E9 ASIA Session
*note: Upon updating the script the conversion from V4 to v5 has lost the weekend extended lines and now prints an asia session for each day. It is recommended (esp for crypto) to extend these lines across the weekend like in the chart example above.
The E9 Asia Session Indicator is a valuable tool for traders aiming to track and analyze the Asia trading session on financial charts. This indicator provides insights into price behavior during the Asia session, which is crucial for making informed trading decisions. Here's an overview of its key functionalities and uses:
1. Session Highs and Lows
Purpose:
The indicator calculates and plots the high and low of the Asia session.
It helps identify key levels of support and resistance established during this trading period.
Importance:
These levels can act as significant reference points for future price movements.
Price action that occurs near these levels often provides clues about potential breakouts or reversals.
2. Session Background Color
Purpose:
The indicator can shade the background of the chart during the Asia session.
Importance:
This visual cue helps quickly identify the session's timeframe, enhancing the trader’s ability to observe price behavior within this specific period.
It aids in distinguishing between different trading sessions and understanding their influence on price action.
3. Start of Session Marker
Purpose:
A visual marker (such as a circle) is plotted at the beginning of each Asia session.
Importance:
This marker helps traders visually pinpoint the start of the session, making it easier to analyze how the price reacts from the session's opening.
4. End of Session Marker
Purpose:
A marker is plotted at the end of the Asia session, indicating where the session closes.
Importance:
This marker is useful for tracking the end of the session and observing price behavior around this critical juncture.
It helps in analyzing whether the session's high or low gets revisited or broken in subsequent sessions.
Practical Uses:
Strategic Planning: Traders can use the plotted high and low levels to set their trading strategies, stop-loss orders, and profit targets.
Market Analysis: Understanding how price interacts with the Asia session’s high and low levels can provide insights into market sentiment and potential price movements.
By incorporating the E9 Asia Session Indicator into your trading toolkit, you can gain a deeper understanding of the Asia session's impact on price dynamics, enhancing your overall trading strategy and decision-making process.
Disclaimer: The information contained in this article does not constitute financial advice or a solicitation to buy or sell any securities. All investments involve risk, and past performance does not guarantee future results. Always evaluate your financial circumstances and investment objectives before making trading decisions.
Cerca negli script per "track"
AnyTimeAndPrice
This indicator allows users to input a specific start time and display the price of a lower timeframe on a higher timeframe chart. It offers customization options for:
- Display name
- Label color
- Line extension
By adding multiple instances of the AnyTimeframeTimeAndPrice indicator, each customized for different times and prices, you can create a powerful and flexible tool for analyzing market data. Here's a potential setup:
1. Instance 1:
- Time: 08:23
- Price: Open
- Display Name: "8:23 Open"
- Label Color: Green
2. Instance 2:
- Time: 12:47
- Price: High
- Display Name: "12:47 High"
- Label Color: Red
3. Instance 3:
- Time: 15:19
- Price: Low
- Display Name: "3:19 Low"
- Label Color: Blue
4. Instance 4:
- Time: 16:53
- Price: Close
- Display Name: "4:53 Close"
- Label Color: Yellow
By having multiple instances, you can:
- Track different times and prices on the same chart
- Customize the display names, label colors, and line extensions for each instance
- Easily compare and analyze the relationships between different times and prices
This setup can be particularly useful for:
- Identifying key levels and support/resistance areas
- Analyzing market trends and patterns
- Making more informed trading decisions
Inputs:
1. AnyStartHour: Integer input for the start hour (default: 09, range: 0-23)
2. AnyStartMinute: Integer input for the start minute (default: 30, range: 0-59)
3. Sourcename: String input for the display name (default: "Open", options: "Open", "Close", "High", "Low")
4. Src_col: Color input for the label color (default: aqua)
5. linetimeExtMulti: Integer input for the line time extension (default: 1, range: 1-5)
Calculations:
1. AnyinputStartTime: Timestamp for the input start time
2. inputhour and inputminute: Hour and minute components of the input start time
3. formattedAnyTime: Formatted string for the input start time (HH:mm)
4. currenttime: Current timestamp
5. currenthour and currentminute: Hour and minute components of the current time
6. formattedTime: Formatted string for the current time (HH:mm)
7. onTime and okTime: Boolean flags for checking if the current time matches the input start time or is within the session
8. firstbartime: Timestamp for the first bar of the session
9. dailyminutesfromSource: Calculation for the daily minutes from the source
10. anyminSrcArray: Request security lower timeframe array for the source
11. ltf (lower timeframe): Integer variable for tracking the lower timeframe
12. Sourcevalue: Float variable for storing the source value
13. linetimeExt: Integer variable for line extension (calculated from linetimeExtMulti)
Logic:
1. Check if the current time matches the input start time or is within the session
2. If true, plot a line and label with the source value and formatted time
3. If not, check if the current time is within the daily session and plot a line and label accordingly
Notes:
- The script uses request.security_lower_tf to request data from a lower timeframe
- The script uses line.new and label.new to plot lines and labels on the chart
- The script uses str.format_time to format timestamps as strings (HH:mm)
- The script uses xloc.bar_time to position lines and labels at the bar time
This script allows users to input a specific start time and display the price of a lower timeframe on a higher timeframe chart, with options for customizing the display name, label color, and line extension.
Median Supertrend | viResearchMedian Supertrend | viResearch
Conceptual Foundation and Innovation
The "Median Supertrend" indicator, developed by viResearch, offers a unique approach to identifying trends by combining a median-based smoothing mechanism with a modified Supertrend calculation. Unlike the traditional Supertrend, which relies solely on price data, this version calculates a median percentile of the closing price over a specified length, resulting in a more accurate representation of underlying trends.
Technical Composition and Calculation
The "Median Supertrend" enhances the conventional Supertrend formula by introducing improvements to minimize lag and improve responsiveness to market volatility.
Median Smoothing:
The script uses the 50th percentile of the closing price over a user-defined period to provide a smoother representation of price movements, reducing the influence of short-term price spikes or dips for more stable trend analysis.
Supertrend Calculation:
The indicator applies the Average True Range (ATR) to determine the upper and lower trend bands, which are then shifted above or below the smoothed price (median) by a multiple of the ATR, customizable by users to adjust sensitivity.
Trend Logic:
The script uses the upper and lower bands to detect whether the price is trending upwards or downwards and introduces persistence logic to prevent excessive shifting of the bands during consolidating market phases. This mechanism ensures that once the trend changes, the bands adjust smoothly rather than oscillating with each price movement.
Directional Analysis:
Based on price action relative to the trend bands, a directional variable (d) is computed to track whether the price crosses above or below these bands, signaling uptrends or downtrends. The script also includes events to detect transitions from bullish to bearish trends and vice versa, with the option to set alerts for timely decision-making.
Features and User Inputs
The "Median Supertrend" offers several customizable parameters to suit different trading styles:
Supertrend Length: Defines the period used to calculate the smoothing, allowing users to adjust the indicator's sensitivity based on market conditions.
Multiplier: Controls how far the trend bands are placed from the median price. Traders can increase the multiplier for less frequent trend changes or decrease it for more sensitive detection.
Median Length: Governs the length over which the median price is calculated, providing further customization to balance responsiveness and stability.
Practical Applications
The "Median Supertrend" is particularly useful in markets with rapid trend reversals and high volatility, offering an effective way to filter out noise and capture significant trend changes promptly.
Key Uses:
Trend Following: The indicator's primary function is to identify prevailing trends and guide traders in aligning with the market's direction, with its smoothing mechanism helping to ensure reliable trend signals.
Trend Reversal Detection: By tracking crossovers and crossunders relative to the Supertrend bands, the indicator helps traders detect potential reversals early, making it valuable in fast-moving markets.
Strategic Positioning: With adjustable sensitivity and real-time alerts, the "Median Supertrend" can adapt to a variety of trading strategies, from scalping to longer-term trend-following.
