manages entries and exits for both long and short trades. It calculates the profit or loss percentage based on the entry and exit prices. The script tracks ongoing trades, dynamically updating the profit or loss as price changes.
█ Examples:
One of the most popular opinions is that when rate starts begin you should sell, then buy back in when rate cuts stop dropping. However, this can be easily proven to be a difficult task. Predicting the end of a rate cut is very difficult to do with the the exception that assumes rates will not fall below 0.25%.
2001-2009
Trade Result: +29.85%
Holding Result: -27.74%
1971-2024
Trade Result: +533%
Holding Result: +5901%
█ Backtest and Real-Time Use:
This backtester is useful for historical analysis and real-time trading. By setting up various entry and exit rules tied to interest rate movements, traders can test and refine strategies based on real historical data and rate decision trends.
This powerful tool allows traders to customize strategies, backtest them through different economic periods, and get visual feedback on their trading performance, helping to make more informed decisions based on interest rate dynamics. The main goal of this indicator is to challenge the belief that future events must mirror the 2001 and 2007 rate cuts. If everyone expects something to happen, it usually doesn’t.
ETH Signal 15m
This strategy uses the Supertrend indicator combined with RSI to generate buy and sell signals, with stop loss (SL) and take profit (TP) conditions based on ATR (Average True Range). Below is a detailed explanation of each part:
1. General Information BINANCE:ETHUSDT.P
Strategy Name: "ETH Signal 15m"
Designed for use on the 15-minute time frame for the ETH pair.
Default capital allocation is 15% of total equity for each trade.
2. Backtest Period
start_time and end_time: Define the start and end time of the backtest period.
start_time = 2024-08-01: Start date of the backtest.
end_time = 2054-01-01: End date of the backtest.
The strategy will only run when the current time falls within this specified range.
3. Supertrend Indicator
Supertrend is a trend-following indicator that provides buy or sell signals based on the direction of price changes.
factor = 2.76: The multiplier used in the Supertrend calculation (increasing this value makes the Supertrend less sensitive to price movements).
atrPeriod = 12: Number of periods used to calculate ATR.
Output:
direction: Determines the buy/sell direction based on Supertrend.
If direction decreases, it signals a buy (Long).
If direction increases, it signals a sell (Short).
4. RSI Indicator
RSI (Relative Strength Index) is a momentum indicator, often used to identify overbought or oversold conditions.
rsiLength = 12: Number of periods used to calculate RSI.
rsiOverbought = 70: RSI level considered overbought.
rsiOversold = 30: RSI level considered oversold.
5. Entry Conditions
Long Entry:
Supertrend gives a buy signal (ta.change(direction) < 0).
RSI must be below the overbought level (rsi < rsiOverbought).
Short Entry:
Supertrend gives a sell signal (ta.change(direction) > 0).
RSI must be above the oversold level (rsi > rsiOversold).
The strategy will only execute trades if the current time is within the backtest period (in_date_range).
6. Stop Loss (SL) and Take Profit (TP) Conditions
ATR (Average True Range) is used to calculate the distance for Stop Loss and Take Profit based on price volatility.
atr = ta.atr(atrPeriod): ATR is calculated using 12 periods.
Stop Loss and Take Profit are calculated as follows:
Long Trade:
Stop Loss: Set at close - 4 * atr (current price minus 4 times the ATR).
Take Profit: Set at close + 2 * atr (current price plus 2 times the ATR).
Short Trade:
Stop Loss: Set at close + 4 * atr (current price plus 4 times the ATR).
Take Profit: Set at close - 2.237 * atr (current price minus 2.237 times the ATR).
Summary:
This strategy enters a Long trade when the Supertrend indicates an upward trend and RSI is not in the overbought region. Conversely, a Short trade is entered when Supertrend signals a downtrend, and RSI is not oversold.
The trade is exited when the price reaches the Stop Loss or Take Profit levels, which are determined based on price volatility (ATR).
Disclaimer:
The content provided in this strategy is for informational and educational purposes only. It is not intended as financial, investment, or trading advice. Trading in cryptocurrency, stocks, or any financial markets involves significant risk, and you may lose more than your initial investment. Past performance is not indicative of future results, and no guarantee of profit can be made. You should consult with a professional financial advisor before making any investment decisions. The creator of this strategy is not responsible for any financial losses or damages incurred as a result of following this strategy. All trades are executed at your own risk.
DP-OCR MTF & MA 2024This script developed is designed for multi-timeframe analysis of previous open, close, and range, with additional signal plots based on various percentage extension levels. It also incorporates EMA calculations for crossover strategies. Here's a quick breakdown of what the script does:
Key Features:
1. Timeframes:
o Two separate timeframes (TF1 and TF2), which can be set by the user (e.g., 15 mins, 30 mins, daily, etc.). The script computes price actions and extensions for both timeframes. For better analysis, use Daily in TF1 and Weekly in TF2
2. Extension Levels:
o Calculates and plots 10%, 21%, 31%, 51%, and 61% extensions (both positive and negative) for each timeframe.
o The most commonly used extension levels are 61%, 31%, -61%, and -21%.
o These extension levels can be turned on or off by the user.
3. Open/Close/Range:
o Tracks the high, low, open, and close for both timeframes.
o Highlights open/close gaps.
o Plots the previous high/low range for both timeframes with a fill and different colors based on price movement.
How to Use:
• You can toggle specific extension levels on or off in the script’s settings.
• For example, when price hits a +61% extension, it could signal a breakout, and when it hits a -61% extension, it may indicate a potential retracement.
• Use these levels in conjunction with your price action analysis to set entry/exit points or stop-loss levels.
4. Today’s Open:
o Plots today’s opening price for both timeframes.
How to Use:
• Use today’s open as a key reference point to determine the day’s price action.
• Compare today’s open with the previous high/low or extension levels to evaluate possible trends or reversals.
5. EMA Calculations:
o The script calculates 5, 15, and 20 period EMAs and plots them on the chart.
o Additional EMA crossover signals can be included for strategy optimization.
How to Use:
• Observe the EMAs for potential crossover signals. For example, a 5-period EMA crossing above a 15-period or 20-period EMA may signal a buy opportunity, while a crossover in the opposite direction may signal a sell.
• Combine the EMA crossovers with extension levels or previous price data to refine your entries and exits.
Customizations Available:
• Users can select whether to display extension levels for either timeframe.
• The script allows automatic adaptation to intraday, daily, weekly, or monthly timeframes based on the current chart settings.
Moreover, the extension levels are calculated based on the previous period’s range, with the most commonly usable extension levels being 61, 31, -61, and -21. These levels are often used for identifying potential price retracements, breakouts, or reversal points in technical analysis.
Greer BuyZone toolGreer BuyZone Tool
Description:
The Greer BuyZone Tool is a custom Pine Script indicator designed to help identify potential long-term investment opportunities by marking BuyZones on the chart. This tool utilizes the Aroon indicator in combination with Fibonacci numbers to define periods where the asset might be a good candidate for dollar-cost averaging.
Features:
BuyZone Detection: The script identifies and marks the beginning and end of a BuyZone with vertical lines and labels.
Visual Markers: A red vertical line and label indicate the start of a BuyZone, while a green vertical line and label mark the end of a BuyZone.
Aroon Indicator Calculation: Utilizes the Aroon indicator with a Fibonacci length (233) to determine key price levels.
