ATH/ATL Tracker [LuxAlgo]The ATH/ATL Tracker effectively displays changes made between new All-Time Highs (ATH)/All-Time Lows (ATL) and their previous respective values, over the entire history of available data.
The indicator shows a histogram of the change between a new ATH/ATL and its respective preceding ATH/ATL. A tooltip showing the price made during a new ATH/ATL alongside its date is included.
🔶 USAGE
By tracking the change between new ATHs/ATLs and older ATHs/ATLs, traders can gain insight into market sentiment, breadth, and rotation.
If many stocks are consistently setting new ATHs and the number of new ATHs is increasing relative to old ATHs, it could indicate broad market participation in a rally. If only a few stocks are reaching new ATHs or the number is declining, it might signal that the market's upward momentum is decreasing.
A significant increase in new ATHs suggests optimism and willingness among investors to buy at higher prices, which could be considered a positive sentiment. On the other hand, a decrease or lack of new ATHs might indicate caution or pessimism.
By observing the sectors where stocks are consistently setting new ATHs, users can identify which sectors are leading the market. Sectors with few or no new ATHs may be losing momentum and could be identified as lagging behind the overall market sentiment.
🔶 DETAILS
The indicator's main display is a histogram-style readout that displays the change in price from older ATH/ATLs to Newer/Current ATH/ATLs. This change is determined by the distance that the current values have overtaken the previous values, resulting in the displayed data.
The largest changes in ATH/ATLs from the ticker's history will appear as the largest bars in the display.
The most recent bars (depending on the selected display setting) will always represent the current ATH or ATL values.
When determining ATH & ATL values, it is important to filter out insignificant highs and lows that may happen constantly when exploring higher and lower prices. To combat this, the indicator looks to a higher timeframe than your chart's timeframe in order to determine these more significant ATHs & ATLs.
For Example: If a user was on a 1-minute chart and 5 highs-new highs occur across 5 adjacent bars, this has the potential to show up as 5 new ATHs. When looking at a higher timeframe, 5 minutes, only the highest of the 5 bars will indicate a new ATH. To assist with this, the indicator will display warnings in the dashboard when a suboptimal timeframe is selected as input.
🔹 Dashboard
The dashboard displays averages from the ATH/ATL data to aid in the anticipation and expectations for new ATH/ATLs.
The average duration is an average of the time between each new ATH/ATL, in this indicator it is calculated in "Days" to provide a more comprehensive understanding.
The average change is the average of all change data displayed in the histogram.
🔶 SETTINGS
Duration: The designated higher timeframe to use for filtering out insignificant ATHs & ATLs.
Order: The display order for the ATH/ATL Bars, Options are to display in chronological (oldest to newest) or reverse chronological order (newest to oldest).
Bar Width: Sets the width for each ATH/ATL bar.
Bar Spacing: Sets the # of empty bars in between each ATH/ATL bar.
Dashboard Settings: Parameters for the dashboard's size and location on the chart.
Трендовый анализ
Death Cross and Golden Cross HighlighterOverview
The script is designed to visually indicate the occurrence of Death Cross and Golden Cross events on a TradingView chart. It achieves this by calculating two moving averages (short-term and long-term) and plotting them on the chart. It then detects when these moving averages cross and highlights these points with labels and background colors.
Inputs
The script begins by defining input parameters:
- Short Moving Average Length: This is set to 50 by default, representing the short-term moving average period.
- Long Moving Average Length: This is set to 200 by default, representing the long-term moving average period.
These inputs allow users to customize the lengths of the moving averages according to their trading strategy.
Moving Averages Calculation
The script calculates two simple moving averages (SMAs) based on the closing prices:
- Short Moving Average (shortMA): Calculated over the short-term period specified by the user.
- Long Moving Average (longMA): Calculated over the long-term period specified by the user.
Plotting the Moving Averages
The moving averages are then plotted on the chart:
- The short-term moving average is plotted in blue.
- The long-term moving average is plotted in red.
These lines help users visually track the trends and potential crossover points.
Identifying Crossovers
The script identifies two key events:
- Golden Cross: Occurs when the short-term moving average crosses above the long-term moving average. This is typically considered a bullish signal, indicating a potential upward trend.
- Death Cross: Occurs when the short-term moving average crosses below the long-term moving average. This is typically considered a bearish signal, indicating a potential downward trend.
Highlighting Crossovers
To make the crossover events more noticeable, the script adds visual cues:
- Golden Cross: When a Golden Cross is detected, a green label with an upward arrow is plotted below the bar where the crossover occurs.
- Death Cross: When a Death Cross is detected, a red label with a downward arrow is plotted above the bar where the crossover occurs.
Background Coloring
Additionally, the script highlights the background of the chart:
- When a Golden Cross occurs, the background color is changed to a translucent green.
- When a Death Cross occurs, the background color is changed to a translucent red.
These background colors help emphasize the crossover events, making them easier to spot.
Usage
To use this script, a user would:
1. Copy the script and paste it into the Pine Script editor on TradingView.
2. Save the script and apply it to their chart.
By doing so, the user will see the moving averages plotted, and any Golden Cross or Death Cross events will be highlighted with labels and background colors. This visual aid helps traders quickly identify significant crossover events, which can inform their trading decisions.
Trend Strength Signals [AlgoAlpha]🌟Introducing the Trend and Strength Signals indicator by AlgoAlpha ! This tool is designed to help you identify trends and gauge market strength with precision and ease. 📈🚀
🛠 Customizable Parameters : Adjust the period, standard deviation multiplier, gauge size, and colors to fit your trading style.
📊 Trend Detection : Visualize trends with clear color-coded signals for uptrends and downtrends.
📈 Strength Gauge : Assess market strength with a dynamic gauge that adapts to the current price action.
🔔 Alerts : Set alerts for bullish and bearish trend crossovers and take profit points to stay ahead of the market.
🎨 Visual Enhancements : Enjoy a clutter-free chart with the integration of plot shapes, color fills, and gradient gauges.
🚀 Quick Guide to Using the Trend and Strength Signals Indicator
Maximize your trading with the Trend and Strength Signals indicator by following these streamlined steps! 🎯✨
🛠 Add the Indicator : Add the indicator to your favorites. Customize settings like period, standard deviation multiplier, and colors to fit your trading style.
📊 Market Analysis : Observe the color-coded candles and gauge to understand market trend direction and strength. Use the alerts for key trading signals.
🔔 Alerts : Enable notifications for trend crossovers and take profit points to catch trading opportunities without constantly monitoring the chart.
⚙️ How it works
This indicator calculates the moving average and standard deviation of the closing price over a customizable period to identify the upper and lower bounds. When the price crosses these bounds, it signals an uptrend or downtrend. The gauge measures market strength by comparing the price to the moving average and scaling it over a customizable range, while the underlying logic uses concepts from the Bollinger Bands, this indicator gives a unique perspective on price behavior through added features and signals derived from it.
Unleash the power of trend and strength analysis with this comprehensive indicator! Happy trading! 🚀📈✨
Low and High Values [Alorse]🌟 What does this indicator do?
This magical indicator shows you the lowest (Low) and highest (High) values of the last X candles directly on your chart. Not only that, but it also tells you how much the price has changed from the opening price of the current candle to these key points, all in percentage format. You'll have a clear and precise view of market movement!
🔧 Customize to your liking
Want to adjust the number of candles to consider? No problem! You can easily change this parameter to suit your preference. Whether you like short-term strategies with just a few candles or prefer more extensive analysis with many candles, our indicator adapts to you.
🚀 How can this indicator help you?
Identify Support and Resistance: By showing the lowest and highest points, it helps you identify key support and resistance levels. Perfect for planning your entries and exits!
Trend Analysis: With the percentage labels, you can quickly see how the price has moved relative to recent extremes, helping you confirm trends or anticipate possible reversals.