Advantages and Strategic Value
The "Median Supertrend" offers advantages over traditional trend indicators:
Reduced Noise: Median smoothing reduces noise from extreme price movements, ensuring more reliable trend signals.
Customizability: With adjustable length and multiplier settings, the indicator allows traders to fine-tune its sensitivity for different market conditions.
Responsiveness: Median-based smoothing, coupled with the ATR, provides a more responsive and adaptive measure of trend direction, particularly valuable in volatile markets.
Summary and Usage Tips
The "Median Supertrend" indicator is a potent tool for capturing market trends with increased precision and reduced lag. It combines the best features of traditional Supertrend indicators with the added stability of median-based smoothing, making it highly effective in volatile markets. Traders are encouraged to experiment with the length and multiplier settings to optimize the indicator for their specific trading strategies, while alerts and visual cues further enhance its utility.
Please keep in mind the following text: Backtests are based on past results and are not indicative of future performance.
Support ResistanceThis indicator was written in pine script code, inspired by the L3 Banker Fund Flow Trend Oscillator indicator whose link I gave below.
This indicator is designed to track the flow of banker funds in the market by analyzing price movements and generating entry signals based on specific criteria. It uses a combination of custom functions and moving averages to identify potential points where bankers might be entering the market.
Key Features:
Fund Flow Trend Calculation:
The indicator calculates the fund flow trend using a combination of weighted moving averages. This helps in identifying the overall trend and potential reversals.
Bull Bear Line:
A key component of the indicator is the Bull Bear Line, which is derived from the typical price, lowest low, and highest high over a specified period. This line helps in determining the strength and direction of the market trend.
Banker Entry Signal:
The indicator generates a banker entry signal when the fund flow trend crosses above the Bull Bear Line, and the Bull Bear Line is below 25. This condition is indicative of a potential entry point for bankers.
Visual Representation:
Entry prices and indices for the last five banker entry signals are stored and used to draw dashed lines on the chart, representing these significant levels.
A dynamic rectangle is drawn between the last two entry prices, which extends to the right until the specified conditions are met. The rectangle's color changes from red to green if the price crosses above it by at least one bar, indicating a potential support zone.
Usage:
Trend Identification:
Use the fund flow trend and Bull Bear Line to identify the prevailing market trend and potential reversal points.
Entry Signals:
Pay attention to the banker entry signals as potential points of entry based on institutional fund flow.
Support and Resistance:
The dynamic rectangle can act as a support zone. Monitor price action relative to this rectangle for potential trading opportunities.
This indicator is a powerful tool for traders looking to align their trades with the movements of large institutional players. By understanding and tracking the flow of banker funds, traders can gain valuable insights into market dynamics and make more informed trading decisions.
Alpha-Sutte Multi-Price Indicator [CHE] Overview
The AlphaSutte MultiPrice Indicator is a powerful tool for forecasting market movements and generating trading signals. At its core is the AlphaSutte Model, which stands out for its innovative approach to predicting future price movements.
Inspired by the () on TradingView, this indicator enhances the original concept by integrating it with the T3 smoothing technique to improve trend identification and signal reliability.
The AlphaSutte Model
The AlphaSutte Model is a mathematical method for forecasting prices based on the analysis of historical price data. It is applied to various price components such as High, Low, Open, and Close. The model predicts future values using differences and weighted averages of previous periods. Here are the key steps and components of the AlphaSutte Model:
1. Data Extraction:
The model extracts historical values at specified intervals. For example, it uses the values from the last four periods for calculations.
2. Difference Calculations:
Differences between successive historical values are calculated:
Delta_x: Difference between the first and fourth values.
Delta_y: Difference between the second and first values.
Delta_z: Difference between the third and second values.
3. Weighted Average Calculation:
These differences are then integrated into a weighted average to forecast the future value:
The weighted average combines the historical values and their differences to calculate the forecasted value, referred to as a_t.
4. Application to Price Components:
The AlphaSutte Model can be applied to various price components:
High: Forecasting the future high price.
Low: Forecasting the future low price.
Open: Forecasting the future opening price.
Close: Forecasting the future closing price.
5. Averaging AlphaSutte Values:
If multiple price components are used for calculation, an average of the AlphaSutte values is computed. This average serves as the basis for generating trading signals.
Trading Signals and Directional Change
The AlphaSutte Model is used to generate long and short trading signals. These signals are confirmed by the directional change of the T3 Indicator to enhance reliability:
Long Signals:
A long signal is generated when the average value of the AlphaSutte Model is positive, and the T3 indicator previously showed a downtrend.
These signals are displayed with green labels and lines on the chart.
Short Signals:
A short signal is generated when the average value of the AlphaSutte Model is negative, and the T3 indicator previously showed an uptrend.
These signals are displayed with red labels and lines on the chart.
StepbyStep Explanation of the Script
The AlphaSutte MultiPrice Indicator script in TradingView is designed to provide comprehensive market trend analysis and trading signal generation. Here is a stepbystep explanation of how the script operates:
1. Input Parameters:
The script begins by defining several input parameters for the T3 indicator and AlphaSutte Model, including:
`t3Length`: The length of the T3 moving average.
`t3VolumeFactor`: The volume factor used in T3 smoothing.
Boolean inputs to determine which price components (High, Low, Open, Close) should use the AlphaSutte Model.
`numLastLabels`: The number of last labels to display for recent signals.
2. T3 Smoothing Function:
The `t3Smoothing` function calculates the T3 smoothed value for the specified source price using a series of exponential moving averages (EMAs):
It calculates six sequential EMAs of the source price.
It then combines these EMAs using specific coefficients to obtain the T3 value.
3. AlphaSutte Calculation Function:
The `get_alpha_sutte` function forecasts future values based on historical price data:
It extracts historical price values at specific intervals.
It calculates the differences (deltas) between these values.
It computes a weighted average of these deltas to obtain the AlphaSutte value.
4. Calculating AlphaSutte Components:
The script calculates the AlphaSutte values for the selected price components (High, Low, Open, Close) based on user input.
It then averages these values if multiple components are selected.
5. Generating Long and Short Conditions:
The script defines conditions for generating long and short signals based on the AlphaSutte average:
`long_condition`: True if the AlphaSutte average is positive.
`short_condition`: True if the AlphaSutte average is negative.
6. Tracking T3 Trend Direction:
The script updates state variables to track whether the T3 line is in an uptrend or downtrend:
`t3_uptrend`: True if the T3 value is higher than the previous T3 value.
`t3_downtrend`: True if the T3 value is lower than the previous T3 value.
7. Generating and Managing Labels and Lines:
The script generates labels and lines on the chart to visualize long and short signals:
For long signals, green labels and lines are created when the long condition is met, and the T3 was previously in a downtrend.
For short signals, red labels and lines are created when the short condition is met, and the T3 was previously in an uptrend.
Old labels and lines are deleted to keep the chart clean and relevant.
8. Updating Lines to Current Candle:
The script dynamically updates the end points of the lines to the current candle to reflect the latest market data.
9. Highlighting Movements:
The script optionally highlights the T3 line based on its direction to visually emphasize the trend:
Green for an uptrend and red for a downtrend.
10. Plotting the T3 Line:
Finally, the T3 line is plotted on the chart with the specified color and line width to provide a clear visualization of the trend.
Conclusion
The primary focus of the AlphaSutte MultiPrice Indicator is on the forecasting capabilities of the AlphaSutte Model. This model's forecasts are the most critical part of the indicator, providing the essential signals for potential market movements. The T3 indicator serves as a confirmation tool, validating these forecasts by indicating the direction of the trend. This combination enhances the reliability of the trading signals, making the AlphaSutte MultiPrice Indicator a valuable asset for traders looking to make informed decisions based on robust market analysis.