How to Use:
Setup: Add the Greer BuyZone Tool to your TradingView chart. It will display vertical lines and labels marking the BuyZone periods.
BuyZone Identification: Use the red lines and labels ("BZ Begins ->>") to identify the start of a BuyZone, and the green lines and labels ("<<- BZ Ends") to determine when the BuyZone ends.
Long-Term Investment: This tool is intended for long-term investing and dollar-cost averaging strategies, not for day trading.
Disclaimer:
This script is provided for informational purposes only and is not intended as financial advice. The Greer BuyZone Tool is designed to assist in identifying potential long-term investment opportunities and is not suitable for day trading. The use of this tool involves risk, and there is no guarantee of profitability. Users are advised to conduct their own research and consult with a qualified financial advisor before making any investment decisions. The creator of this script assumes no liability for any losses or damages resulting from the use of this indicator.
Author: Sean Lee Greer
Date: 9/1/2024
BTC Top Indicator - Extension from 20 Week SMA (Normalized)This Indicator calculates the logarithmic deviation of the BTCUSD price from its 20-week SMA and dynamically normalizes it between a lower signal line (-0.57) and an upper trendline defined by two historical points (May 30, 2011, at 1.75 and March 4, 2024, at 0.45).
The indicator line color changes dynamically:
green below 0
blue at 0.5
red above 1
Ideal for analyzing BTCUSD on the Index chart to identify potential overbought or oversold levels. It's better suited for identifying tops, than bottoms.
Linear and Logarithmic Fibonacci Levels and (Price&Time) FansIntroduction
The Fibonacci Retracement tool is a go-to for traders looking to spot potential support and resistance levels. By measuring the distance between swing highs and lows, you can apply Fibonacci ratios like 0.236, 0.382, and 0.618 to predict key market levels.
Traditionally, these levels are set by dividing this distance into equal parts—known as Linear Levels. A more refined approach, Logarithmic Price and Time Levels, divides the distance into proportionally equal segments. Plus, this indicator now includes Fibonacci fans, adding another layer of analysis by projecting potential price levels using trendlines based on Fibonacci ratios.
This tool makes it easier to identify both Linear and Logarithmic levels while also leveraging Fibonacci fans for a more complete market view.
Applications
Logarithmic Levels and Fibonacci fans are ideal for volatile markets. In crypto, they’re especially effective for BTCUSDT (check out the wick from January 23, 2024). They also help spot accumulation and distribution patterns in high-volume altcoins like FETUSDT . In traditional markets, they’re useful for tracking stocks like TSLA and NVDA with extreme price swings, as well as indices in inflation-affected markets like XU100 , or recession-hit currency pairs like JPYUSD .
How to Use
This indicator is intuitive and similar to TradingView’s Fibonacci Tool. Select your reference levels (Level 1 and Level 0), then tweak the settings to customize your analysis, including adding Fibonacci fans for extra insights.
Why It’s Different
Unlike TradingView’s tool, which forces you to switch to a logarithmic scale (messing with other indicators and trend lines), this indicator lets you view both Linear and Logarithmic levels—and Fibonacci fans on Price and Time Series—without changing your chart’s scale. The original Fibonacci Code was derived from zekicanozkanli, modified and upgraded to plot fib front and back fans as well. Due to TV Max Plot restrictions I need to publish just Front and Back and Front Fibs separately.
Linear and Logarithmic Fibonacci Levels and FansIntroduction
The Fibonacci Retracement tool is a go-to for traders looking to spot potential support and resistance levels. By measuring the distance between swing highs and lows, you can apply Fibonacci ratios like 0.236, 0.382, and 0.618 to predict key market levels.
Traditionally, these levels are set by dividing this distance into equal parts—known as Linear Levels. A more refined approach, Logarithmic Levels, divides the distance into proportionally equal segments. Plus, this indicator now includes Fibonacci fans, adding another layer of analysis by projecting potential price levels using trendlines based on Fibonacci ratios.
This tool makes it easier to identify both Linear and Logarithmic levels while also leveraging Fibonacci fans for a more complete market view.
Applications
Logarithmic Levels and Fibonacci fans are ideal for volatile markets. In crypto, they’re especially effective for BTCUSDT (check out the wick from January 23, 2024). They also help spot accumulation and distribution patterns in high-volume altcoins like FETUSDT . In traditional markets, they’re useful for tracking stocks like TSLA and NVDA with extreme price swings, as well as indices in inflation-affected markets like XU100 , or recession-hit currency pairs like JPYUSD .
How to Use
This indicator is intuitive and similar to TradingView’s Fibonacci Tool. Select your reference levels (Level 1 and Level 0), then tweak the settings to customize your analysis, including adding Fibonacci fans for extra insights.
Why It’s Different
Unlike TradingView’s tool, which forces you to switch to a logarithmic scale (messing with other indicators and trend lines), this indicator lets you view both Linear and Logarithmic levels—and Fibonacci fans—without changing your chart’s scale. The original Fibonacci Code was derived from zekicanozkanli, modified and upgraded to plot fib fans as well.
Logarithmic and Linear Fibonacci LevelsIntroduction
Fibonacci levels are a technical analysis tool used by some traders to identify potential support and resistance levels. The principle for determining these levels is to take the distance between selected reference high and low points (swing high and swing low in general) as 1 unit and mark the ratios derived from the Fibonacci sequence, such as 0.236, 0.382, 0.618, etc., over this 1 unit. In the conventional method of level determination, the 1 unit is divided into equal distances within itself, and Fibonacci levels are determined based on these equal distances. These types of levels are called Linear Levels . A relatively less common method involves dividing the 1 unit into progressively smaller, more accurately described as proportionally equal, distances and determining Fibonacci levels based on these distances. These types are called Logarithmic Levels . The purpose of this indicator is to provide ease of use in determining both Linear and Logarithmic levels.
Where can it be Used?
Logarithmic Levels can be used in any instrument where volatility is high for any reason. Specifically in crypto, Logarithmic Levels work very well for BINANCE:BTCUSDT (to observe this, please study the wick from January 23, 2024). As another example, Logarithmic Levels can be used to identify potential accumulation and distribution schemes in altcoins with relatively high volume and market capitalization (refer to the chart provided above BINANCE:FETUSDT ). Additionally, when analyzing traditional markets, Logarithmic Levels can be beneficial for stocks with highly inflated or deflated prices (e.g., NASDAQ:TSLA , NASDAQ:NVDA ), in stock markets of countries battling high inflation (e.g., BIST:XU100 ), or in currency pairs of countries experiencing a recession (e.g., FX_IDC:JPYUSD ).
How can it be Used?
It is designed similarly to the Fibonacci Tool provided by Trading View to ensure users feel familiar with it. When you start the indicator, select the reference levels (Level 1 and Level 0), then click on the indicator settings to choose specific levels and customize them according to your preferences.
What Makes it Unique?
Indeed, in the Fibonacci Tool provided by Trading View, we can see both linear and logarithmic levels. However, to view logarithmic levels, it is necessary to switch the relevant instrument's Super Chart to a logarithmic scale. This causes the levels we want to remain 'linear' to also be displayed in their logarithmic form, potentially leading to errors in other indicators we use, incorrect functioning of trend lines drawn in linear scaling, and so on. Additionally, when the Super Chart is scaled logarithmically, it prevents the ability to set alerts for prices and trend lines. This indicator was created to avoid these problems without needing to change the chart's scaling method and to allow the simultaneous viewing of both Linear and Logarithmic levels.