Trading Strategies: Imagine the price is near a recent low, but the percentage indicates a significant drop from the opening. This could be a buy signal if you expect a rebound. Conversely, if the price is near a recent high with a large percentage increase, you might consider selling.
Calculate Stop Loss: Use this indicator to determine your Stop Loss levels by leaving a bit of margin between the indicator value and your desired SL. This helps protect your positions while allowing for some price fluctuation.
📊 Examples of Use
Intraday Trader: Use the indicator with 10-20 candles to capture quick moves and capitalize on daily fluctuations.
Mid-term Trader: Set the indicator to consider 50 candles for a broader view of trends and reversal points.
Long-term Strategist: Adjust the indicator to 100 candles or more to identify highs and lows over larger time frames.
🛠️ Customizable Parameters
Number of Candles: Define the number of candles the indicator will analyze to calculate the lowest and highest values. It's all up to you!
Volume-Enhanced Momentum Moving Average (VEMMA)Volume-Enhanced Momentum Moving Average (VEMMA)
Overview:
The Volume-Enhanced Momentum Moving Average (VEMMA) helps you spot market trends by combining momentum and volume as a moving average. This unique moving average adjusts itself based on the strength and activity of the market, giving you a clearer picture of what’s happening.
How It Works:
1. Key Settings (all of these are adjustable in the settings panel of the indicator):
◦ Base Length: Looks back over the last 50 days by default.
◦ Momentum Length: Uses the past 14 days to measure market strength.
◦ Volume Length: Uses the past 30 days to average trading volume.
◦ High/Low Thresholds: Considers RSI values above 70 as high momentum and below 30 as low momentum.
2. Momentum and Volume:
◦ Momentum: Calculated using the Relative Strength Index (RSI) to see if the market is gaining or losing strength.
◦ Volume: Average trading volume is calculated over the last 30 days to gauge trading activity.
3. VEMMA Calculation:
◦ For each of the past 50 days:
▪ Check Momentum: If RSI > 70, it’s high momentum; if RSI < 30, it’s low.
▪ Weight by Volume: High momentum days with high volume get more weight; low momentum days get less.
▪ Combine: Multiply the closing price by this weight and sum it up.
◦ Average: Divide the total by 50 to get the VEMMA value.
4. Visuals:
◦ Lines: Two lines, VEMMA1 (blue) and VEMMA2 (orange), show the adjusted moving averages.
◦ Colours: Background colors help you quickly spot high (green) and low (red) momentum periods.
How to Use:
• Spot Trends: Rising VEMMA lines suggest an uptrend; falling lines suggest a downtrend.
• Confirm Signals: When both VEMMA1 and VEMMA2 move together, it indicates a strong trend.
• Identify Reversals: Watch for background color changes from green to red or vice versa to catch potential trend reversals.
If the market has been strong and active, the VEMMA line will rise more sharply. If the market is weak and quiet, the line will be smoother.
Benefits:
• Integrated View: Combines market strength and trading activity for a fuller picture.
• Responsive: Adapts to significant market changes, highlighting key movements.
• Easy to Read: Clear visuals with color-coded backgrounds make interpretation simple.
Remember, just like any other indicator, this is not supposed to be used alone. Use it as part of your greater trading strategy. I do however believe it works exceptionally well for finding longer term trends early. The default VEMMA settings work very well as replacement for the EMA 200. Try it and see how it goes. Play around with the settings. Feedback appreciated.
Enhanced Reversal DetectionScript Description:
The "Enhanced Reversal Detection" indicator is a powerful tool designed to identify potential market reversals across various financial instruments. It incorporates a sophisticated algorithm that analyzes price action along with key technical indicators such as the Relative Strength Index (RSI), Bollinger Bands, and Moving Average (MA).
How to Use:
Adjustable Parameters: The indicator offers a range of adjustable parameters to cater to different trading preferences and market conditions.
RSI Length: Adjusts the length of the RSI calculation to fine-tune sensitivity.
Overbought Level: Sets the threshold for identifying overbought conditions on the RSI scale.
Oversold Level: Sets the threshold for identifying oversold conditions on the RSI scale.
Bollinger Bands Length: Determines the length of the Bollinger Bands calculation.
Bollinger Bands Multiplier: Adjusts the standard deviation multiplier for the Bollinger Bands, influencing band width.
Moving Average Length: Defines the length of the Moving Average calculation to capture trend direction.
Min Bars Between Signals: Sets the minimum number of bars required between consecutive reversal signals.
ADX Length: Adjusts the length of the Average Directional Index (ADX) calculation.
ADX Threshold: Defines the threshold value for ADX, serving as a filter for reversal signals.
Signal Generation: The indicator generates signals for both bullish and bearish reversals based on predefined criteria. A bullish reversal signal is triggered when the closing price exceeds the lower Bollinger Band and RSI falls below the oversold threshold. Conversely, a bearish reversal signal occurs when the closing price falls below the upper Bollinger Band and RSI surpasses the overbought threshold.
Alerts: Traders can opt to receive alerts for bullish and bearish reversal signals, enabling them to stay informed of potential trading opportunities even when away from the platform.
Publication Readiness:
To ensure readiness for publication in the TradingView public library, the script has been meticulously crafted and documented:
The code is extensively commented to provide clear explanations of parameters, calculations, and signal generation logic.
Best coding practices have been followed to enhance readability and maintainability.
Rigorous testing has been conducted to validate the accuracy and reliability of signal generation across various market conditions.
The script adheres to TradingView's guidelines and policies for script publication, ensuring compliance with platform standards and user expectations.
With its comprehensive features and user-friendly design, the "Enhanced Reversal Detection" indicator is poised to become a valuable asset for traders seeking to identify high-probability reversal opportunities in the financial markets.
ka66: FX Sessions High/LowThis indicator is specific to the 24-hour Forex Market. It provides 2 features:
Demarcating forex sessions with open and close lines. Note that looking at various sources online, we use the convention that the Asia session starts with the Tokyo market open, rather than the earlier Sydney session. Presumably this is better since we then have more liquidity in the market. Note that we have three sessions: Asia, London, New York.
At the end of each session, we begin plotting that (closed) session's high and low, which acts as a natural support and resistance for the Forex market. This is the key feature it provides. The first feature is mainly there for a visual guide, which can be turned off via the UI settings, but it certainly helps verifying the logic!
For more background, we are taking the idea of Previous Day High/Low (PDH/PDL), but adjusting it to a multi-session market like Forex. In essence, this is is a "Previous Session High/Low" indicator.
PDH/PDL works fine when you have a market with Regular Trading Hours, ignoring Extended Hours. However, in the Forex market, each session can have differing sentiments, e.g. we often see say London bringing prices up, and New York bringing them back down.
The break of session high/lows (or bouncing off them) can reflect where the potential direction price is going to take.
I also categorised this as a Sentiment indicator, because support and resistance areas where prices react do provide the sentiment of the market. They aren't just lines, they are prices of interest to major players.
Stock Rating [TrendX_]# OVERVIEW
This Stock Rating indicator provides a thorough evaluation of a company (NON-FINANCIAL ONLY) ranging from 0 to 5. The rating is the average of six core financial metrics: efficiency, profitability, liquidity, solvency, valuation, and technical ratings. Each metric encompasses several financial measurements to ensure a robust and holistic evaluation of the stock.