Best regards Chervolino
Candlestick Structure [LuxAlgo]The Candlestick Structure indicator detects major market trends and displays various candlestick patterns aligning with the detected trend, filtering out potentially unwanted patterns as a result. Multiple trend detection methods are included and can be selected by the users.
A dashboard showing the alignment percentage of each individual pattern is also provided.
🔶 USAGE
By distinguishing major and minor trend detection, we can still detect patterns based on minor trends, yet filter out the patterns that do not align with the major trend.
By detecting candlestick patterns that align with a major trend, we can effectively detect the ending points of retracements, potentially providing various entry points of interest within a trend.
Users are able to track the alignment of each candlestick pattern in the dashboard to reveal which patterns typically align with the trend and which may not.
Note: Alignment % only checks if the pattern's direction is the same as the current trend direction. These are only raw readings and not any type of confidence score.
🔶 DETAILS
In this indicator, we are identifying and tracking 16 different Candlestick Patterns.
🔹 Bullish Patterns
Hammer: Identified by a small upper wick (or no upper wick) with a small body, and an elongated lower wick whose length is 2X greater than the candle body’s width.
Inverted Hammer: Identified by a small lower wick (or no lower wick) with a small body, and an elongated upper wick whose length is 2X greater than the candle body’s width.
Bullish Engulfing: A 2 bar pattern identified by a large bullish candle body fully encapsulating (opening lower and closing higher) the previous small (bearish) candle body.
Rising 3: A 5 bar pattern identified by an initial full-bodied bullish candle, followed by 3 bearish candles that trade within the high and low of the initial candle, followed by another full-bodied bullish candle closing above the high of the initial candle.
3 White Soldiers: Identified by 3 full-bodied bullish candles, each opening within the body and closing below the high, of the previous candle.
Morning Star: A 3 bar pattern identified by a full-bodied bearish candle, followed by a small-bodied bearish candle, followed by a full-bodied bullish candle that closes above the halfway point of the first candle.
Bullish Harami: A 2 bar pattern, identified by an initial bearish candle, followed by a small bullish candle whose range is entirely contained within the body of the initial candle.
Tweezer Bottom: A 2 bar pattern identified by an initial bearish candle, followed by a bullish candle, both having equal lows.
🔹 Bearish Patterns
Hanging Man: Identified by a small upper wick (or no upper wick) with a small body, and an elongated lower wick whose length is 2X greater than the candle body’s width.
Shooting Star: Identified by a small lower wick (or no lower wick) with a small body, and an elongated upper wick whose length is 2X greater than the candle body’s width.
Bearish Engulfing: A 2 bar pattern identified by a large bearish candle body fully encapsulating (opening higher and closing lower) the previous small (bullish) candle body.
Falling 3: A 5 bar pattern identified by an initial full-bodied bearish candle, followed by 3 bullish candles that trade within the high and low of the initial candle, followed by another full-bodied bearish candle closing below the low of the initial candle.
3 Black Crows: Identified by 3 full-bodied bearish candles, each open within the body and closing below the low, of the previous candle.
Evening Star: A 3 bar pattern identified by a full-bodied bullish candle, followed by a small-bodied bullish candle, followed by a full-bodied bearish candle that closes below the halfway point of the first candle.
Bearish Harami: A 2 bar pattern, identified by an initial bullish candle, followed by a small bearish candle whose range is entirely contained within the body of the initial candle.
Tweezer Top: A 2 bar pattern identified by an initial bullish candle, followed by a bearish candle, both having equal highs.
🔹 Trend Types
Major trend is displayed at all times, the display will change depending on the trend method selected.
The minor trend can also be visualized; to avoid confusion, the minor trend can optionally be displayed through the candle colors.
Supertrend: Displays Upper and Lower SuperTrend, When we break above the upper, it is considered an Uptrend. When we break below the lower, it is considered a Downtrend.
EMAs: Displays Fast and Slow EMAs, When Fast>Slow, it is considered an Uptrend. When Fast
RiskMetrics█ OVERVIEW
This library is a tool for Pine programmers that provides functions for calculating risk-adjusted performance metrics on periodic price returns. The calculations used by this library's functions closely mirror those the Broker Emulator uses to calculate strategy performance metrics (e.g., Sharpe and Sortino ratios) without depending on strategy-specific functionality.
█ 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.
One way investors and analysts assess the risk of an investment is by analyzing its volatility , i.e., the statistical dispersion of historical returns. Investors often use volatility in risk estimation because it provides a quantifiable way to gauge the expected extent of fluctuation in returns. Elevated volatility implies heightened uncertainty in the market, which suggests higher expected risk. Conversely, low volatility implies relatively stable returns with relatively minimal fluctuations, thus suggesting lower expected risk. Several risk-adjusted performance metrics utilize volatility in their calculations for this reason.
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.
The built-in Sharpe and Sortino ratios that strategies calculate and display in the Performance Summary tab use a default risk-free rate of 2%, and the metrics in this library's example code use the same default rate. Users can adjust this value to fit their analysis needs.
Risk-adjusted performance
Risk-adjusted performance metrics gauge the effectiveness of an investment by considering its returns relative to the perceived risk. They aim to provide a more well-rounded picture of performance by factoring in the level of risk taken to achieve returns. Investors can utilize such metrics to help determine whether the returns from an investment justify the risks and make informed decisions.
The two most commonly used risk-adjusted performance metrics are the Sharpe ratio and the Sortino ratio.
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.
█ CALCULATIONS
Return period detection
Calculating risk-adjusted performance metrics requires collecting returns across several periods of a given size. Analysts may use different period sizes based on the context and their preferences. However, two widely used standards are monthly or daily periods, depending on the available data and the investment's duration. The built-in ratios displayed in the Strategy Tester utilize returns from either monthly or daily periods in their calculations based on the following logic:
• Use monthly returns if the history of closed trades spans at least two months.
• Use daily returns if the trades span at least two days but less than two months.
• Do not calculate the ratios if the trade data spans fewer than two days.
This library's `detectPeriod()` function applies related logic to available chart data rather than trade data to determine which period is appropriate:
• It returns true if the chart's data spans at least two months, indicating that it's sufficient to use monthly periods.
• It returns false if the chart's data spans at least two days but not two months, suggesting the use of daily periods.
• It returns na if the length of the chart's data covers less than two days, signifying that the data is insufficient for meaningful ratio calculations.
It's important to note that programmers should only call `detectPeriod()` from a script's global scope or within the outermost scope of a function called from the global scope, as it requires the time value from the first bar to accurately measure the amount of time covered by the chart's data.
Collecting periodic returns
This library's `getPeriodicReturns()` function tracks price return data within monthly or daily periods and stores the periodic values in an array . It uses a `detectPeriod()` call as the condition to determine whether each element in the array represents the return over a monthly or daily period.
The `getPeriodicReturns()` function has two overloads. The first overload requires two arguments and outputs an array of monthly or daily returns for use in the `sharpe()` and `sortino()` methods. To calculate these returns:
1. The `percentChange` argument should be a series that represents percentage gains or losses. The values can be bar-to-bar return percentages on the chart timeframe or percentages requested from a higher timeframe.
2. The function compounds all non-na `percentChange` values within each monthly or daily period to calculate the period's total return percentage. When the `percentChange` represents returns from a higher timeframe, ensure the requested data includes gaps to avoid compounding redundant values.
3. After a period ends, the function queues the compounded return into the array , removing the oldest element from the array when its size exceeds the `maxPeriods` argument.
The resulting array represents the sequence of closed returns over up to `maxPeriods` months or days, depending on the available data.
The second overload of the function includes an additional `benchmark` parameter. Unlike the first overload, this version tracks and collects differences between the `percentChange` and the specified `benchmark` values. The resulting array represents the sequence of excess returns over up to `maxPeriods` months or days. Passing this array to the `sharpe()` and `sortino()` methods calculates generalized Information ratios , which represent the risk-adjustment performance of a sequence of returns compared to a risky benchmark instead of a risk-free rate. For consistency, ensure the non-na times of the `benchmark` values align with the times of the `percentChange` values.