[Suitable Hope] Crypto Upside Model 3.0The "Crypto Upside Model 3.0" indicator dynamically calculates the potential price of any cryptocurrency based on various percentages of Ethereum or Bitcoin's market capitalization.
By fetching and analyzing marketcap data from TradingView sources, it allows traders to visualize potential price targets if their chosen cryptocurrency reaches specific market dominance levels. This tool is designed for daily timeframe analysis and can be used to set informed price expectations and strategic investment goals, providing valuable insights for long-term investment planning.
Why using the Crypto Upside Model 3.0?
Strategic Planning: Helps traders and investors set realistic price targets and investment goals by visualizing potential market cap scenarios.
Informed Decision-Making: Provides a data-driven approach to understanding how a cryptocurrency might perform relative to major assets like Bitcoin and Ethereum.
Customizable Analysis: Allows users to choose different comparison assets (ETH or BTC) and visualize various market cap dominance percentages, offering tailored insights.
Daily Timeframe Focus: Ideal for swing traders and long-term investors who operate on a daily analysis timeframe, providing relevant and actionable data.
Bull Markets: Identify potential price targets if your cryptocurrency's market cap increases significantly.
Bear Markets: Assess how much value could be retained relative to major cryptocurrencies.
Strategic Entry/Exit Points: Use the visualized targets to plan entry or exit points in your trading strategy.
Comparative Advantage
Dynamic Adaptation: Unlike fixed indicators, this tool adapts to any active chart, making it versatile for multiple cryptocurrencies.
Market Cap Insights: Provides a unique perspective by linking price targets to market cap dominance, a critical factor in the crypto market.
User Instructions
Setup: Add the " Upside Model 3.0" indicator to your TradingView chart.
Configuration: Use the input settings to select the comparison cryptocurrency (ETH or BTC) and enable the desired market cap percentage plots.
Analysis: The indicator will display potential price targets based on the selected market cap percentages, providing a visual guide for setting price expectations.
Limitations
Marketcap Data Availability: The indicator relies on marketcap data from TradingView, which may not be available for all cryptocurrencies. If the data is unavailable, the indicator will not function for that asset. This tool is more likely to work with older, established cryptocurrencies, as marketcap data for newer cryptocurrencies may not yet be available.
Daily Timeframe Restriction: The indicator is designed to work exclusively on the daily timeframe, limiting its applicability for intraday trading.
Assumptions of Market Dynamics: The calculations assume a direct correlation between market dominance and price, which may not account for other market dynamics and external factors influencing prices.
Data Accuracy: The accuracy of the indicator depends on the reliability of the data provided by TradingView, which may sometimes experience delays or inaccuracies.
Currently available cryptocurrencies: Bitcoin, Ethereum, Solana, Binance Coin, Cardano, Ripple, Polkadot, Avalanche, Chainlink, Litecoin, Dogecoin, Terra, Uniswap, VeChain, Stellar, Internet Computer, Hedera, Filecoin, Monero, Aave, TRON, NEAR Protocol, Compound, Maker,... For all compatible cryptocurrencies, please consult CRYPTOCAP's documentation.
Final notes
Although various sources ask a payment or user data for similar kind of private indicators, this one is entirely free and open source. "Uncanny" isn't it? I hope this indicator will provide you value. Feel free to leave a message if you have any questions or constructive feedback.
Examples of how I use this indicator
When using ETH's historical price as a reference compared to Bitcoin's marketcap, we can notice that price generally has been held between the +-30% and 50% lines of BTC's marketcap. If history is repeating again, we can expect major resistances around the 50% looking ahead into the future. This for me would be a great area to potentially reduce my ETH spot position.
When using SOL's historical price action, we can notice that the 15% line of ETH's marketcap has been a top in the previous cycle. Today SOL (July 2024), is back at this level. Could this be a top again or could price break this 15% level and head perhaps towards 30% which currently sits around $260? Time will tell.
These are 2 simple example of how I interpret the data. I'm keen to hear what other findings with other pairs you can find.
[Pandora] Vast Volatility Treasure TroveINTRODUCTION:
Volatility enthusiasts, prepare for VICTORY on this day of July 4th, 2024! This is my "Vast Volatility Treasure Trove," intended mostly for educational purposes, yet these functions will also exhibit versatility when combined with other algorithms to garner statistical excellence. Once again, I am now ripping the lid off of Pandora's box... of volatility. Inside this script is a 'vast' collection of volatility estimators, reflecting the indicators name. Whether you are a seasoned trader destined to navigate financial strife or an eagerly curious learner, this script offers a comprehensive toolkit for a broad spectrum of volatility analysis. Enjoy your journey through the realm of market volatility with this code!
WHAT IS MARKET VOLATILITY?:
Market volatility refers to various fluctuations in the value of a financial market or asset over a period of time, often characterized by occasional rapid and significant deviations in price. During periods of greater market volatility, evolving conditions of prices can move rapidly in either direction, creating uncertainty for investors with results of sharp declines as well as rapid gains. However, market volatility is a typical aspect expected in financial markets that can also present opportunities for informed decision-making and potential benefits from the price flux.
SCRIPT INTENTION:
Volatility is assuredly omnipresent, waxing and waning in magnitude, and some readers have every intention of studying and/or measuring it. This script serves as an all-in-one armada of volatility estimators for TradingView members. I set out to provide a diverse set of tools to analyze and interpret market volatility, offering volatile insights, and aid with the development of robust trading indicators and strategies.
In today's fast-paced financial markets, understanding and quantifying volatility is informative for both seasoned traders and novice investors. This script is designed to empower users by equipping them with a comprehensive suite of volatility estimators. Each function within this script has been meticulously crafted to address various aspects of volatility, from traditional methods like Garman-Klass and Parkinson to more advanced techniques like Yang-Zhang and my custom experimental algorithms.
Ultimately, this script is more than just a collection of functions. It is a gateway to a deeper understanding of market volatility and a valuable resource for anyone committed to mastering the complexities of financial markets.
SCRIPT CONTENTS:
This script includes a variety of functions designed to measure and analyze market volatility. Where applicable, an input checkbox option provides an unbiased/biased estimate. Below is a brief description of each function in the original order they appear as code upon first publish:
Parkinson Volatility - Estimates volatility emphasizing the high and low range movements.
Alternate Parkinson Volatility - Simpler version of the original Parkinson Volatility that I realized.
Garman-Klass Volatility - Estimates volatility based on high, low, open, and close prices using a formula that adjusts for biases in price dynamics.
Rogers-Satchell-Yoon Volatility #1 - Estimates volatility based on logarithmic differences between high, low, open, and close values.
Rogers-Satchell-Yoon Volatility #2 - Similar estimate to Rogers-Satchell with the same result via an alternate formulation of volatility.
Yang-Zhang Volatility - An advanced volatility estimate combining both strengths of the Garman-Klass and Rogers-Satchell estimators, with weights determined by an alpha parameter.
Yang-Zhang (Modified) Volatility - My experimental modification slightly different from the Yang-Zhang formula with improved computational efficiency.
Selectable Volatility - Basic customizable volatility calculation based on the logarithmic difference between selected numerator and denominator prices (e.g., open, high, low, close).
Close-to-Close Volatility - Estimates volatility using the logarithmic difference between consecutive closing prices. Specifically applicable to data sources without open, high, and low prices.