## EFFICIENCY METRICS
1. Asset-to-Liability Ratio : Measures a company's ability to cover its liabilities with its assets.
2. Equity-to-Liability Ratio : Indicates the proportion of equity used to finance the company relative to liabilities.
3. Net Margin : Shows the percentage of revenue that translates into profit.
4. Operating Expense : Reflects the costs required for normal business operations.
5. Operating Expense Ratio : Compares operating expenses to total revenue.
6. Operating Profit Ratio : Measures operating profit as a percentage of revenue.
7. PE to Industry Relative PE/PB : Compares the company's PE ratio to the industry average.
## PROFITABILITY METRICS
1. ROA : Indicates how efficiently a company uses its assets to generate profit.
2. ROE : Measures profitability relative to shareholders' equity.
3. EBITDA : Reflects a company's operational profitability.
4. Free Cash Flow Margin : Shows the percentage of revenue that remains as free cash flow.
5. Revenue Growth : Measures the percentage increase in revenue over a period.
6. Gross Margin : Reflects the percentage of revenue exceeding the cost of goods sold.
7. Net Margin : Percentage of revenue that is net profit.
8. Operating Margin : Measures the percentage of revenue that is operating profit.
## LIQUIDITY METRICS
1. Current Ratio : Indicates the ability to cover short-term obligations with short-term assets.
2. Interest Coverage Ratio : Measures the ability to pay interest on outstanding debt.
3. Debt-to-EBITDA : Compares total debt to EBITDA.
4. Debt-to-Equity Ratio : Indicates the relative proportion of debt and equity financing.
## SOLVENCY METRICS
1. Altman Z-score : Predicts bankruptcy risk
2. Beneish M-score : Detects earnings manipulation.
3. Fulmer H-factor : Predicts business failure risk.
## VALUATION METRICS
1. Industry Relative PE/PB Comparison : Compares the company's PE and PB ratios to industry averages.
2. Momentum of PE, PB, and EV/EBITDA Multiples : Tracks the trends of PE, PB, and EV/EBITDA ratios over time.
## TECHNICAL METRICS
1. Relative Strength Index (RSI) : Measures the speed and change of price movements.
2. Supertrend : Trend-following indicator that identifies market trends.
3. Moving Average Golden-Cross : Occurs when a short-term MA crosses above mid-term and long-term MA which are determined by half-PI increment in smoothing period.
4. On-Balance Volume Golden-Cross : Measures cumulative buying and selling pressure.
Cosine Kernel Regressions [QuantraSystems]Cosine Kernel Regressions
Introduction
The Cosine Kernel Regressions indicator (CKR) uses mathematical concepts to offer a unique approach to market analysis. This indicator employs Kernel Regressions using bespoke tunable Cosine functions in order to smoothly interpret a variety of market data, providing traders with incredibly clean insights into market trends.
The CKR is particularly useful for traders looking to understand underlying trends without the 'noise' typical in raw price movements. It can serve as a standalone trend analysis tool or be combined with other indicators for more robust trading strategies.
Legend
Fast Trend Signal Line - This is the foreground oscillator, it is colored upon the earliest confirmation of a change in trend direction.
Slow Trend Signal Line - This oscillator is calculated in a similar manner. However, it utilizes a lower frequency within the cosine tuning function, allowing it to capture longer and broader trends in one signal. This allows for tactical trading; the user can trade smaller moves without losing sight of the broader trend.
Case Study
In this case study, the CKR was used alongside the Triple Confirmation Kernel Regression Oscillator (KRO)
Initially, the KRO indicated an oversold condition, which could be interpreted as a signal to enter a long position in anticipation of a price rebound. However, the CKR’s fast trend signal line had not yet confirmed a positive trend direction - suggesting that entering a trade too early and without confirmation could be a mistake.
Waiting for a confirmed positive trend from the CKR proved beneficial for this trade. A few candles after the oversold signal, the CKR's fast trend signal line shifted upwards, indicating a strong upward momentum. This was the optimal entry point suggested by the CKR, occurring after the confirmation of the trend change, which significantly reduced the likelihood of entering during a false recovery or continuation of the downtrend.
This is one of the many uses of the CKR - by timing entries using the fast signal line , traders could avoid unnecessary losses by preventing premature entries.
Methodology
The methodology behind CKR is a multi-layered approach and utilizes many ‘base’ indicators.
Relative Strength Index
Stochastic Oscillator
Bollinger Band Percent
Chande Momentum Oscillator
Commodity Channel Index
Fisher Transform
Volume Zone Oscillator
The calculated output from each indicator is standardized and scaled before being averaged. This prevents any single indicator from overpowering the resulting signal.
// ╔════════════════════════════════╗ //
// ║ Scaling/Range Adjustment ║ //
// ╚════════════════════════════════╝ //
RSI_ReScale (_res ) => ( _res - 50 ) * 2.8
STOCH_ReScale (_stoch ) => ( _stoch - 50 ) * 2
BBPCT_ReScale (_bbpct ) => ( _bbpct - 0.5 ) * 120
CMO_ReScale (_chandeMO ) => ( _chandeMO * 1.15 )
CCI_ReScale (_cci ) => ( _cci / 2 )
FISH_ReScale (_fish1 ) => ( _fish1 * 30 )
VZO_ReScale (_VP, _TV ) => (_VP / _TV) * 110
These outputs are then fed into a customized cosine kernel regression function, which smooths the data, and combines all inputs into a single coherent output.
// ╔════════════════════════════════╗ //
// ║ COSINE KERNEL REGRESSIONS ║ //
// ╚════════════════════════════════╝ //
// Define a function to compute the cosine of an input scaled by a frequency tuner
cosine(x, z) =>
// Where x = source input
// y = function output
// z = frequency tuner
var y = 0.
y := math.cos(z * x)
Y
// Define a kernel that utilizes the cosine function
kernel(x, z) =>
var y = 0.
y := cosine(x, z)
math.abs(x) <= math.pi/(2 * z) ? math.abs(y) : 0. // cos(zx) = 0
// The above restricts the wave to positive values // when x = π / 2z
The tuning of the regression is adjustable, allowing users to fine-tune the sensitivity and responsiveness of the indicator to match specific trading strategies or market conditions. This robust methodology ensures that CKR provides a reliable and adaptable tool for market analysis.
Anchored Monte Carlo Shuffled Projection [LuxAlgo]The Anchored Monte Carlo Shuffled Projection tool randomly simulates future price points based on historical bar movements made before a user-anchored point in time.
By anchoring our data and projections to a single point in time, users can better understand and reflect on how the price played out while taking into consideration our random simulations.
🔶 USAGE
After selecting the indicator to apply to the chart, you will be prompted to "Set the Anchor Point". Do so by clicking on the desired location on your chart, only time is used as the anchor point.
Note: To select a new anchor point when applied to the chart, click on the 'More' dropdown next to the indicator status bar (○○○), then select "Reset points...".
Alternate Method: You are also able to click and drag the vertical line that displays on the anchor point bar when the indicator is highlighted.
By randomly simulating bar movements, a range is developed of potential price action which could be utilized to locate future price development as well as potential support/resistance levels.
Performing numerous simulations and taking the average at each step will converge toward the result highlighted by the "Average Line", and can point out where the price might develop, assuming the trend and amount of volatility persist.
Current closing price + Sum of changes in the calculation window
This constraint will cause the simulations always to display an endpoint consistent with the current lookback's slope.
While this may be helpful to some traders, this indicator includes an option to produce a less biased range, as seen below:
🔶 DETAILS
The Anchored Monte Carlo Shuffled Projection tool creates simulations based on prices within a user-set lookback window originating at the specified anchor point. Simulations are done as follows:
Collect each bar's price changes in the user-set window.
Randomize the order of each change in the window.
Project the cumulative sum of the shuffled changes from the current closing price.
Collect data on each point along the way.
This is the process for the Default calculation; for the 'Randomize Direction' calculation, when added onto the front for every other change, the value is inverted, creating the randomized endpoints for each simulation.
The script contains each simulation's data for that bar, with a maximum of 1000 simulations.
To get a glimpse behind the scenes, each simulation (up to 99) can be viewed using the 'Visualize Simulations' Options, as seen below.