Ratio methods
This library's `sharpe()` and `sortino()` methods respectively calculate the Sharpe and Sortino ratios based on an array of returns compared to a specified annual benchmark. Both methods adjust the annual benchmark based on the number of periods per year to suit the frequency of the returns:
• If the method call does not include a `periodsPerYear` argument, it uses `detectPeriod()` to determine whether the returns represent monthly or daily values based on the chart's history. If monthly, the method divides the `annualBenchmark` value by 12. If daily, it divides the value by 365.
• If the method call does specify a `periodsPerYear` argument, the argument's value supersedes the automatic calculation, facilitating custom benchmark adjustments, such as dividing by 252 when analyzing collected daily stock returns.
When the array passed to these methods represents a sequence of excess returns , such as the result from the second overload of `getPeriodicReturns()`, use an `annualBenchmark` value of 0 to avoid comparing those excess returns to a separate rate.
By default, these methods only calculate the ratios on the last available bar to minimize their resource usage. Users can override this behavior with the `forceCalc` parameter. When the value is true , the method calculates the ratio on each call if sufficient data is available, regardless of the bar index.
Look first. Then leap.
█ FUNCTIONS & METHODS
This library contains the following functions:
detectPeriod()
Determines whether the chart data has sufficient coverage to use monthly or daily returns
for risk metric calculations.
Returns: (bool) `true` if the period spans more than two months, `false` if it otherwise spans more
than two days, and `na` if the data is insufficient.
getPeriodicReturns(percentChange, maxPeriods)
(Overload 1 of 2) Tracks periodic return percentages and queues them into an array for ratio
calculations. The span of the chart's historical data determines whether the function uses
daily or monthly periods in its calculations. If the chart spans more than two months,
it uses "1M" periods. Otherwise, if the chart spans more than two days, it uses "1D"
periods. If the chart covers less than two days, it does not store changes.
Parameters:
percentChange (float) : (series float) The change percentage. The function compounds non-na values from each
chart bar within monthly or daily periods to calculate the periodic changes.
maxPeriods (simple int) : (simple int) The maximum number of periodic returns to store in the returned array.
Returns: (array) An array containing the overall percentage changes for each period, limited
to the maximum specified by `maxPeriods`.
getPeriodicReturns(percentChange, benchmark, maxPeriods)
(Overload 2 of 2) Tracks periodic excess return percentages and queues the values into an
array. The span of the chart's historical data determines whether the function uses
daily or monthly periods in its calculations. If the chart spans more than two months,
it uses "1M" periods. Otherwise, if the chart spans more than two days, it uses "1D"
periods. If the chart covers less than two days, it does not store changes.
Parameters:
percentChange (float) : (series float) The change percentage. The function compounds non-na values from each
chart bar within monthly or daily periods to calculate the periodic changes.
benchmark (float) : (series float) The benchmark percentage to compare against `percentChange` values.
The function compounds non-na values from each bar within monthly or
daily periods and subtracts the results from the compounded `percentChange` values to
calculate the excess returns. For consistency, ensure this series has a similar history
length to the `percentChange` with aligned non-na value times.
maxPeriods (simple int) : (simple int) The maximum number of periodic excess returns to store in the returned array.
Returns: (array) An array containing monthly or daily excess returns, limited
to the maximum specified by `maxPeriods`.
method sharpeRatio(returnsArray, annualBenchmark, forceCalc, periodsPerYear)
Calculates the Sharpe ratio for an array of periodic returns.
Callable as a method or a function.
Namespace types: array
Parameters:
returnsArray (array) : (array) An array of periodic return percentages, e.g., returns over monthly or
daily periods.
annualBenchmark (float) : (series float) The annual rate of return to compare against `returnsArray` values. When
`periodsPerYear` is `na`, the function divides this value by 12 to calculate a
monthly benchmark if the chart's data spans at least two months or 365 for a daily
benchmark if the data otherwise spans at least two days. If `periodsPerYear`
has a specified value, the function divides the rate by that value instead.
forceCalc (bool) : (series bool) If `true`, calculates the ratio on every call. Otherwise, ratio calculation
only occurs on the last available bar. Optional. The default is `false`.
periodsPerYear (simple int) : (simple int) If specified, divides the annual rate by this value instead of the value
determined by the time span of the chart's data.
Returns: (float) The Sharpe ratio, which estimates the excess return per unit of total volatility.
method sortinoRatio(returnsArray, annualBenchmark, forceCalc, periodsPerYear)
Calculates the Sortino ratio for an array of periodic returns.
Callable as a method or a function.
Namespace types: array
Parameters:
returnsArray (array) : (array) An array of periodic return percentages, e.g., returns over monthly or
daily periods.
annualBenchmark (float) : (series float) The annual rate of return to compare against `returnsArray` values. When
`periodsPerYear` is `na`, the function divides this value by 12 to calculate a
monthly benchmark if the chart's data spans at least two months or 365 for a daily
benchmark if the data otherwise spans at least two days. If `periodsPerYear`
has a specified value, the function divides the rate by that value instead.
forceCalc (bool) : (series bool) If `true`, calculates the ratio on every call. Otherwise, ratio calculation
only occurs on the last available bar. Optional. The default is `false`.
periodsPerYear (simple int) : (simple int) If specified, divides the annual rate by this value instead of the value
determined by the time span of the chart's data.
Returns: (float) The Sortino ratio, which estimates the excess return per unit of downside
volatility.
Pre-COVID High and COVID LowOverview
The "Pre-COVID High and COVID Low" indicator is designed to identify and mark significant price levels on your chart, specifically targeting the pre-COVID-19 high and the low during the initial COVID-19 market impact. This script is particularly useful for traders who are interested in analyzing how stocks or other financial instruments reacted during the onset of the COVID-19 pandemic, providing a historical perspective that may help in making informed trading decisions.
How It Works
Date Ranges : The script uses predefined date ranges to calculate the highest and lowest price levels before and during the early stages of the COVID-19 pandemic. These ranges are:
Pre-COVID High: Between January 1, 2020, and March 31, 2020.
COVID Low: Between March 1, 2020, and March 31, 2020.
Calculation Method :
The highest price during the pre-COVID period is tracked and recorded as the "Pre-COVID High".
The lowest price during the specified COVID period is tracked and recorded as the "COVID Low".
Visibility Conditions : The script includes logic to ensure that these historical levels are only displayed if they fall within a range close to the current visible price range on the chart. This prevents the indicator from compressing the price scale unduly.
How to Use It
Adding to Your Char t: To use this indicator, add it to any chart on TradingView. It works best with daily time frames to clearly visualize the impact over these specific months.
Interpretation :
The "Pre-COVID High" is marked with a red line and is labeled the first day it becomes applicable.
The "COVID Low" is marked with a green line and is similarly labeled on its applicable day.
Trading Strategy Consideration : Traders can use these historical levels as potential support or resistance zones for their trading strategies. These levels can indicate significant price points where the market previously showed strong reactions.
Venit A.I Trading V1RSI indicatorThis indicator is designed to provide buy and sell signals based on the Relative Strength Index (RSI). Here's a breakdown of its components and functionality:
1. **Input Parameters**:
- `Period`: This parameter allows the user to adjust the period used in calculating the RSI.
- `Upper Threshold` and `Lower Threshold`: These parameters define the overbought and oversold levels for the RSI.
- `Imverse Algorithm`: This parameter allows the user to toggle between different algorithms for generating buy and sell signals.
- `Show Lines`: This parameter toggles the visibility of lines on the chart indicating buy and sell signals.
- `Show Labels`: This parameter toggles the visibility of labels on the chart indicating buy and sell signals.
2. **RSI Calculation**:
- The RSI is calculated using the specified period (`myPeriod`), typically representing the closing prices of the asset.