Open-to-Close Volatility - (Overnight Volatility): Estimates volatility based on the logarithmic difference between the opening price and the last closing price emphasizing overnight gaps.
Hilo Volatility - Estimates volatility using a method similar to Parkinson's method, which considers the logarithm of the high and low prices.
Vantage Volatility - My experimental custom 'vantage' method to estimate volatility similar to Yang-Zhang, which incorporates various factors (Alpha, Beta, Gamma) to generate a weighted logarithmic calculation. This may be a volatility advantage or disadvantage, hence it's name.
Schwert Volatility - Estimates volatility based on arithmetic returns.
Historical Volatility - Estimates volatility considering logarithmic returns.
Annualized Historical Volatility - Estimates annualized volatility using logarithmic returns, adjusted for the number of trading days in a year.
If I omitted any other known varieties, detailed requests for future consideration can be made below for their inclusion into this script within future versions...
BONUS ALGORITHMS:
This script also includes several experimental and bonus functions that push the boundaries of volatility analysis as I understand it. These functions are designed to provide additional insights and also are my ideal notions for traders looking to explore other methods of volatility measurement.
VOLATILITY APPLICATIONS:
Volatility estimators serve a common role across various facets of trading and financial analysis, offering insights into market behavior. These tools are already in instrumental with enhancing risk management practices by providing a deeper understanding of market dynamics and the inherent uncertainty in asset prices. With volatility estimators, traders can effectively quantifying market risk and adjust their strategies accordingly, optimizing portfolio performance and mitigating potential losses. Additionally, volatility estimations may serve as indication for detecting overbought or oversold market conditions, offering probabilistic insights that could inform strategic decisions at turning points. This script
distinctly offers a variety of volatility estimators to navigate intricate financial terrains with informed judgment to address challenges of strategic planning.
CODE REUSE:
You don't have to ask for my permission to use/reuse these functions in your published scripts, simply because I have better things to do than answer requests for the reuse of these functions.
Notice: Unfortunately, I will not provide any integration support into member's projects at all. I have my own projects that require way too much of my day already.
Option Pair ZigzagOptions Pair Zigzag:
Though we can split the chart window and view multiple charts, this indicator is useful when we view options charts.
How this indicator works:
The indicator works in non-overlay mode.
The indicator will find other option pair symbol and load it’s chart in indicator window. It will also draw a zigzag on both the charts. It will also fetch the SPOT symbol and display SPOT Close price of latest candle.
Useful information:
A. Support resistance: Higher High (HH) and Lower Low (LL) markings can be treated as strong support and or resistance and LH, HL markings can be treated as weak support and or resistance.
B. Trend identification: Easy identification of trend based on trend lines and trend markings i.e. Higher High (HH), Lower Low (LL), Lower High (LH), Higher Low (HL)
C. Use of Rate of change (ROC )– Labels drawn on swing points are equipped with ROC% between swing points. ROC% between Call and Put option charts can be compared and used to identify strong and weak moves.
Example:
1. User loads a call option chart of ‘NIFTY240620C23500’ (NIFTY 50 INDEX OPTIONS 20 JUN 2024 CALL 23500)
2. Since user has selected CALL Option, Indicator rules/logic will find PUT Option symbol of same strike and expiry
3. PUT Option chart would then shown in the indicator window
4. Draw zigzag on both the charts
5. Plot labels on both the charts
6. Labels are equipped with a tooltip showing rate of change between 2 pivot points
Input Parameters:
Left bars – Parameter required for plotting zigzag
Right bars – Parameter required for plotting zigzag
Plot HHLL Labels – Enable/disable plotting of labels
Use cases:
Refer to chart snapshots:
1. Buy Call Option or Sell Put Option - How one can trade on formation of a consolidation range
2. Breakdown of Swing structure - One can observe Swing structure (Zigzag) formed on a SPOT chart and trade on break of swing structure
3. Triangle formation - Observe the patterns formed on the SPOT chart and trade either Call or Put options. Example snapshot shows trade based on triangle pattern
Chart Snapshot:
One can split chart window and load base symbol chart which will help to review bases symbol and options chart at the same time.
Buy Call Option or Sell Put Option
Breakdown of Swing structure
Triangle formation
US Presidential Elections (Names & Dates)US Presidential Elections (Names & Dates)
Description :
This indicator marks key dates in US presidential history, highlighting both election days and inauguration dates. It's designed to provide historical context to your charts, allowing you to see how major political events align with market movements.
Key Features:
• Displays US presidential elections from 1936 to 2052
• Shows inauguration dates for each president
• Customizable colors and styles for both election and inauguration markers
• Toggle visibility of election and inauguration labels separately
• Adapts to different timeframes (daily, weekly, monthly)
• Includes president names for historical context
The indicator uses yellow labels for election days and blue labels for inauguration dates. Election labels show the year and "Election", while inauguration labels display the name of the incoming president.
Customization options include:
• Colors for election and inauguration labels and text
• Line widths for both types of events
• Label placement styles
This tool is perfect for traders and analysts who want to correlate political events with market trends over long periods. It provides a unique perspective on how presidential cycles might influence financial markets.
Note: Future elections (2024 onwards) are marked with a placeholder (✅) as the presidents are not yet known.
Use this indicator to:
• Identify potential market patterns around election cycles
• Analyze historical market reactions to specific presidencies
• Add political context to your long-term chart analysis
Enhance your chart analysis with this comprehensive view of US presidential history!
Bloodbath IndicatorThis indicator identifies days where the number of new 52-week lows for all issues exceeds a user-defined threshold (default 4%), potentially signaling a market downturn. The background of the chart turns red on such days, providing a visual alert to traders following the "Bloodbath Sidestepping" strategy.
Based on: "THE RIPPLE EFFECT OF DAILY NEW LOWS," By Ralph Vince and Larry Williams, 2024 Charles H. Dow Award Winner
threshold: Percentage of issues making new 52-week lows to trigger the indicator (default: 4.0).
Usage:
The chart background will turn red on days exceeding the threshold of new 52-week lows.
Limitations:
This indicator relies on historical data and doesn't guarantee future performance.
It focuses solely on new 52-week lows and may miss other market signals.
The strategy may generate false positives and requires further analysis before trading decisions.
Disclaimer:
This script is for informational purposes only and should not be considered financial advice. Always conduct your own research before making any trading decisions.
Sharpe and Sortino Ratios█ OVERVIEW
This indicator calculates the Sharpe and Sortino ratios using a chart symbol's periodic price returns, offering insights into the symbol's risk-adjusted performance. It features the option to calculate these ratios by comparing the periodic returns to a fixed annual rate of return or the returns from another selected symbol's context.
█ CONCEPTS
Returns, risk, and volatility
The return on an investment is the relative gain or loss over a period, often expressed as a percentage. Investment returns can originate from several sources, including capital gains, dividends, and interest income. Many investors seek the highest returns possible in the quest for profit. However, prudent investing and trading entails evaluating such returns against the associated risks (i.e., the uncertainty of returns and the potential for financial losses) for a clearer perspective on overall performance and sustainability.
The profitability of an investment typically comes at the cost of enduring market swings, noise, and general uncertainty. To navigate these turbulent waters, investors and portfolio managers often utilize volatility , a measure of the statistical dispersion of historical returns, as a foundational element in their risk assessments because it provides a tangible way to gauge the uncertainty in returns. High volatility suggests increased uncertainty and, consequently, higher risk, whereas low volatility suggests more stable returns with minimal fluctuations, implying lower risk. These concepts are integral components in several risk-adjusted performance metrics, including the Sharpe and Sortino ratios calculated by this indicator.