Because the script holds the full simulation data, the script can also calculate this data, such as standard deviations.
In this script the Standard deviation lines are the average of all standard deviations across the vertical data groups, this provides a singular value that can be displayed a distance away from the simulation center line.
🔶 SETTINGS
Lookback: Sets the number of Bars to include in calculations.
Simulation Count: Sets the number of randomized simulations to calculate. (Max 1000)
Randomize Direction: See Details Above. Creates a more 'Normalized' Distribution
Visualize Simulations: See Details Above. Turns on Visualizations, and colors are randomly generated. Visualized max does not cap the calculated max. If 1000 simulations are used, the data will be from 1000 simulations, however, only the last 99 simulations will be visualized.
🔹 Standard Deviations
Standard Deviation Multiplier: Sets the multiplier to use for the Standard Deviation distance away from the center line.
🔹 Style
Extend Lines: Extends the Simulated Value Lines into the future for further reference and analysis.
[InvestorUnknown] Performance MetricsOverview
The Performance Metrics indicator is a tool designed to help traders and investors understand and utilize key performance metrics in their strategies. This indicator is inspired by the Rolling Risk-Adjusted Performance Ratios created by @EliCobra, but it offers enhanced usability and additional features to provide a more user-friendly code for understanding the calculations.
Features
Rolling Lookback:
Dynamic Lookback Calculation: The indicator automatically calculates the number of bars from the start of the asset's price history, up to a maximum of 5000 bars due to TradingView platform restrictions.
Adjustable Lookback Period: Users can manually set a lookback period or choose to use the rolling lookback feature for dynamic calculations.
RollingLookback() =>
x = bar_index + 1
y = x > 4999 ? 5000 : x > 1 ? (x - 1) : x
y
Trend Analysis
The Trend Analysis section in this indicator helps traders identify the direction of the market trend based on the balance of positive and negative returns over time. This is achieved by calculating the sums of positive and negative returns and optionally smoothing these values to provide a clearer trend signal.
Configuration: Enable smoothing if you want to reduce noise in the trend analysis. Choose between EMA and SMA for smoothing. Set the length for smoothing according to your preference for sensitivity (shorter lengths are more sensitive to changes, longer lengths provide smoother signals).
Interpretation:
- A positive trend difference (filled with green) indicates a bullish trend, suggesting more positive returns.
- A negative trend difference (filled with red) indicates a bearish trend, suggesting more negative returns.
- Colored bars provide a quick visual cue on the trend direction, helping to make timely trading decisions.
// The Trend Analysis section calculates and optionally smooths the sums of positive and negative returns.
// This helps identify the trend direction based on the balance of positive and negative returns over time.
Ps = Smooth ? Smooth_type == "EMA" ? ta.ema(pos_sum, Smooth_len) : ta.sma(pos_sum, Smooth_len) : pos_sum
Ns = Smooth ? Smooth_type == "EMA" ? ta.ema(neg_sum, Smooth_len) : ta.sma(neg_sum, Smooth_len) : neg_sum
// Calculate the difference between smoothed positive and negative sums
dif = Ps + Ns
Performance Metrics Table
Visual Table Display: Option to display a table on the chart with calculated performance metrics. This table includes comprehensive metrics like Mean Return, Positive and Negative Mean Return, Standard Deviation, Sharpe Ratio, Sortino Ratio, and Omega Ratio.
Performance Metrics Calculated
Mean Return:
Description: The average return over the lookback period.
Purpose: Helps in understanding the overall performance of the asset by providing a simple average of returns.
Positive Mean Return:
Description: The average of all positive returns over the lookback period.
Purpose: Highlights the average gain during profitable periods, giving insight into the asset's potential upside.
Negative Mean Return:
Description: The average of all negative returns over the lookback period.
Purpose: Focuses on the average loss during unprofitable periods, helping to assess the downside risk.
Standard Deviation (STDEV):
Description: A measure of volatility that calculates the dispersion of returns from the mean.
Purpose: Indicates the risk associated with the asset. Higher standard deviation means higher volatility and risk.
Sharpe Ratio:
Description: A risk-adjusted return metric that divides the mean return by the standard deviation of returns. It can be annualized if selected.
Purpose: Provides a standardized way to compare the performance of different assets by considering both return and risk. A higher Sharpe Ratio indicates better risk-adjusted performance.
sharpe_ratio = mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1)
Sortino Ratio:
Description: Similar to the Sharpe Ratio but focuses only on downside volatility. It divides the mean return by the standard deviation of negative returns. It can be annualized if selected.
Purpose: Offers a better assessment of downside risk by ignoring upside volatility. A higher Sortino Ratio indicates a higher return per unit of downside risk.
sortino_ratio = mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1)
Omega Ratio:
Description: The ratio of the probability-weighted average of positive returns to the probability-weighted average of negative returns.
Purpose: Measures the overall likelihood of positive returns compared to negative returns. An Omega Ratio greater than 1 indicates more frequent and/or larger positive returns compared to negative returns.
omega_ratio = (prob_pos * mean_pos) / (prob_neg * -mean_neg)
By calculating and displaying these metrics, the indicator provides a comprehensive view of the asset's performance, enabling traders and investors to make informed decisions based on both returns and risk-adjusted metrics.
Use Cases:
Performance Evaluation: Assesses an asset's performance by analyzing both returns and risk factors, giving a clear picture of profitability and volatility.
Risk Comparison: Compares the risk-adjusted returns of different assets or portfolios, aiding in identifying investments with superior risk-reward trade-offs.
Risk Management: Helps manage risk exposure by evaluating downside risks and overall volatility, enabling more informed and strategic investment decisions.
Dynamic Adaptive Regression BandsThis script provides a dynamic adaptive regression band indicator that adjusts based on recent market volatility. The regression bands are calculated using a length parameter adapted to the ATR (Average True Range) to ensure responsiveness to market conditions.
Key Features:
Dynamic Length Adjustment: The length of the regression calculation is adjusted based on the ATR to reflect current market volatility.
Multiple Bands: The script plots upper and lower bands at different ratios (1.618, 2.618, and 4.236) to provide comprehensive support and resistance levels.
Detailed Fillings: The areas between bands are filled with different colors to visualize different levels of volatility and trend strength.
Usage:
Regression Line: The main regression line follows the general trend of the price.
Upper/Lower Bands: These bands represent volatility-adjusted support and resistance levels.
Extended Bands: Additional bands at different ratios provide extended support and resistance zones for further trend analysis.
Original Script Credit:
This script is inspired by the original "Regr Linear Bands" script by MarcoValente, published on Jan 15, 2017. The original script starts from a linear regression and uses Fibonacci parameters to add bands above and below. The original work incorporates range and volatility, making the price move between bands of the same color. The middle line (linear regression) serves as a good signal; after a break occurs, the price typically moves to the last or second last band.
Super Trend and RSI Strategy### Super Trend and RSI Strategy: A Brief Overview
The Super Trend and RSI (Relative Strength Index) strategy is a popular trading approach that combines the trend-following capabilities of the Super Trend indicator with the momentum analysis of the RSI. This hybrid strategy aims to provide traders with reliable entry and exit signals by confirming trends and identifying potential reversals.
#### Super Trend Indicator
The Super Trend indicator is a trend-following tool that signals the current market direction. It is calculated using the Average True Range (ATR) to identify volatility and price movement. The indicator plots lines above or below the price, signaling bullish (green) or bearish (red) trends:
- **Buy Signal**: When the price crosses above the Super Trend line and the line turns green.
- **Sell Signal**: When the price crosses below the Super Trend line and the line turns red.
#### Relative Strength Index (RSI)
The RSI is a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100. It helps identify overbought or oversold conditions:
- **Overbought Condition**: RSI value above 70, suggesting the asset may be overvalued and a correction could be imminent.