3. **Buy and Sell Conditions**:
- Buy conditions are determined based on whether the RSI crosses below the lower threshold (`myThresholdDn`), indicating potential oversold conditions.
- Sell conditions are determined based on whether the RSI crosses above the upper threshold (`myThresholdUp`), indicating potential overbought conditions.
- The choice of buy and sell conditions can be toggled using the `Imverse Algorithm` parameter.
4. **Position Tracking**:
- The indicator maintains a variable `myPosition` to track the current position (buy or sell) based on the generated signals.
- If a buy signal occurs (`buy` condition is true), `myPosition` is set to 0. If a sell signal occurs (`sell` condition is true) or the previous position was a buy, `myPosition` is set to 1. Otherwise, `myPosition` remains unchanged.
5. **Visualization**:
- Buy and sell signals are plotted on the chart using shapes (`plotshape`) based on the `myLineToggle` and `myLabelToggle` parameters.
- Lines are drawn on the chart to visually represent buy and sell signals.
- Labels are placed on the chart indicating buy and sell signals.
6. **Alerts**:
- The indicator provides alerts for buy and sell signals using the `alertcondition` function.
Overall, this indicator aims to provide traders with signals based on RSI movements, helping them identify potential buying and selling opportunities in the market. The flexibility in parameters allows users to customize the indicator based on their trading preferences and strategies.
MultiWAPThe VWAP tracks the average price, giving weight to each candle based upon its' relative volume.
In other words, high-volume candles move the VWAP faster than low-volume candles.
On a good day, market maker:
-Buys the dip
-Pumps past resistance, causing bullish FOMO
-Sells into the bullish FOMO, causing bearish FOMO
-Buys the dip (rinse and repeat)
By default, MultiWAP begins at the first visible bar.
Range low/high - tracks the most recent high/low
Upper VWAP - tracks retail's average buy price (MM is selling)
Lower VWAP - tracks MM's average buy price (MM is buying)
If price closes below the lower VWAP or the range low, the lower VWAP and range low are reset.
If price closes above the upper VWAP or the range high, the upper VWAP and range high are reset.
Resets are indicated by the dots. Resetting either VWAP moves it close to last price, making it easy to breach again.
A down-trend that lasts many bars will produce a string of green dots. When the accumulation phase ends, price pulls away from the lower VWAP, so it stops resetting. The ABSENCE of green dots tells you that we're in the markup phase/up-trend.
An up-trend that lasts many bars will produce a string of red dots. When the distribution phase ends, price pulls away from the upper VWAP, so it stops resetting. The ABSENCE of red dots tells you that we're in the markdown phase/down-trend.
By default, the net result is two VWAP's that automatically anchor themselves to the most recent, significant, and visible, high and low.
Usage:
For any timeframe, I recommend starting zoomed way out. Find the last green dot and drop an "Anchored VWAP" there. Now, zoom in until that candle is no longer visible. Find the last green dot and drop an anchored VWAP there. Continue doing so until you notice the lower VWAP getting reset to basically the same place.
This works the same, in reverse, during down-trends.
Multi Time Frame Exponential Moving Average and dasboardThis Pine script, titled "Multi Time Frame Exponential Moving Average (MTF EMA)," provides an innovative approach for traders who wish to track trends across multiple timeframes without having to switch between different charts. It combines two main features: an indicator displaying exponential moving averages (EMA) on five different time periods, as well as a compact dashboard that synthesizes this information on a single chart window.
The originality of this script lies in its ability to provide a comprehensive analysis of EMA trends across different time intervals, allowing traders to quickly and clearly understand the market dynamics without having to navigate between multiple charts. Rather than switching from one chart to another to observe trends on different time scales, traders can now consult a single dashboard to obtain all the necessary information.
The script uses exponential moving averages (EMA) to identify trends over five time periods: 5 minutes, 15 minutes, 1 hour, 4 hours, and 1 day. The values of the EMAs are calculated based on the closing prices of candles. Bullish or bearish trends are indicated by upward or downward arrows respectively, making it easy to interpret the information on the dashboard.
To use this script, traders can simply add it to their chart on the TradingView platform. They can customize the parameters of the exponential moving averages according to their preferences and choose between a dark or light theme for the dashboard. Then, they can observe trends on different time scales directly on the dashboard, enabling them to make informed trading decisions.
In summary, this script offers a practical and innovative solution for tracking trends across multiple timeframes, combining the efficiency of exponential moving averages with the convenience of a dashboard centralized on a single chart. This allows traders to save time and stay informed about market movements effectively and efficiently.
MUJBOT - ADVANCED DAILY OPENTitle: MUJBOT - ADVANCED DAILY OPEN
Description:
The "MUJBOT - ADVANCED DAILY OPEN" is a versatile and user-friendly TradingView indicator designed to enhance daily trading strategies by highlighting the daily open price on the chart. This indicator is particularly useful for traders who focus on intraday price movements around the opening price of the trading day.
Key Features:
Daily Open Line: Visually represents the opening price of each trading day on the chart, providing a clear reference point for the day's initial market sentiment.
Dynamic Testing Counter: Keeps track of how many times the price tests or crosses the daily open level within the day. This feature offers insight into the significance and market reaction to the daily open price.
Customizable Display: Includes an option to show or hide the daily open line and the testing counter label. Traders can easily toggle the display according to their preference, keeping their charts uncluttered.
Real-Time Updates: The label and line are dynamically updated in real-time with each new price bar, ensuring traders have the most current information at their fingertips.
Simplicity and Efficiency: With a straightforward design, the indicator adds minimal complexity to the chart while providing valuable trading information.
Usage:
Intraday Trading: Ideal for intraday traders, the indicator helps in identifying how the current price is behaving relative to the opening price, which can be a crucial factor in decision-making.
Support and Resistance: The daily open can act as a natural support or resistance level. Monitoring how the price interacts with this level can provide insights into potential breakout or reversal opportunities.
Trend Analysis: Observing the frequency of the daily open price being tested can give clues about the day's trend strength and potential continuation or reversal.
Customization Options:
Toggle the visibility of the daily open line and label.
The line extends six bars ahead from the daily open for clear visibility.
The label displays the daily open price and the count of how many times it has been tested.
Conclusion:
The "MUJBOT - ADVANCED DAILY OPEN" indicator is a valuable tool for traders who emphasize the importance of the daily open in their trading strategy. Its simplicity, combined with real-time tracking features, makes it an essential addition to the trader's toolkit on TradingView.
Feel free to modify or add any additional details specific to your trading strategy or indicator functionality.
Market Average TrendThis indicator aims to be complimentary to SPDR Tracker , but I've adjusted the name as I've been able to utilize the "INDEX" data provider to support essentially every US market.
This is a breadth market internal indicator that allows quick review of strength given the 5, 20, 50, 100, 150 and 200 simple moving averages. Each can be toggled to build whatever combinations are desired, I recommend reviewing classic combinations such as 5 & 20 as well as 50 & 200.
It's entirely possible that I've missed some markets that "INDEX" provides data for, if you find any feel free to drop a comment and I'll add support for them in an update.
Markets currently supported:
S&P 100
S&P 500
S&P ENERGIES
S&P INFO TECH
S&P MATERIALS
S&P UTILITIES
S&P FINANCIALS
S&P REAL ESTATE
S&P CON STAPLES
S&P HEALTH CARE
S&P INDUSTRIALS
S&P TELECOM SRVS
S&P CONSUMER DISC
S&P GROWTH
NAS 100
NAS COMP
DOW INDUSTRIAL
DOW COMP
DOW UTILITIES
DOW TRANSPORTATION
RUSSELL 1000
RUSSELL 2000
RUSSELL 3000
You can utilize this to watch stocks for dip buys or potential trend continuation entries, short entries, swing exits or numerous other portfolio management strategies.
If using it with stocks, it's advisable to ensure the stock often follows the index, otherwise obviously it's great to use with major indexes and determine holdings sentiment.