Risk-free rate
The risk-free rate represents the rate of return on a hypothetical investment carrying no risk of financial loss. This theoretical rate provides a benchmark for comparing the returns on a risky investment and evaluating whether its excess returns justify the risks. If an investment's returns are at or below the theoretical risk-free rate or the risk premium is below a desired amount, it may suggest that the returns do not compensate for the extra risk, which might be a call to reassess the investment.
Since the risk-free rate is a theoretical concept, investors often utilize proxies for the rate in practice, such as Treasury bills and other government bonds. Conventionally, analysts consider such instruments "risk-free" for a domestic holder, as they are a form of government obligation with a low perceived likelihood of default.
The average yield on short-term Treasury bills, influenced by economic conditions, monetary policies, and inflation expectations, has historically hovered around 2-3% over the long term. This range also aligns with central banks' inflation targets. As such, one may interpret a value within this range as a minimum proxy for the risk-free rate, as it may correspond to the minimum rate required to maintain purchasing power over time. This indicator uses a default value of 2% as the risk-free rate in its Sharpe and Sortino ratio calculations. Users can adjust this value from the "Risk-free rate of return" input in the "Settings/Inputs" tab.
Sharpe and Sortino ratios
The Sharpe and Sortino ratios are two of the most widely used metrics that offer insight into an investment's risk-adjusted performance . They provide a standardized framework to compare the effectiveness of investments relative to their perceived risks. These metrics can help investors determine whether the returns justify the risks taken to achieve them, promoting more informed investment decisions.
Both metrics measure risk-adjusted performance similarly. However, they have some differences in their formulas and their interpretation:
1. Sharpe ratio
The Sharpe ratio , developed by Nobel laureate William F. Sharpe, measures the performance of an investment compared to a theoretically risk-free asset, adjusted for the investment risk. The ratio uses the following formula:
Sharpe Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑎
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑎 = Standard deviation of the investment's returns (volatility)
A higher Sharpe ratio indicates a more favorable risk-adjusted return, as it signifies that the investment produced higher excess returns per unit of increase in total perceived risk.
2. Sortino ratio
The Sortino ratio is a modified form of the Sharpe ratio that only considers downside volatility , i.e., the volatility of returns below the theoretical risk-free benchmark. Although it shares close similarities with the Sharpe ratio, it can produce very different values, especially when the returns do not have a symmetrical distribution, since it does not penalize upside and downside volatility equally. The ratio uses the following formula:
Sortino Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑑
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑑 = Downside deviation (standard deviation of negative excess returns, or downside volatility)
The Sortino ratio offers an alternative perspective on an investment's return-generating efficiency since it does not consider upside volatility in its calculation. A higher Sortino ratio signifies that the investment produced higher excess returns per unit of increase in perceived downside risk.
The risk-free rate (𝑅𝑓) in the numerator of both ratio formulas acts as a baseline for comparing an investment's performance to a theoretical risk-free alternative. By subtracting the risk-free rate from the expected return (𝑅𝑎−𝑅𝑓), the numerator essentially represents the risk premium of the investment.
Comparison with another symbol
In addition to the conventional Sharpe and Sortino ratios, which compare an instrument's returns to a risk-free rate, this indicator can also compare returns to a user-specified benchmark symbol , allowing the calculation of Information ratios .
An Information ratio is a generalized form of the Sharpe ratio that compares an investment's returns to a risky benchmark , such as SPY, rather than a risk-free rate. It measures the investment's active return (the difference between its returns and the benchmark returns) relative to its tracking error (i.e., the volatility of the active return) using the following formula:
𝐼𝑅 = (𝑅𝑝 − 𝑅𝑏) / 𝑇𝐸
Where:
• 𝑅𝑝 = Average return on the portfolio or investment
• 𝑅𝑏 = Average return from the benchmark instrument
• 𝑇𝐸 = Tracking error (volatility of 𝑅𝑝 − 𝑅𝑏)
Comparing returns to a benchmark instrument rather than a theoretical risk-free rate offers unique insights into risk-adjusted performance. Higher Information ratios signify that the investment produced higher active returns per unit of increase in risk relative to the benchmark. Conventional choices for non-risk-free benchmarks include major composite indices like the S&P 500 and DJIA, as the resulting ratios can provide insight into the effectiveness of an investment relative to the broader market.
Users can enable this generalized calculation for both the Sharpe and Sortino ratios by selecting the "Benchmark symbol returns" option from the "Benchmark type" dropdown in the "Settings/Inputs" tab.
It's crucial to note that this indicator compares the charts symbol's rate of change (return) to the rate of change in the benchmark symbol. Consequently, not all symbols available on TradingView are suitable for use with these ratios due to the nature of what their values represent. For instance, using a bond as a benchmark will produce distorted results since each bar's values represent yields rather than prices, meaning it compares the rate of change in the yield. To maintain consistency and relevance in the calculated ratios, ensure the values from the compared symbols strictly represent price information.
█ FEATURES
This indicator provides traders with two widely used metrics for assessing risk-adjusted performance, generalized to allow users to compare the chart symbol's price returns to a fixed risk-free rate or the returns from another risky symbol. Below are the key features of this indicator:
Timeframe selection
The "Returns timeframe" input determines the timeframe of the calculated price returns. Users can select any value greater than or equal to the chart's timeframe. The default timeframe is "1M".
Periodic returns tracking
This indicator compounds and collects requested price returns from the selected timeframe over monthly or daily periods, similar to how the Broker Emulator works when calculating strategy performance metrics on trade data. It employs the following logic:
• Track returns over monthly periods if the chart's data spans at least two months.
• Track returns over daily periods if the chart's data spans at least two days but not two months.
• Do not track or collect returns if the data spans less than two days, as the amount of data is insufficient for meaningful ratio calculations.
The indicator uses the returns collected from up to a specified number of periods to calculate the Sharpe and Sortino ratios, depending on the available historical data. It also uses these periodic returns to calculate the average returns it displays in the Data Window.
Users can control the maximum number of periods the indicator analyzes with the "Max no. of periods used" input in the "Settings/Inputs" tab. The default value is 60 periods.
Benchmark specification
The "Benchmark return type" input specifies the benchmark type the indicator compares to the chart symbol's returns in the ratio calculations. It features the following two options:
• "Risk-free rate of return (%)": Compares the price returns to a user-specified annual rate of return representing a theoretical risk-free rate (e.g., 2%).
• "Benchmark symbol return": Compares the price returns to a selected benchmark symbol (e.g., "AMEX:SPY) to calculate Information ratios.
When comparing a chart symbol's returns to a specified benchmark symbol, this indicator aligns the times of data points from the benchmark with the times of data points from the chart's symbol to facilitate a fair comparison between symbols with different active sessions.
Visualization and display
• The indicator displays the periodic returns requested from the specified "Returns timeframe" in a separate pane. The plot includes dynamic colors to signify positive and negative returns.
• When the "Returns timeframe" value represents a higher timeframe, the indicator displays background highlights on the main chart pane to signify when a new value is available and whether the return is positive or negative.
• When the specified benchmark return type is a benchmark symbol, the indicator displays the requested symbol's returns in the separate pane as a gray line for visual comparison.