- **Oversold Condition**: RSI value below 30, suggesting the asset may be undervalued and a rebound could be imminent.
#### Strategy Implementation
1. **Trend Confirmation with Super Trend**:
- Enter a long position (buy) when the Super Trend turns green and the price closes above it.
- Enter a short position (sell) when the Super Trend turns red and the price closes below it.
2. **Momentum Confirmation with RSI**:
- For long positions, ensure the RSI is not in the overbought zone (preferably below 70).
- For short positions, ensure the RSI is not in the oversold zone (preferably above 30).
3. **Entry Signals**:
- **Buy Signal**: Super Trend turns green, price closes above the Super Trend line, and RSI is below 70.
- **Sell Signal**: Super Trend turns red, price closes below the Super Trend line, and RSI is above 30.
4. **Exit Signals**:
- Close long positions when the Super Trend turns red or the RSI enters the overbought zone.
- Close short positions when the Super Trend turns green or the RSI enters the oversold zone.
#### Advantages and Considerations
- **Advantages**:
- Combines trend-following and momentum analysis for more robust signals.
- Helps filter out false signals by requiring confirmation from both indicators.
- **Considerations**:
- Like all trading strategies, it is not foolproof and can generate false signals.
- Best used in conjunction with other analysis techniques and proper risk management.
- Performance can vary across different market conditions and timeframes.
The Super Trend and RSI strategy is a versatile tool that can enhance trading decisions by providing clearer entry and exit points, helping traders capture significant market moves while avoiding potential pitfalls of relying on a single indicator.
Adaptive Trend Lines [MAMA and FAMA]Updated my previous algo on the Adaptive Trend lines, however I have added new functionalities and sorted out the settings.
You can now switch between normalized and non-normalized settings, the colors have also been updated and look much better.
The MAMA and FAMA
These indicators was originally developed by John F. Ehlers (Stocks & Commodities V. 19:10: MESA Adaptive Moving Averages). Everget wrote the initial functions for these in pine script. I have simply normalized the indicators and chosen to use the Laplace transformation instead of the hilbert transformation
How the Indicator Works:
The indicator employs a series of complex calculations, but we'll break it down into key steps to understand its functionality:
LaplaceTransform: Calculates the Laplace distribution for the given src input. The Laplace distribution is a continuous probability distribution, also known as the double exponential distribution. I use this because of the assymetrical return profile
MESA Period: The indicator calculates a MESA period, which represents the dominant cycle length in the price data. This period is continuously adjusted to adapt to market changes.
InPhase and Quadrature Components: The InPhase and Quadrature components are derived from the Hilbert Transform output. These components represent different aspects of the price's cyclical behavior.
Homodyne Discriminator: The Homodyne Discriminator is a phase-sensitive technique used to determine the phase and amplitude of a signal. It helps in detecting trend changes.
Alpha Calculation: Alpha represents the adaptive factor that adjusts the sensitivity of the indicator. It is based on the MESA period and the phase of the InPhase component. Alpha helps in dynamically adjusting the indicator's responsiveness to changes in market conditions.
MAMA and FAMA Calculation: The MAMA and FAMA values are calculated using the adaptive factor (alpha) and the input price data. These values are essentially adaptive moving averages that aim to capture the current trend more effectively than traditional moving averages.
But Omar, why would anyone want to use this?
The MAMA and FAMA lines offer benefits:
The indicator offers a distinct advantage over conventional moving averages due to its adaptive nature, which allows it to adjust to changing market conditions. This adaptability ensures that investors can stay on the right side of the trend, as the indicator becomes more responsive during trending periods and less sensitive in choppy or sideways markets.
One of the key strengths of this indicator lies in its ability to identify trends effectively by combining the MESA and MAMA techniques. By doing so, it efficiently filters out market noise, making it highly valuable for trend-following strategies. Investors can rely on this feature to gain clearer insights into the prevailing trends and make well-informed trading decisions.
This indicator is primarily suppoest to be used on the big timeframes to see which trend is prevailing, however I am not against someone using it on a timeframe below the 1D, just be careful if you are using this for modern portfolio theory, this is not suppoest to be a mid-term component, but rather a long term component that works well with proper use of detrended fluctuation analysis.
Dont hesitate to ask me if you have any questions
Again, I want to give credit to Everget and ChartPrime!
Code explanation as required by House Rules:
fastLimit = input.float(title='Fast Limit', step=0.01, defval=0.01, group = "Indicator Settings")
slowLimit = input.float(title='Slow Limit', step=0.01, defval=0.08, group = "Indicator Settings")
src = input(title='Source', defval=close, group = "Indicator Settings")
input.float: Used to create input fields for the user to set the fastLimit and slowLimit values.
input: General function to get user inputs, like the data source (close price) used for calculations.
norm_period = input.int(3, 'Normalization Period', 1, group = "Normalized Settings")
norm = input.bool(defval = true, title = "Use normalization", group = "Normalized Settings")
input.int: Creates an input field for the normalization period.
input.bool: Allows the user to toggle normalization on or off.
Color settings in the code:
col_up = input.color(#22ab94, group = "Color Settings")
col_dn = input.color(#f7525f, group = "Color Settings")
Constants and functions
var float PI = math.pi
laplace(src) =>
(0.5) * math.exp(-math.abs(src))
_computeComponent(src, mesaPeriodMult) =>
out = laplace(src) * mesaPeriodMult
out
_smoothComponent(src) =>
out = 0.2 * src + 0.8 * nz(src )
out
math.pi: Represents the mathematical constant π (pi).
laplace: A function that applies the Laplace transform to the source data.
_computeComponent: Computes a component of the data using the Laplace transform.
_smoothComponent: Smooths data by averaging the current value with the previous one (nz function is used to handle null values).
Alpha function:
_computeAlpha(src, fastLimit, slowLimit) =>
mesaPeriod = 0.0
mesaPeriodMult = 0.075 * nz(mesaPeriod ) + 0.54
...
alpha = math.max(fastLimit / deltaPhase, slowLimit)
out = alpha
out
_computeAlpha: Calculates the adaptive alpha value based on the fastLimit and slowLimit. This value is crucial for determining the MAMA and FAMA lines.
Calculating MAMA and FAMA:
mama = 0.0
mama := alpha * src + (1 - alpha) * nz(mama )
fama = 0.0
fama := alpha2 * mama + (1 - alpha2) * nz(fama )
Normalization:
lowest = ta.lowest(mama_fama_diff, norm_period)
highest = ta.highest(mama_fama_diff, norm_period)
normalized = (mama_fama_diff - lowest) / (highest - lowest) - 0.5
ta.lowest and ta.highest: Find the lowest and highest values of mama_fama_diff over the normalization period.
The oscillator is normalized to a range, making it easier to compare over different periods.
And finally, the plotting:
plot(norm == true ? normalized : na, style=plot.style_columns, color=col_wn, title = "mama_fama_diff Oscillator Normalized")
plot(norm == false ? mama_fama_diff : na, style=plot.style_columns, color=col_wnS, title = "mama_fama_diff Oscillator")
Example of Normalized settings:
Example for setup:
Try to make sure the lower timeframe follows the higher timeframe if you take a trade based on this indicator!
Advanced Fractal and Hurst IndicatorAdvanced Fractal and Hurst Indicator (AFHI)
Description:
The Advanced Fractal and Hurst Indicator (AFHI) is a custom technical analysis tool designed to identify market trends and potential reversals by leveraging the concepts of Fractal Dimension and the Hurst Exponent . These advanced mathematical concepts provide insights into the complexity and persistence of price movements, making this indicator a powerful addition to any trader's toolkit.