Important!
The "INDEX" data provider only supplies updates to all of the various data feeds at the end of day, I've noticed quite some delays even after market close and not taken time to review their actual update schedule (if even published). Therefore, it's strongly recommended to mostly ignore the last value in the series until it's the day after.
Only works on daily timeframes and above, please don't comment that it's not working if on other timeframes lower than daily :)
Feedback and suggestions are always welcome, enjoy!
OTT CollectionIf you are not yet familiar with OTT, this script could provide an introduction to help you get started.
"Optimized Trend Tracker" (OTT) is an effective trend-following indicator created by Anıl Özekşi . It aims to detect the current trend direction based on an elegant mathematical construct. The key defining characteristic of OTT is its reliance on a trailing-stop mechanism. This enables OTT to identify price movements and follow the price until a reversal occurs. The widespread adoption of OTT in various algo-trading platforms has fostered the development of diverse applications of the indicator over time. Examining its history, eight distinct applications emerge.
1) OTT - Optimized Trend Tracker
2) TOTT - Twin Ott
3) OTT Channel - Half Channel & Fibonacci Channel
4) RISOTTO - Rsi Ott
5) SOTT - Stochastic Ott
6) HOTT & LOTT - Highest-Lowest Ott + Sum Option
7) ROTT - Relative Ott
8) FT - "Fırsatçı" Trend
BONUS: RTR - Relative True Range
Each system functions as an independent indicator and the "OTT Collection" is intended to present all of them in a single script.
ORIGINALITY
Primarily, this script introduces previously unreleased OTT applications on Tradingview (RISOTTO, ROTT, FT). In contrast to previously published examples that treat OTT as a variable, this script portrays OTT as a function, rendering it adaptable for more intricate computations. Consequently, OTT has evolved into a versatile tool capable of facilitating complex analyses. Furthermore, this script offers an innovative feature that permits the blocking of consecutive signals in the same direction, catering to user preferences. (This feature is crucial for all indicators utilizing band structures such as TOTT and HOTT-LOTT).
USAGE
It is simple to use. The settings section of the indicator groups the parameters. In first group, the System parameter allows you to select the OTT system you want to display on the chart. Activating the Pyramiding parameter enables the display of consecutive signals in the same direction (for TOTT and HOTT-LOTT). In the second group you can change the display options with the Barcolor, Signal and Bars parameters. The OTT system you select is configured with the parameters in the group with the corresponding system heading. (For example, suppose you select OTT CHANNEL in the system parameter. The parameters defining the channels are grouped under the heading "OTT CHANNELS" in the settings section.) Also the parameters you chose are displayed in table form on the chart screen. The table also presents the total number of bars on the chart and the number of signals generated by the selected system.
MECHANICS
Let's take a look at how the indicator works. This indicator incorporates eight distinct OTT systems, each characterized by unique parameters, lines, and signals. (Exception: OTT Channel does not include any referenced signals.)
1) WHAT IS "OTT"?
OTT comprises two lines: Support and Target. There's an up-trending market when the Support is superior to the Target, and a down-trending market when the Support is inferior to the Target. It is governed by two parameters. The Support (moving average) is determined by the Length parameter, while the Multiplier parameter is employed for percentage calculations. Lower values are adept at capturing short-term fluctuations, whereas higher values are more adept at identifying long-term trends. These principles apply to all parameters within the indicator.
DETAILED INFO : The OTT function in the script automatically performs the calculation process described in this section. So, if you know how OTT works you can skip the details. To comprehend its functioning, it's essential to grasp the "MOST" indicator, also devised by Anıl Özekşi. The fundamental principle of MOST involves creating bands that function akin to a trailing stop-loss. Initially, a moving average, referred to as the 'Support,' is established. (Anıl Özekşi employs VAR/VIDYA as the moving average type in all his systems.) Subsequently, the Support line is adjusted both upward and downward by a percentage multiplier to establish a band system. In the context of the trailing stop-loss concept, when the Support line approaches either the lower or upper band, the respective band ceases to move in parallel with the Support line and becomes horizontal. Consequently, the Support always intersects the band at some point. The values of the upper or lower bands, determined by this intersection, are referred to as the MOST line. OTT is generated by consolidating the values of MOST shifted upwards and downwards by half the coefficient percentage into a single line using the same method as above, and calculating the value of this line from two bars ago. Support is the data series of OTT and it serves as a source in OTT function. The OTT line is named as "Target" in this scipt. Support and Target will automatically vary according to the OTT application selected in the "System" parameter.
2) WHAT IS "TOTT"?
Twin OTT , also known as the "OTT Band," involves three parameters: Length, Multiplier, and Band Multiplier. It consists of three lines: Support, Upper Line, and Lower Line. OTT is determined by the Length and Multiplier parameters, while TOTT is calculated by adjusting OTT upwards and downwards as per the Band Multiplier parameter. The indicator generates signals based on the intersections of the Support and these two new OTT levels.
3) WHAT IS "OTT CHANNEL"?
Similar to TOTT, the OTT CHANNEL is also based on shifted OTT levels, employing a similar calculation method. The primary distinction lies in the fact that TOTT has a single Band Multiplier, whereas OTT CHANNEL incorporates two line multipliers for the band. It encompasses four parameters: Length, Multiplier, Upper Line Multiplier, and Lower Line Multiplier. OTT is defined by the Length and Multiplier parameters. The Upper Line Multiplier and Lower Line Multiplier parameters establish the channel boundaries by shifting the OTT line. Subsequently, levels are drawn between the upper and lower lines. The additional Channel Type parameter determines which levels are displayed on the chart. The "Half Channel" option draws channels shifted by half the coefficient. The "Fibonacci Channel" option draws channels shifted by 0.382 and 0.618 coefficients. The "Both" option plots all levels.
4) WHAT IS "RISOTTO"?
OTT also has application examples in momentum oscillators. RISOTTO utilizes the RSI indicator and operates with three parameters. The RSI is defined by the Length 1 parameter, while the Support is determined by the Length 2 parameter. The Multiplier parameter is utilized for percentage calculations. RISOTTO comprises two lines: Support and Target. To ensure more stable calculations, a constant (+1000) is added to the oscillator average when applying OTT to momentum oscillators. This approach eradicates nonsensical results stemming from percentage calculations when the oscillator reaches a value of 0. The indicator generates signals based on the intersection of these two lines.
5) WHAT IS "SOTT"?
Stochastic OTT is an another example of application on oscillator. Its working principle is akin to that of RISOTTO. It operates with three parameters. The Stochastic %k is defined by the Length 1 parameter, while the Stochastic %d is determined by the Length 2 parameter. The Multiplier parameter is utilized for percentage calculations. SOTT comprises two lines: Support and Target. The indicator generates signals based on the intersection of these two lines.
6) WHAT IS "HOTT-LOTT"?
OTT can be applied to the highest and lowest series as well. HOTT-LOTT operates with three parameters: Length, Multiplier, and Sum N Bars. The highest and lowest series are defined by the Length parameter. The Multiplier parameter is utilized for percentage calculations. It encompasses two lines: Upper Line and Lower Line, where HOTT employs the highest series and LOTT uses the lowest series. If the 'High' price surpasses HOTT, the indicator generates Long signals. Similarly, if the 'Low' price falls below LOTT, the indicator generates Short signals. When the Sum N Bars option is activated, signals are generated based on the confirmation concept for N bars.
7) WHAT IS "ROTT"?
Relative OTT serves as a valuable tool for long-period filters. ROTT operates with two parameters. The Support is determined by the length parameter and equals twice the moving average. The Multiplier parameter is utilized for percentage calculations. The indicator generates signals based on the intersection of these two lines.
8) WHAT IS "FT"?
"Fırsatçı" (opportunistic) Trend is a system that revolves around two levels, namely major and minor OTT. It operates with three parameters: Length, Major Multiplier, and Minor Multiplier. FT comprises two lines, Support and Target. The indicator generates signals based on the intersection of these two lines.