• Within the separate pane, the indicator displays a single-cell table that shows the base period it uses for periodic returns, the number of periods it uses in the calculation, the timeframe of the requested data, and the calculated Sharpe and Sortino ratios.
• The Data Window displays the chart symbol and benchmark returns, their periodic averages, and the Sharpe and Sortino ratios.
█ FOR Pine Script™ CODERS
• This script utilizes the functions from our RiskMetrics library to determine the size of the periods, calculate and collect periodic returns, and compute the Sharpe and Sortino ratios.
• The `getAlignedPrices()` function in this script requests price data for the chart's symbol and a benchmark symbol with consistent time alignment by utilizing spread symbols , which helps facilitate a fair comparison between different symbol types. Retrieving prices from spreads avoids potential information loss and data misalignment that can otherwise occur when using separate requests from each symbol's context when those symbols have different sessions or data times.
• For consistency, the `getAlignedPrices()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences for fair comparison between futures instruments.
• This script uses the `changePercent()` function from our ta library to calculate the percentage changes of the requested data.
• The newly released `force_overlay` parameter in display-related functions allows indicators to display visuals on the main chart and a separate pane simultaneously. We use the parameter in this script's bgcolor() call to display background highlights on the main chart.
Look first. Then leap.
Smart Money Analysis with Golden/Death Cross [YourTradingSensei]Description of the script "Smart Money Analysis with Golden/Death Cross":
This TradingView script is designed for market analysis based on the concept of "Smart Money" and includes the detection of Golden Cross and Death Cross signals.
Key features of the script:
Moving Averages (SMA):
Two moving averages are calculated: a short-term (50 periods) and a long-term (200 periods).
The intersections of these moving averages are used to determine Golden Cross and Death Cross signals.
High Volume:
The current trading volume is analyzed.
Periods of high volume are identified when the current volume exceeds the average volume by a specified multiplier.
Support and Resistance Levels:
Key support and resistance levels are determined based on the highest and lowest prices over a specified period.
Buy and Sell Signals:
Buy and sell signals are generated based on moving average crossovers, high volume, and the closing price relative to key levels.
Golden Cross and Death Cross:
A Golden Cross occurs when the short-term moving average crosses above the long-term moving average.
A Death Cross occurs when the short-term moving average crosses below the long-term moving average.
These signals are displayed on the chart with text color changes for better visualization.
Using the script:
The script helps traders visualize key signals and levels, aiding in making informed trading decisions based on the behavior of major market players and technical analysis.
Custom candle lighting(CCL) © 2024 by YourTradingSensei is licensed under CC BY-NC-SA 4.0. To view a copy of this license.
Intellect_city - Halvings Bitcoin CycleWhat is halving?
The halving timer shows when the next Bitcoin halving will occur, as well as the dates of past halvings. This event occurs every 210,000 blocks, which is approximately every 4 years. Halving reduces the emission reward by half. The original Bitcoin reward was 50 BTC per block found.
Why is halving necessary?
Halving allows you to maintain an algorithmically specified emission level. Anyone can verify that no more than 21 million bitcoins can be issued using this algorithm. Moreover, everyone can see how much was issued earlier, at what speed the emission is happening now, and how many bitcoins remain to be mined in the future. Even a sharp increase or decrease in mining capacity will not significantly affect this process. In this case, during the next difficulty recalculation, which occurs every 2014 blocks, the mining difficulty will be recalculated so that blocks are still found approximately once every ten minutes.
How does halving work in Bitcoin blocks?
The miner who collects the block adds a so-called coinbase transaction. This transaction has no entry, only exit with the receipt of emission coins to your address. If the miner's block wins, then the entire network will consider these coins to have been obtained through legitimate means. The maximum reward size is determined by the algorithm; the miner can specify the maximum reward size for the current period or less. If he puts the reward higher than possible, the network will reject such a block and the miner will not receive anything. After each halving, miners have to halve the reward they assign to themselves, otherwise their blocks will be rejected and will not make it to the main branch of the blockchain.
The impact of halving on the price of Bitcoin
It is believed that with constant demand, a halving of supply should double the value of the asset. In practice, the market knows when the halving will occur and prepares for this event in advance. Typically, the Bitcoin rate begins to rise about six months before the halving, and during the halving itself it does not change much. On average for past periods, the upper peak of the rate can be observed more than a year after the halving. It is almost impossible to predict future periods because, in addition to the reduction in emissions, many other factors influence the exchange rate. For example, major hacks or bankruptcies of crypto companies, the situation on the stock market, manipulation of “whales,” or changes in legislative regulation.
---------------------------------------------
Table - Past and future Bitcoin halvings:
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Date: Number of blocks: Award:
0 - 03-01-2009 - 0 block - 50 BTC
1 - 28-11-2012 - 210000 block - 25 BTC
2 - 09-07-2016 - 420000 block - 12.5 BTC
3 - 11-05-2020 - 630000 block - 6.25 BTC
4 - 20-04-2024 - 840000 block - 3.125 BTC
5 - 24-03-2028 - 1050000 block - 1.5625 BTC
6 - 26-02-2032 - 1260000 block - 0.78125 BTC
7 - 30-01-2036 - 1470000 block - 0.390625 BTC
8 - 03-01-2040 - 1680000 block - 0.1953125 BTC
9 - 07-12-2043 - 1890000 block - 0.09765625 BTC
10 - 10-11-2047 - 2100000 block - 0.04882813 BTC
11 - 14-10-2051 - 2310000 block - 0.02441406 BTC
12 - 17-09-2055 - 2520000 block - 0.01220703 BTC
13 - 21-08-2059 - 2730000 block - 0.00610352 BTC
14 - 25-07-2063 - 2940000 block - 0.00305176 BTC
15 - 28-06-2067 - 3150000 block - 0.00152588 BTC
16 - 01-06-2071 - 3360000 block - 0.00076294 BTC
17 - 05-05-2075 - 3570000 block - 0.00038147 BTC
18 - 08-04-2079 - 3780000 block - 0.00019073 BTC
19 - 12-03-2083 - 3990000 block - 0.00009537 BTC
20 - 13-02-2087 - 4200000 block - 0.00004768 BTC
21 - 17-01-2091 - 4410000 block - 0.00002384 BTC
22 - 21-12-2094 - 4620000 block - 0.00001192 BTC
23 - 24-11-2098 - 4830000 block - 0.00000596 BTC
24 - 29-10-2102 - 5040000 block - 0.00000298 BTC
25 - 02-10-2106 - 5250000 block - 0.00000149 BTC
26 - 05-09-2110 - 5460000 block - 0.00000075 BTC
27 - 09-08-2114 - 5670000 block - 0.00000037 BTC
28 - 13-07-2118 - 5880000 block - 0.00000019 BTC
29 - 16-06-2122 - 6090000 block - 0.00000009 BTC
30 - 20-05-2126 - 6300000 block - 0.00000005 BTC
31 - 23-04-2130 - 6510000 block - 0.00000002 BTC
32 - 27-03-2134 - 6720000 block - 0.00000001 BTC
MarkdownUtilsLibrary "MarkdownUtils"
This library shows all of CommonMark's formatting elements that are currently (2024-03-30)
available in Pine Script® and gives some hints on how to use them.