How It Works:
Fractal Dimension (FD) :
The Fractal Dimension measures the complexity of price movements. A higher Fractal Dimension indicates a more complex, choppy market, while a lower value suggests smoother trends.
The FD is calculated using the log difference of price movements over a specified length.
Hurst Exponent (HE) :
The Hurst Exponent indicates the tendency of a time series to either regress to the mean or cluster in a direction. Values below 0.5 indicate a tendency to revert to the mean (mean-reverting), while values above 0.5 suggest a trending market.
The HE is calculated using the rescaled range method, comparing the range of price movements to the standard deviation.
Composite Indicator :
The Composite Indicator combines the smoothed Fractal Dimension and Hurst Exponent to provide a single value indicating market conditions. This is done by normalizing the FD and HE values and combining them into one metric.
A positive Composite Indicator suggests an uptrend, while a negative value indicates a downtrend.
Smoothing :
Both FD and HE values are smoothed using a simple moving average to reduce noise and provide clearer signals.
Trend Confirmation :
A 50-period moving average (MA) is used to confirm the trend direction. The price being above the MA indicates an uptrend, while below the MA indicates a downtrend.
Background Shading :
The indicator pane is shaded green during uptrend conditions (positive Composite Indicator and price above MA) and red during downtrend conditions (negative Composite Indicator and price below MA).
How Traders Can Use It:
Identifying Trends :
Traders can use the AFHI to identify current market trends. The background shading in the indicator pane provides a visual cue for trend direction, with green indicating an uptrend and red indicating a downtrend.
Trend Confirmation :
The Composite Indicator line, plotted in purple, helps confirm the trend. Positive values suggest a strong uptrend, while negative values indicate a strong downtrend.
Entry and Exit Signals :
Traders can use the transitions of the Composite Indicator and the background shading to time their entry and exit points. For instance, a shift from red to green shading suggests a potential buy opportunity, while a shift from green to red suggests a potential sell opportunity.
Alerts :
The script includes alert conditions that can notify traders when the Composite Indicator signals a new trend direction. Alerts can be set up for both uptrends and downtrends, helping traders stay informed of key market changes.
Strategy Development :
By integrating AFHI into their trading strategies, traders can develop more robust systems that account for market complexity and persistence. The indicator can be used alongside other technical tools to enhance decision-making and improve trade accuracy.
Multi Timeframe Moving Average Convergence Divergence {DCAquant}Overview
The MTF MACD indicator provides a unique view of MACD (Moving Average Convergence Divergence) and Signal Line dynamics across various timeframes. It calculates the MACD and Signal Line for each selected timeframe and aggregates them for analysis.
Key Features
MACD Calculation
Utilizes standard MACD calculations based on user-defined parameters like fast length, slow length, and signal smoothing.
Determines the difference between the MACD and Signal Line to identify convergence or divergence.
Multiple Timeframe Analysis
Allows users to select up to six different timeframes for analysis, ranging from minutes to days, providing a holistic view of market trends.
Calculates MACD and Signal Line for each timeframe independently.
Aggregated Analysis
Combines MACD and Signal Line values from multiple timeframes to derive a consolidated view.
Optionally applies moving average smoothing to aggregated MACD and Signal Line values for better clarity.
Position Identification
Determines the trading position (Long, Short, or Neutral) based on the relationship between MACD and Signal Line.
Considers the proximity of MACD and Signal Line to identify potential trading opportunities.
Visual Representation
Plots MACD and Signal Line on the price chart for visual analysis.
Utilizes color-coded backgrounds to indicate trading conditions (Long, Short, or Neutral) for quick interpretation.
Dynamic Table Display
Displays trading position alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table.
Offers flexibility in table placement and size for user preference.
How to Use
Parameter Configuration
Adjust parameters like fast length, slow length, and signal smoothing to fine-tune MACD calculations.
Select desired timeframes for analysis based on trading preferences and market conditions.
Interpretation
Monitor the relationship between MACD and Signal Line on the price chart.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable insights.
Decision Making
Consider entering Long positions when MACD is above the Signal Line and vice versa for Short positions.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management
Combine MTF MACD analysis with risk management strategies to optimize trade entries and exits.
Set stop-loss and take-profit levels based on individual risk tolerance and market conditions.
Conclusion
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator offers a robust framework for traders to analyze market trends across multiple timeframes efficiently. By combining MACD insights from various time horizons and presenting them in a clear and actionable format, it empowers traders to make informed decisions and enhance their trading strategies.
Disclaimer
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator provided here is intended for educational and informational purposes only. Trading in financial markets involves risk, and past performance is not indicative of future results. The use of this indicator does not guarantee profits or prevent losses.
Please be aware that trading decisions should be made based on your own analysis, risk tolerance, and financial situation. It is essential to conduct thorough research and seek advice from qualified financial professionals before engaging in any trading activity.
The MTF MACD indicator is a tool designed to assist traders in analyzing market trends and identifying potential trading opportunities. However, it is not a substitute for sound judgment and prudent risk management.
By using this indicator, you acknowledge that you are solely responsible for your trading decisions, and you agree to indemnify and hold harmless the developer and distributor of this indicator from any losses, damages, or liabilities arising from its use.
Trading in financial markets carries inherent risks, and you should only trade with capital that you can afford to lose. Exercise caution and discretion when implementing trading strategies, and consider seeking independent financial advice if necessary.
Multi Timeframe Relative Strength Index {DCAquant}Overview
The Multi Timeframe Relative Strength Index (MTF RSI) is a powerful technical analysis tool designed to provide insights into market momentum and potential trend reversals across multiple timeframes. Leveraging the Relative Strength Index (RSI) formula, this indicator offers traders a comprehensive view of market sentiment and identifies overbought and oversold conditions.
Key Features
RSI Calculation:
Utilizes the standard RSI calculation formula to measure the magnitude of recent price changes and assess the strength of market trends.
Employs a user-defined length parameter to customize the sensitivity of the RSI calculation based on trading preferences.
Multiple Timeframe Analysis:
Allows traders to analyze RSI values across up to six different timeframes, ranging from minutes to days, providing a holistic perspective on market dynamics.
Calculates RSI values independently for each selected timeframe, enabling comparison and trend identification.
Threshold Levels:
Defines overbought and oversold levels to highlight potential reversal points in market trends.
Offers flexibility in adjusting threshold levels based on individual risk tolerance and trading strategies.
Neutral Zone:
Establishes upper and lower neutral thresholds to identify periods of consolidation or sideways movement in price.
Helps traders distinguish between trending and ranging market conditions for more accurate analysis.
Moving Average Smoothing:
Provides the option to apply moving average smoothing to aggregated RSI values for enhanced clarity and reduced noise.
Enables smoother visualization of RSI trends, facilitating easier interpretation for traders.
Visual Representation:
Plots the aggregated MTF RSI values on the price chart, allowing traders to visually assess market momentum and potential reversal points.
Utilizes color-coded backgrounds to indicate Long, Short, or Neutral conditions for quick identification.
Dynamic Table Display:
Displays trading signals alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table format.
Offers flexibility in table placement and size to accommodate user preferences.
How to Use:
Parameter Configuration:
Adjust the length parameter to fine-tune the sensitivity of the RSI calculation based on the desired timeframe and trading strategy.
Define overbought and oversold levels to identify potential reversal points in market trends.
Customize upper and lower neutral thresholds to differentiate between trending and ranging market conditions.
Interpretation:
Monitor the aggregated MTF RSI values plotted on the price chart for signals of overbought or oversold conditions.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable trading insights.
Trading Strategy:
Consider entering Long positions when the aggregated MTF RSI is above the upper neutral threshold, indicating potential bullish momentum.
Evaluate Short opportunities when the aggregated MTF RSI falls below the lower neutral threshold, signaling possible bearish momentum.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management:
Combine MTF RSI analysis with robust risk management strategies, including stop-loss and take-profit levels, to manage trading risks effectively.