9) WHAT IS "RTR"?
Relative True Range is not an OTT system; however, it serves as a complementary feature. It does not have any referenced signals. RTR is devised to obtain a normalized result of the current market volatility. It operates with two parameters: ATR, which is determined by the Length 1 parameter, and RTR, defined by the Length 2 parameter.
A TIP
If any indicator is defined in function form instead of the OTT function, the applications can also be adapted for different indicators. E.g. Supertrend, PMAX, AlphaTrend, etc.
UPDATE
Anıl Özekşi is a competent algotrader who shares his work with open sources. I will update the indicator as new applications are released.
DISCLEIMER
This is just an indicator, nothing more. The script is for informational and educational purposes only. The use of the script does not constitute professional and/or financial advice. The responsibility for risks associated with the use of the script is solely owned by the user. Do not forget to manage your risk. And trade as safely as possible. Good luck!
Smart Money Breakouts [ChartPrime]The " Smart Money Breakouts " indicator is designed to identify breakouts based on changes in character (CHOCH) or breaks of structure (BOS) patterns, facilitating automated trading with user-defined Take Profit (TP) level.
the indicator incorporates essential elements such as volume analysis and a data table to assist traders in optimizing their strategies.
🔸 Breakout Detection:
The indicator scans price movements for "Change in Character" (CHOCH) and "Break of Structure" (BOS) patterns, signaling potential breakout opportunities in the market.
🔸User-Defined TP :
Traders can customize the Take Profit (TP) through the indicator settings, with these levels dynamically calculated based on the Average True Range (ATR). This allows for precise risk management and profit targets that adapt to market volatility.
🔸 Volume Analysis and Trade Direction Specific Analysis:
The indicator includes a volume checker that provides valuable insights into the strength of the breakout, taking into account trade direction.
🔸If the volume label is red and the trade is long, it suggests a higher likelihood of hitting the Stop Loss (SL).
🔸If the volume label is green and the trade is long, it indicates a higher probability of hitting the Take Profit (TP).
🔸For short trades, a red volume label suggests a higher likelihood of hitting TP, while a green label suggests a higher likelihood of hitting SL.
🔸A yellow volume label suggests that the volume is inconclusive, neither favoring bullish nor bearish movements.
🔸Data Table:
The indicator features a data table that keeps track of the number of winning and losing trades for specific timeframes or configurations.
This table serves as a valuable tool for traders to analyze performance and discover optimal settings and timeframes.
The "Smart Money Breakouts" indicator provides traders with a comprehensive solution for breakout trading, combining technical analysis of changes in character and breaks of structure, volume insights, and performance tracking while dynamically adjusting TP and SL levels based on market volatility through the ATR.
Liquidity Heatmap [BigBeluga]The Liquidity Heatmap is an indicator designed to spot possible resting liquidity or potential stop loss using volume or Open interest.
The Open interest is the total number of outstanding derivative contracts for an asset—such as options or futures—that have not been settled. Open interest keeps track of every open position in a particular contract rather than tracking the total volume traded.
The Volume is the total quantity of shares or contracts traded for the current timeframe.
🔶 HOW IT WORKS
Based on the user choice between Volume or OI, the idea is the same for both.
On each candle, we add the data (volume or OI) below or above (long or short) that should be the hypothetical liquidation levels; More color of the liquidity level = more reaction when the price goes through it.
Gradient color is calculated between an average of 2 points that the user can select. For example: 500, and the script will take the average of the highest data between 500 and 250 (half of the user's choice), and the gradient will be based on that.
If we take volume as an example, a big volume spike will mean a lot of long or short activity in that candle. A liquidity level will be displayed below/above the set leverage (4.5 = 20x leverage as an example) so when the price revisits that zone, all the 20x leverage should be liquidated.
Huge volume = a lot of activity
Huge OI = a lot of positions opened
More volume / OI will result in a stronger color that will generate a stronger reaction.
🔶 ROUTE
Here's an example of a route for long liquidity:
Enable the filter = consider only green candles.
Set the leverage to 4.5 (20x).
Choose Data = Volume.
Process:
A green candle is formed.
A liquidity level is established.
The level is placed below to simulate the 20x leverage.
Color is applied, considering the average volume within the chosen area.
Route completed.
🔶 FEATURE
Possibility to change the color of both long and short liquidity
Manual opacity value
Manual opacity average
Leverage
Autopilot - set a good average automatically of the opacity value
Enable both long or short liquidity visualization
Filtering - grab only red/green candle of the corresponding side or grab every candle
Data - nzVolume - Volume - nzOI - OI
🔶 TIPS
Since the limit of the line is 500, it's best to plot 2 scripts: one with only long and another with only short.
🔶 CONCLUSION
The liquidity levels are an interesting way to think about possible levels, and those are not real levels.
DrNon_NASDAQ10Title: NASDAQ 10 Index with TOP 10 Securities
Introduction:
TradingView offers traders and investors a powerful platform for technical analysis and trading. One of its notable features is the ability to create custom indices based on the values of multiple individual securities. In this blog post, we will explore how to build a custom index with 10 securities in TradingView using Pine Script, the platform's proprietary programming language.
Description:
Custom indices allow market participants to track the performance of a specific group of securities, providing valuable insights into the collective performance of the chosen assets. By leveraging Pine Script, traders can easily develop and deploy custom indicators and strategies to build their own indices.
The script provided focuses on creating a custom index with 10 securities. The selected securities include popular stocks such as AAPL (Apple Inc.), MSFT (Microsoft Corporation), GOOG (Alphabet Inc.), AMZN (Amazon.com Inc.), NVDA (NVIDIA Corporation), TSLA (Tesla Inc.), META (Facebook, Inc.), AVGO (Broadcom Inc.), PEP (PepsiCo, Inc.), and COST (Costco Wholesale Corporation).
Using the security() function in Pine Script, we retrieve the closing prices of each individual security to ensure accurate data for the index calculation.
The index value is then calculated by summing the closing prices of the 10 securities. This simple arithmetic operation captures the overall performance of the custom index.
To visualize the index, we use the plot() function to display the index value on the chart. Traders can observe the custom index alongside other technical indicators or price action, aiding in decision-making and market analysis.
By building a custom index with 10 securities in TradingView, traders gain a consolidated view of the performance of these chosen assets. This allows for easier tracking of sector trends, evaluation of specific strategies, and the ability to compare the performance of individual portfolios against the broader market.
Conclusion:
TradingView's Pine Script provides traders and investors with a flexible solution to build custom indices. By defining the 10 individual securities, calculating the index value, and plotting it on the chart, traders can monitor the collective performance of these chosen assets. Custom indices offer insights into sector performance, enable the evaluation of specific strategies, and provide a benchmark for comparing portfolio performance. By harnessing the power of custom indices in TradingView, traders can enhance their decision-making process and gain a competitive edge in the market.
Position and Profit/LossHelps users track their position and profit/loss in real-time.
Instructions :
Open the indicator settings
Input your Quantity, Buy Price, Fee, and Target Price
This indicator is designed to provide users with simple real-time tracking of their positions and profit/loss within a trading session. It offers clear and concise information that enables users to understand their current position's profitability, making it easier for them to manage their trades effectively.
Input parameters
qty : Quantity of the position (default value: 100.0). The target label is represented by a green cross
buy_price : Buy price of the position (default value: 1.0).
fee : Fee percentage for the transaction (default value: 0.0016). note that this is not a percentage, but rather a decimal. So 0.0016 is 0.16%
target : Target price for the position (default value: 1.0). This is an extra label to show you where your target is on the chart. The target label is represented by a green cross
In addition to the main profit/loss label, the script also displays two auxiliary labels. The "BuyPrice" label presents the buy price of the position as a red cross symbol on the chart, allowing users to easily identify their entry point. The "targetSell" label displays the target sell price as green cross symbol, indicating the desired exit point for the position. These visual markers help users visualize their trading strategy.