The documentation will be in the tooltip of each of the following functions. It is also
logged into Pine Logs by default if it is called. We can disable the logging by setting `pLog = false`.
mediumMathematicalSpace()
Medium mathematical space that can be used in e.g. the library names like `Markdown Utils`.
Returns: The medium mathematical space character U+205F between those double quotes " ".
zeroWidthSpace()
Zero-width space.
Returns: The zero-width character U+200B between those double quotes "".
stableSpace(pCount)
Consecutive space characters in Pine Script® are replaced by a single space character on output.
Therefore we require a "stable" space to properly indent text e.g. in Pine Logs. To use it in code blocks
of a description like this one, we have to copy the 2(!) characters between the following reverse brackets instead:
# > <
Those are the zero-width character U+200B and a space.
Of course, this can also be used within a text to add some extra spaces.
Parameters:
pCount (simple int)
Returns: A zero-width space combined with a space character.
headers(pLog)
Headers
```
# H1
## H2
### H3
#### H4
##### H5
###### H6
```
*results in*
# H1
## H2
### H3
#### H4
##### H5
###### H6
*Best practices*: Add blank line before and after each header.
Parameters:
pLog (bool)
paragrahps(pLog)
Paragraphs
```
First paragraph
Second paragraph
```
*results in*
First paragraph
Second paragraph
Parameters:
pLog (bool)
lineBreaks(pLog)
Line breaks
```
First row
Second row
```
*results in*
First row\
Second row
Parameters:
pLog (bool)
emphasis(pLog)
Emphasis
With surrounding `*` and `~` we can emphasize text as follows. All emphasis can be arbitrarily combined.
```
*Italics*, **Bold**, ***Bold italics***, ~~Scratch~~
```
*results in*
*Italics*, **Bold**, ***Bold italics***, ~~Scratch~~
Parameters:
pLog (bool)
blockquotes(pLog)
Blockquotes
Lines starting with at least one `>` followed by a space and text build block quotes.
```
Text before blockquotes.
> 1st main blockquote
>
> 1st main blockquote
>
>> 1st 1-nested blockquote
>
>>> 1st 2-nested blockquote
>
>>>> 1st 3-nested blockquote
>
>>>>> 1st 4-nested blockquote
>
>>>>>> 1st 5-nested blockquote
>
>>>>>>> 1st 6-nested blockquote
>
>>>>>>>> 1st 7-nested blockquote
>
> 2nd main blockquote, 1st paragraph, 1st row\
> 2nd main blockquote, 1st paragraph, 2nd row
>
> 2nd main blockquote, 2nd paragraph, 1st row\
> 2nd main blockquote, 2nd paragraph, 2nd row
>
>> 2nd nested blockquote, 1st paragraph, 1st row\
>> 2nd nested blockquote, 1st paragraph, 2nd row
>
>> 2nd nested blockquote, 2nd paragraph, 1st row\
>> 2nd nested blockquote, 2nd paragraph, 2nd row
Text after blockquotes.
```
*results in*
Text before blockquotes.
> 1st main blockquote
>
>> 1st 1-nested blockquote
>
>>> 1st 2-nested blockquote
>
>>>> 1st 3-nested blockquote
>
>>>>> 1st 4-nested blockquote
>
>>>>>> 1st 5-nested blockquote
>
>>>>>>> 1st 6-nested blockquote
>
>>>>>>>> 1st 7-nested blockquote
>
> 2nd main blockquote, 1st paragraph, 1st row\
> 2nd main blockquote, 1st paragraph, 2nd row
>
> 2nd main blockquote, 2nd paragraph, 1st row\
> 2nd main blockquote, 2nd paragraph, 2nd row
>
>> 2nd nested blockquote, 1st paragraph, 1st row\
>> 2nd nested blockquote, 1st paragraph, 2nd row
>
>> 2nd nested blockquote, 2nd paragraph, 1st row\
>> 2nd nested blockquote, 2nd paragraph, 2nd row
Text after blockquotes.
*Best practices*: Add blank line before and after each (nested) blockquote.
Parameters:
pLog (bool)
lists(pLog)
Paragraphs
#### Ordered lists
The first line starting with a number combined with a delimiter `.` or `)` starts an ordered
list. The list's numbering starts with the given number. All following lines that also start
with whatever number and the same delimiter add items to the list.
#### Unordered lists
A line starting with a `-`, `*` or `+` becomes an unordered list item. All consecutive items with
the same start symbol build a separate list. Therefore every list can only have a single symbol.
#### General information
To start a new list either use the other delimiter or add some non-list text between.
List items in Pine Script® allow line breaks but cannot have paragraphs or blockquotes.
Lists Pine Script® cannot be nested.
```
1) 1st list, 1st item, 1st row\
1st list, 1st item, 2nd row
1) 1st list, 2nd item, 1st row\
1st list, 2nd item, 2nd row
1) 1st list, 2nd item, 1st row\
1st list, 2nd item, 2nd row
1. 2nd list, 1st item, 1st row\
2nd list, 1st item, 2nd row
Intermediary text.
1. 3rd list
Intermediary text (sorry, unfortunately without proper spacing).
8. 4th list, 8th item
8. 4th list, 9th item
Intermediary text.
- 1st list, 1st item
- 1st list, 2nd item
* 2nd list, 1st item
* 2nd list, 2nd item
Intermediary text.
+ 3rd list, 1st item
+ 3rd list, 2nd item
```
*results in*
1) 1st list, 1st item, 1st row\
1st list, 1st item, 2nd row
1) 1st list, 2nd item, 1st row\
1st list, 2nd item, 2nd row
1) 1st list, 2nd item, 1st row\
1st list, 2nd item, 2nd row
1. 2nd list, 1st item, 1st row\
2nd list, 1st item, 2nd row
Intermediary text.
1. 3rd list
Intermediary text (sorry, unfortunately without proper spacing).
8. 4th list, 8th item
8. 4th list, 9th item
Intermediary text.
- 1st list, 1st item
- 1st list, 2nd item
* 2nd list, 1st item
* 2nd list, 2nd item
Intermediary text.
+ 3rd list, 1st item
+ 3rd list, 2nd item
Parameters:
pLog (bool)
code(pLog)
### Code
`` `Inline code` `` is formatted like this.
To write above line we wrote `` `` `Inline code` `` ``.
And to write that line we added another pair of `` `` `` around that code and
a zero-width space of function between the inner `` `` ``.
### Code blocks
can be formatted like that:
~~~
```
export method codeBlock() =>
"code block"
```
~~~
Or like that:
```
~~~
export method codeBlock() =>
"code block"
~~~
```
To write ````` within a code block we can either surround it with `~~~`.
Or we "escape" those ````` by only the zero-width space of function (stableSpace) in between.
To escape \` within a text we use `` \` ``.
Parameters:
pLog (bool)
horizontalRules(pLog)
Horizontal rules
At least three connected `*`, `-` or `_` in a separate line build a horizontal rule.
```
Intermediary text.
---
Intermediary text.
***
Intermediary text.
___
Intermediary text.
```
*results in*
Intermediary text.
---
Intermediary text.
***
Intermediary text.
___
Intermediary text.
*Best practices*: Add blank line before and after each horizontal rule.
Parameters:
pLog (bool)
tables(pLog)
Tables
A table consists of a single header line with columns separated by `|`
and followed by a row of alignment indicators for either left (`---`, `:---`), centered (`:---:`) and right (`---:`)
A table can contain several rows of data.