Practice prudent risk management and trade within your risk tolerance to minimize potential losses.
Disclaimer
Trading in financial markets involves risk, and past performance is not indicative of future results. The use of the MTF RSI indicator does not guarantee profits or prevent losses. Traders should conduct their own analysis, exercise caution, and seek advice from qualified financial professionals before making trading decisions.
Market Slayer (i)Market Slayer (i)
This script is designed to provide insights into market trends and generate trading signals based on a combination of moving average crossovers and trend confirmation. It aims to assist traders in identifying potential entry and exit points in the market.
Input Parameters:
Trend Timeframe: Allows the user to specify the timeframe for trend analysis. Default is set to W (weekly).
Trend Value: Defines the sensitivity of the trend detection algorithm.
Short SMA Length: Length of the short-term Simple Moving Average (SMA).
Long SMA Length: Length of the long-term Simple Moving Average (SMA).
Bullish Color: Color representation for bullish signals.
Bearish Color: Color representation for bearish signals.
Take Profit Color: Color representation for take profit events.
Simple Moving Average (SMA) Logic:
Two SMAs are calculated based on the provided lengths: one short-term and one long-term.
Short-term SMA values are plotted with a semi-transparent bearish color.
Long-term SMA values are plotted with a semi-transparent bullish color.
Trend Logic:
The script employs a modified SSL (Schaff Trend Cycle) indicator to determine the trend direction.
Trend direction is determined based on whether the closing price is above or below the SSL (Schaff Trend Cycle) indicator.
Trend changes are detected by comparing the current trend direction with the previous two trend directions.
Signal Logic:
Buy signals are generated when the short-term SMA crosses above the long-term SMA and the trend is bullish.
Sell signals are generated when the short-term SMA crosses below the long-term SMA and the trend is bearish.
Signals are confirmed only if there is no open position.
Take Profit Logic:
Take profit events are triggered when the trend changes direction after a position has been opened.
Take profit events are confirmed only if there is an open position.
Alerts:
Various alerts are included to notify traders of different events such as signal generation, take profit opportunities, and trend changes.
Usage of lookahead:
Within the script, the lookahead argument is utilized in the request.security() function to control how much historical data should be loaded for trend analysis.
Setting lookahead=barmerge.lookahead_on enables the script to consider future price movements when calculating trend conditions.
This functionality can enhance the accuracy of trend detection by incorporating future bars into the analysis.
Usage:
Traders can use this script on the TradingView platform to visualize market trends, identify potential entry and exit points, and receive timely alerts for trading opportunities.
Investify360 ICT IndicatorThe Investify360 ICT Indicator is designed to follow the ICT (Inner Circle Trader) strategy. It provides essential buy and sell signals based on price movements relative to a simple moving average (SMA). The indicator is built to be beginner-friendly with clear labels and color-coded signals.
Key Features
Simple Moving Average (SMA):
The script calculates a simple moving average based on a user-defined period (length), defaulting to 14 periods. This moving average helps smooth out price data and identify trends.
Buy and Sell Signals:
Buy Signal: A buy signal is generated when the current price (src, defaulting to the close price) crosses above the SMA. This event is typically interpreted as a potential upward trend.
Sell Signal: A sell signal is generated when the current price crosses below the SMA. This event is often interpreted as a potential downward trend.
These signals are visually represented on the chart with up and down labels respectively.
Labels and Colors:
Buy Signal: Displayed with an up label (BUY) in green color.
Sell Signal: Displayed with a down label (SELL) in red color.
The colors for these signals can be customized through the script inputs (buyColor and sellColor).
Beginner-Friendly Labels:
To assist beginners, the script includes a label at the start of the chart indicating the position of the moving average line (MA Line). This label is shown on the first bar to clarify the purpose of the plotted line.
Plotting the Moving Average:
The SMA is plotted on the chart with a yellow line, making it easily distinguishable. The moving average line helps traders visualize the trend direction.
Grid TraderGrid Trader Indicator ( GTx ):
Overview
The Grid Trader Indicator is a tool that helps traders visualize key levels within a specified trading range. The indicator plots accumulation and distribution levels, an entry level, an exit level, and a midpoint. This guide will help you understand how to use the indicator and its features for effective grid trading.
Basics of Trading Range, Grid Buy, and Grid Sell
Trading Range
A trading range is the horizontal price movement between a defined upper ( resistance ) and lower ( support ) level over a period of time. When a security trades within a range, it repeatedly moves between these two levels without trending upwards or downwards significantly. Traders often use the trading range to identify potential buy and sell points:
Upper Level (Resistance): This is the price level at which selling pressure overcomes buying pressure, preventing the price from rising further.
Lower Level (Support): This is the price level at which buying pressure overcomes selling pressure, preventing the price from falling further.
Grid Trading Strategy
Grid trading is a type of trading strategy that involves placing buy and sell orders at predefined intervals around a set price. It aims to profit from the natural market volatility by buying low and selling high in a range-bound market. The strategy divides the trading range into several grid levels where orders are placed.
Grid Buy
Grid buy orders are placed at intervals below the current price . When the price drops to these levels, buy orders are triggered . This strategy ensures that the trader buys more as the price falls, potentially lowering the average purchase price .
Grid Sell
Grid sell orders are placed at intervals above the current price . When the price rises to these levels, sell orders are triggered . This ensures that the trader sells portions of their holdings as the price increases, potentially securing profits at higher levels .
Key Points of Grid Trading
Grid Size : The interval between each buy and sell order. This can be constant (e.g., $2 intervals) or variable based on certain conditions.
Accumulation Range : The lower part of the trading range where buy orders are placed.
Distribution Range : The upper part of the trading range where sell orders are placed.
Midpoint : The average price of the entry and exit levels, often used as a reference point for balance.
As the price moves up and down within this range, your buy orders will be triggered as the price drops and your sell orders will be triggered as the price rises. This allows you to accumulate more of the asset at lower prices and sell portions at higher prices, profiting from the price oscillations within the defined range. Grid trading can be particularly effective in a sideways market where there is no clear long-term trend. However, it requires careful monitoring and adjustment of grid levels based on market conditions to minimize risks and maximize returns .
Configuring the Indicator :
Once the indicator is added, you will see a settings icon next to it. Click on it to open the settings menu.
Adjust the Upper Level , Lower Level , Entry Level , and Exit Level to match your trading strategy and market conditions.
Set the Levels Visibility to control how many bars back the levels will be plotted.
Interpreting the Levels :
Accumulation Levels : These are plotted below the entry level and are potential buy zones. They are labeled as Accumulation Level 1, 2, and 3.
Distribution Levels : These are plotted above the exit level and are potential sell zones. They are labeled as Distribution Level 1, 2, and 3.
Upper Level : Marked in fuchsia, indicating the top boundary of the trading range.
Exit Level : Marked in yellow, indicating the level at which you plan to exit trades.
Midpoint : Marked in white, indicating the average of the entry and exit levels.
Entry Level : Marked in yellow, indicating the level at which you plan to enter trades.
Lower Level : Marked in aqua, indicating the bottom boundary of the trading range.
By visualizing key levels, you can make informed decisions on where to place buy and sell orders, potentially maximizing your trading profits through systematic grid trading.
Double Vegas SuperTrend Enhanced - Strategy [presentTrading]
█ Introduction and How It Is Different
The "Double Vegas SuperTrend Enhanced" strategy is a sophisticated trading system that combines two Vegas SuperTrend Enhanced. Very Powerful!
Let's celebrate the joy of Children's Day on June 1st! Enjoyyy!
BTCUSD LS performance
The strategy aims to pinpoint market trends with greater accuracy and generate trades that align with the overall market direction.