The script takes into account that users may only need this information displayed on the last bar, as continuous updates might not be necessary. By checking if the current bar is the last one, the script ensures that the labels are only displayed when relevant.
Limitations
The script assumes that trading is done using the same quantity; which is not always the case. This will change with subsequent updates.
Time Series Model IndicatorHello,
I am releasing this time series modelling indicator.
Brief overview of the indicator's functionality:
The Time Series Model indicator is a technical analysis tool that calculates and visualizes a linear regression line based on historical price data. It assesses the trend direction and provides an outer band around the regression line to indicate potential support and resistance levels. The indicator also detects outliers in the price data and calculates correlations between the time variable and the closing price. It offers various customization options such as input length, user-defined hours in advance, display settings for tables and fills, and the ability to show variable correlations. Overall, this indicator aims to help traders identify trends, potential reversals, and price extremes in a given time series.
Specific Functions:
Slope Calculations: The indicator calculates the slope and intercept of the regression line using the specified length of assessment (user defined). It also computes the residuals, standard error of the regression, and the upper and lower bounds of the standard error region. Additionally, it calculates multiple standard deviation bands around the regression line. The slope will change to green if the stock is in an uptrend and to red if the stock is in a downtrend.
Outliers: This feature detects extreme positive and negative outliers based on the z-score calculated from the price data. It highlights the outliers with a red background color to red if this option is selected.
Correlation to Time Assessments: This feature performs trend assessments based on the correlation between time and price data. It identifies uptrends, downtrends, falling trends, rising trends, etc.
Outerband Plots: This feature plots the regression line, standard error bands, and multiple standard deviation bands around the regression line. It also fills the areas between these lines.
Trend Assessment: This feature further assesses the trend based on the strength of the correlation. It identifies strong up or down trends, moderate trends, weak trends, no trend, etc.
Linear Regression Time Data: This section retrieves price data (close, high, low, open) for the specified timeframe and stores them in arrays for a linear regression analysis.
Define LinReg Variables: This section calculates linear regression lines and their upper and lower control limits for the close, low and high prices. It also calculates the correlation between close price and time.
Manual assessments: This feature allows for the manual assessment of time series data. The user can input a look forward for hours in the future and get the predicted price range based on the current time relationship. See image below:
Calculating model "fit": The indicator will display the amount of time the stock closes within and outside its respective bands to ascertain the degree of "fit" (see image below):
Explanations:
The outer cloud: The outer, tealish green cloud represents the regression line + 1.5 standard deviations from the regression line.
The inner cloud: The inner, white coloured cloud represents the immediate time series range calculated through regression of the open, high and low price of the ticker.
Correlations:
The ability of the indicator to calculate correlations on both the smaller and larger timeframes are its strongest feature. You can see the formation of trends by tracking the correlation over the length of the time series model's assessment. You can also track the degree of change. The image below shows the correlation table:
In this image, we can see that the stock is in a moderate downtrend manifested by a correlation of -0.73 (purple arrow).
This downtrend is weakening as manifested by a positive change of 0.05 on the shorter timeframe.
If we scroll down on the table and see the Close, High and Low, we can see that the larger trend over time is a downtrend and that this downtrend is actually strengthening. We know this by the negative change (negative change = significant inverse relationship to time is increasing. i.e. as time increases, the stock price decreases proportionately).
So what does negative correlation to time mean?
If a stock's price exhibits a negative correlation to time, it implies that there is a systematic relationship between the passage of time and the stock's price movement in the opposite direction. This finding could have several potential implications for traders and investors. Firstly, it suggests that the stock's price tends to decrease as time progresses, indicating a downward trend or bearish sentiment. This information might be useful for traders looking to capitalize on short-selling or hedging strategies. Secondly, it could indicate a potential opportunity to predict future price movements based on the timing of negative correlations. By understanding the relationship between time and price, investors may be able to make more informed decisions about when to buy or sell the stock. Lastly, a negative correlation to time may also suggest the influence of external factors or market conditions that systematically impact the stock's performance over time. Therefore, monitoring this correlation can provide insights into broader market dynamics and help investors better understand the stock's behavior.
What about a positive correlation to time?
If a stock's price demonstrates a positive correlation to time, it means that there is a consistent relationship between the passage of time and the stock's price movement in the same direction. This positive correlation to time can have significant implications for traders and investors. Firstly, it indicates a potential upward trend or bullish sentiment, suggesting that the stock's price tends to increase as time progresses. This information can be valuable for investors seeking long-term growth opportunities or looking to capitalize on upward price movements. Secondly, a positive correlation to time may provide insights into the stock's historical performance patterns and help identify potential buying or selling opportunities based on the timing of positive correlations. Additionally, understanding this correlation can aid in assessing the stock's overall trajectory and identifying potential market trends. It's important to note that positive correlation to time does not guarantee future performance, but it can offer valuable information to inform investment decisions.
Because this indicator is pretty big, I have done an overview and tutorial video which I will link below:
As always, please leave your comments and suggestions below.
I thank you for taking the time to read and check out this indicator.
Safe trades everyone and enjoy your weekend!
market sessions by sellstreetIndicator of trading sessions:
Indicator created to track the opening of trading sessions:
Asia, Frankfurt, London, New York.
Tracking the opening of these key levels
- Day Opening (DO), Week Opening (WO), Month Opening (MO).
- New York (NYM) openings display.
- Highs and lows of the previous day (PDH/PDL).
- Day of the week display.
- Formation of the Сentral Bank Dealers Range (CBDR).
Indicator settings.
The open source code will help traders to understand the technical part of the script.
Flexible visual and technical setup of the indicator:
- Ability to enable/disable the display of trading sessions on the history.
- Enabling/disabling the display of the key opening levels on the chart history for a convenient backtest.
- Automatically switch to summer/winter time.
To use this indicator, add it to your favorites after the chart
TradingView must be overloaded to work correctly.
Simple Dominance Momentum IndicatorThe Simple Dominance Momentum Indicator is a powerful tool for tracking market trends in the world of cryptocurrency. By analyzing the relationship between dominance and market movement, this indicator helps traders identify when money is flowing into or out of the market.
Using the pane structure on TradingView, the Dominance Momentum Indicator makes it easy to visualize and track data from CryptoCap charts. Whether you're a seasoned investor or starting out, this indicator can help you make more informed trading decisions.
All this indicator does is create the pane with a line chart using the Dominance charts to allow you to see the data with one button instead of doing it all manually. However with the addition to allow it to toggle between crypto and stables, so if you are using a /BTC pair, you don't have to add a new pane on, it automatically converts. If you are looking at USDT pairs for example, it will highlight that one for you.
While it can work under any conditions, the Dominance Momentum Indicator is particularly effective on higher timeframes, providing valuable insight into the overall plot of the market trend. With a 55EMA and a faster-moving average of 21EMA, this indicator is designed to help you stay ahead of the curve and make smarter trading decisions.
Remember the golden rule for stablecoin dominance. Down = good, and up = bad; however, you can just invert the indicator, so it flows with the market.
When it comes to the dominance of individual cryptocurrencies, for example, DOT.D, you might find that it going up = increasing dominance is STRENGTH. If the dominance of that is increasing it means it's growing.
Creator Credit: Jamie Goodland
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
Extension %This is a tracking tool to measure two different kinds of distances:
- Gaps, from the open/close or the high/low value to the nearest open/close or high/low value.
- Price extensions of one or two candles from a preferred starting point (open, high, low or close) to a final point (open, high, low or close). The two-candles mode includes an optional rectangle to help you visualize the first and the last point of the measurement.
The script will plot a label with a percentage when the extension reaches the value you set. Unless you choose to track the one-candle price extension, the label will always be displayed on the high/low value of the second candle.