The table can be written as follows but hasn't to be formatte like that. By adding (stableSpace)
on the correct side of the header we could even adjust the spacing if we don't like it as it is. Only around
the column separator we should only use a usual space on each side.
```
Header 1 | Header 1 | Header 2 | Header 3
--- | :--- | :----: | ---:
Left (Default) | Left | Centered | Right
Left (Default) | Left | Centered | Right
```
*results in*
Header 1 | Header 1 | Header 2 | Header 3
--- | :--- | :----: | ---:
Left (Default) | Left | Centered | Right
Left (Default) | Left | Centered | Right
Parameters:
pLog (bool)
links(pLog)
## Links.
### Inline-style
` (Here should be the link to the TradingView homepage)`\
results in (Here should be the link to the TradingView homepage)
` (Here should be the link to the TradingView homepage "Trading View tooltip")`\
results in (Here should be the link to the TradingView homepage "Trading View tooltip")
### Reference-style
One can also collect all links e.g. at the end of a description and use a reference to that as follows.
` `\
results in .
` `\
results in .
` `\
results in .
` (../tradingview/scripts/readme)`\
results in (../tradingview/scripts/readme).
### URLs and email
URLs are also identified by the protocol identifier, email addresses by `@`. They can also be surrounded by `<` and `>`.
Input | Result
--- | ---
`Here should be the link to the TradingView homepage` | Here should be the link to the TradingView homepage
`` |
`support@tradingview.com` | support@tradingview.com
`` |
## Images
We can display gif, jp(e)g and png files in our documentation, if we add `!` before a link.
### Inline-style:
`! (Here should be the link to the favicon of the TradingView homepage "Trading View icon")`
results in
! (Here should be the link to the favicon of the TradingView homepage "Trading View icon")\
### Reference-style:
`! `
results in
!
## References for reference-style links
Even though only the formatted references are visible here in the output, this text is also followed
by the following references with links in the style
` : Referenced link`
```
: Here should be the link to the TradingView homepage "Trading view text-reference tooltip"
: Here should be the link to the TradingView homepage "Trading view number-reference tooltip"
: Here should be the link to the TradingView homepage "Trading view self-reference tooltip"
: Here should be the link to the favicon of the TradingView homepage "Trading View icon (reference)"
```
: Here should be the link to the TradingView homepage "Trading view text-reference tooltip"
: Here should be the link to the TradingView homepage "Trading view number-reference tooltip"
: Here should be the link to the TradingView homepage "Trading view self-reference tooltip"
: Here should be the link to the favicon of the TradingView homepage "Trading View icon (reference)"
Parameters:
pLog (bool)
taskLists(pLog)
Task lists.
Other Markdown implementations can also display task lists for list items like `- ` respective `- `.
This can only be simulated by inline code `` ´ ` ``.
Make sure to either add a line-break `\` at the end of the line or a new paragraph by a blank line.
### Task lists
` ` Finish library
` ` Finish library
Parameters:
pLog (bool)
escapeMd(pLog)
Escaping Markdown syntax
To write and display Markdown syntax in regular text, we have to escape it. This can be done
by adding `\` before the Markdown syntax. If the Markdown syntax consists of more than one character
in some cases also the character of function can be helpful if a command consists of
more than one character if it is placed between the separate characters of the command.
Parameters:
pLog (bool)
test()
Calls all functions of above script.
True stock performance based on Earnings YieldThe whole basis of the stock market is that you invest your money into a business that can use that money to increase it's earnings and pay you back for that investment with dividends and increased stock value. But because we are human the market often overbuy stocks that cant keep up their earnings with the current inflow of investments. We can also oversell a stock that is keeping up with earnings in regards to the stock price but we don't care because of the sentiment we have.
Earnings Yield is simply the percentage of Earnings Per Share in relation to the stock price. Alone, it's a great fundamental indicator to analyze a company. But I wanted to use it in another way and got tired of using the calculator all the time so that's why I made this indicator.
The goal is to see if the STOCK price is moving accordingly to the BUSINESS earnings. It works by calculating the difference of EY (TTM) previous close (1 bar) to the close thereafter. It then calculates the stock performance of the latest bar and divides that to get decimal form instead of percent. Then it divides the stock performance in decimal form with the difference of EY calculated before. The result shows how much the stock prices moves in relation to how much EY is moving. The theory is that if EY barely moves but the stock price moves heavily, you have a sentiment driven trend.
Example: Week 1 EY = 1.201. Week 2 EY = 1.105.
1.201 - 1.105 = 0.096
Week 2 performed a 11,2% increase in stock price. = 0.112 in decimal form.
0.112 / 0.096 = 1.67
1.67 is the multiple that plots this indicator.
Here is an good example of a stock that's currently in a highly sentiment driven trend, NVIDIA! (Posted 2024-03-30)
Here is an example of a Swedish stock that retail investors flocked to that have been blowned out completely.
When do I buy and sell?
This indicator is not meant to give exact entries or exits. The purpose is to scout the current and past sentiment, possible divergencies and see if a stock is over or under valued. I did add a 50 EMA to get some form of mean plotted. One could buy when true performance is low and sell when true performance drops below the 50 EMA. You could also just sell a part of your position and set a trailing exit with a ordinary 50 EMA or something like that. Often the sentiment will keep driving the price up. But if it last for 1 month or 1 year is impossible to tell.
Try it out and learn how it works and use it as you like. Cheers!
RSI Strategy with Manual TP and SL 19/03/2024This TradingView script implements a simple RSI (Relative Strength Index) strategy with manual take profit (TP) and stop-loss (SL) levels. Let's break down the script and analyze its components:
RSI Calculation: The script calculates the RSI using the specified length parameter. RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and typically values above 70 indicate overbought conditions while values below 30 indicate oversold conditions.
Strategy Parameters:
length: Length of the RSI period.
overSold: Threshold for oversold condition.
overBought: Threshold for overbought condition.
trail_profit_pct: Percentage for trailing profit.
Entry Conditions:
For a long position: RSI crosses above 30 and the daily close is above 70% of the highest close in the last 50 bars.
For a short position: RSI crosses below 70 and the daily close is below 130% of the lowest close in the last 50 bars.
Entry Signals:
Long entry is signaled when both conditions for a long position are met.
Short entry is signaled when both conditions for a short position are met.
Manual TP and SL:
Take profit and stop-loss levels are calculated based on the entry price and the specified percentage.
For long positions, the take profit level is set above the entry price and the stop-loss level is set below the entry price.
For short positions, the take profit level is set below the entry price and the stop-loss level is set above the entry price.
Strategy Exits:
Exit conditions are defined for both long and short positions using the calculated take profit and stop-loss levels.
Chart Analysis:
This strategy aims to capitalize on short-term momentum shifts indicated by RSI crossings combined with daily price movements.
It utilizes manual TP and SL levels, providing traders with flexibility in managing their positions.
The strategy may perform well in ranging or oscillating markets where RSI signals are more reliable.
However, it may encounter challenges in trending markets where RSI can remain overbought or oversold for extended periods.
Traders should backtest this strategy thoroughly on historical data and consider optimizing parameters to suit different market conditions.
Risk management is crucial, so traders should carefully adjust TP and SL percentages based on their risk tolerance and market volatility.
Overall, this strategy provides a structured approach to trading based on RSI signals while allowing traders to customize their risk management. However, like any trading strategy, it should be used judiciously and in conjunction with other forms of analysis and risk management techniques.