This approach differentiates itself by integrating volatility adjustments and leveraging the Vegas Channel's width to refine the SuperTrend calculations, resulting in a dynamic and responsive trading system.
Additionally, the strategy incorporates customizable take-profit and stop-loss levels, providing traders with a robust framework for risk management.
-> check Vegas SuperTrend Enhanced - Strategy
█ Strategy, How It Works: Detailed Explanation
🔶 Vegas Channel and SuperTrend Calculations
The strategy initiates by calculating the Vegas Channel, which is derived from a simple moving average (SMA) and the standard deviation (STD) of the closing prices over a specified window length. This channel helps in measuring market volatility and forms the basis for adjusting the SuperTrend indicator.
Vegas Channel Calculation:
- vegasMovingAverage = SMA(close, vegasWindow)
- vegasChannelStdDev = STD(close, vegasWindow)
- vegasChannelUpper = vegasMovingAverage + vegasChannelStdDev
- vegasChannelLower = vegasMovingAverage - vegasChannelStdDev
SuperTrend Multiplier Adjustment:
- channelVolatilityWidth = vegasChannelUpper - vegasChannelLower
- adjustedMultiplier = superTrendMultiplierBase + volatilityAdjustmentFactor * (channelVolatilityWidth / vegasMovingAverage)
The adjusted multiplier enhances the SuperTrend's sensitivity to market volatility, making it more adaptable to changing market conditions.
BTCUSD Local picture.
🔶 Average True Range (ATR) and SuperTrend Values
The ATR is computed over a specified period to measure market volatility. Using the ATR and the adjusted multiplier, the SuperTrend upper and lower levels are determined.
ATR Calculation:
- averageTrueRange = ATR(atrPeriod)
**SuperTrend Calculation:**
- superTrendUpper = hlc3 - (adjustedMultiplier * averageTrueRange)
- superTrendLower = hlc3 + (adjustedMultiplier * averageTrueRange)
The SuperTrend levels are continuously updated based on the previous values and the current market trend direction. The market trend is determined by comparing the closing prices with the SuperTrend levels.
Trend Direction:
- If close > superTrendLowerPrev, then marketTrend = 1 (bullish)
- If close < superTrendUpperPrev, then marketTrend = -1 (bearish)
🔶 Trade Entry and Exit Conditions
The strategy generates trade signals based on the alignment of both SuperTrends. Trades are executed only when both SuperTrends indicate the same market direction.
Entry Conditions:
- Long Position: Both SuperTrends must signal a bullish trend.
- Short Position: Both SuperTrends must signal a bearish trend.
Exit Conditions:
- Positions are exited if either SuperTrend reverses its trend direction.
- Additional conditions include holding periods and configurable take-profit and stop-loss levels.
█ Trade Direction
The strategy allows traders to specify the desired trade direction through a customizable input setting. Options include:
- Long: Only enter long positions.
- Short: Only enter short positions.
- Both: Enter both long and short positions based on the market conditions.
█ Usage
To utilize the "Double Vegas SuperTrend Enhanced" strategy, traders need to configure the input settings according to their trading preferences and market conditions. The strategy includes parameters for ATR periods, Vegas Channel window lengths, SuperTrend multipliers, volatility adjustment factors, and risk management settings such as hold days, take-profit, and stop-loss percentages.
█ Default Settings
The strategy comes with default settings that can be adjusted to fit individual trading styles:
- trade Direction: Both (allows trading in both long and short directions for maximum flexibility).
- ATR Periods: 10 for SuperTrend 1 and 5 for SuperTrend 2 (shorter ATR period results in more sensitivity to recent price movements).
- Vegas Window Lengths: 100 for SuperTrend 1 and 200 for SuperTrend 2 (longer window length results in smoother moving averages and less sensitivity to short-term volatility).
- SuperTrend Multipliers: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher multipliers lead to wider SuperTrend channels, reducing the frequency of trades).
- Volatility Adjustment Factors: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher adjustment factors increase the responsiveness to changes in market volatility).
- Hold Days: 5 (defines the minimum duration a position is held, ensuring trades are not exited prematurely).
- Take Profit: 30% (sets the target profit level to lock in gains).
- Stop Loss: 20% (sets the maximum acceptable loss level to mitigate risk).
Push and Exhaustion Strategy with VWAP and Moving AveragesOverview:
The Push and Exhaustion Strategy Indicator is a custom technical analysis tool designed to help traders identify potential market turning points by highlighting significant price movements (pushes) and subsequent periods of reduced momentum (exhaustion). This indicator also incorporates key moving averages (50-period and 200-period) and the Volume Weighted Average Price (VWAP) to provide additional context for trading decisions.
Components:
Push and Exhaustion Thresholds:
Push Threshold: Set at 1.5 by default. This means the price must increase by 50% or more compared to the previous close to signal a push.
Exhaustion Threshold: Set at 0.7 by default. This means the price must decrease by 30% or more compared to the previous close to signal exhaustion.
VWAP (Volume Weighted Average Price):
VWAP is plotted on the chart to provide an average price weighted by volume, giving insight into the true average price paid for an asset.
Moving Averages:
50-period Moving Average (MA): Plotted in blue, it helps identify the short-to-mid-term trend direction.
200-period Moving Average (MA): Plotted in orange, it helps identify the long-term trend direction.
How It Works:
Push Condition:
A push signal is generated when the current closing price is at least 1.5 times the previous closing price (pushThreshold).
Additionally, the closing price must be above the VWAP, indicating strong upward momentum.
When these conditions are met, a green triangle is plotted above the price bar.
Exhaustion Condition:
An exhaustion signal is generated when the current closing price is at most 0.7 times the previous closing price (exhaustionThreshold).
Additionally, the closing price must be below the VWAP, indicating weakened momentum and potential reversal.
When these conditions are met, a red triangle is plotted below the price bar.
Visualization:
The indicator plots green triangles above bars to indicate a push signal and red triangles below bars to indicate an exhaustion signal.
It also plots the 50-period and 200-period moving averages as blue and orange lines, respectively.
The VWAP is plotted as a purple line, showing the average price considering the trading volume.
Alerts:
The indicator includes optional alerts that notify the trader when a push or exhaustion signal is detected.
Usage:
Push Signals: Traders might use push signals to enter trades in the direction of strong momentum, typically buying in an uptrend.
Exhaustion Signals: Traders might use exhaustion signals to anticipate potential reversals, considering exiting positions or entering counter-trend trades.
Moving Averages: The 50-period and 200-period moving averages help provide context to the overall trend, aiding in decision-making.
VWAP: Being above or below the VWAP helps validate the strength of the price movement.
This indicator provides a comprehensive view of market momentum, aiding traders in making informed decisions by highlighting significant price moves and potential reversals within the context of prevailing trends.
Ichimoku Cloud w/ HelpersIchimoku Cloud w/ Helpers is your standard Ichimoku Cloud indicator with two additions.
Checkout TradingView's write up on the Ichimoku Cloud here .
The two additions added to this indicator are described below:
1 — A box is drawn centered on the current bar and stretching a length equal to the 'Senkou Span B Period'.
• The box encompasses the highest high and lowest low in that period.
2 — Two new lines are added.
• Green Line : Projection from the Lagging Line (Chikou Span) to the Span A line, indicating historical price action relative to future projected support/resistance.
• Red Line : Projection from the Kijun-sen (Base Line) to the Span B line, indicating medium-term trend direction relative to future projected support/resistance.
Use cases :
• The Box is simply a visual cue to draw your eye towards the area that the Ichimoku Cloud is currently attempting to analyze: Past, Present and Future.
• The green and red lines add a way to interpret the sentiment:
• Diverging Lines with Green Above Red --> Interpret as Bullish Sentiment
• Converging Lines with Green Crossing Above Red --> Interpret as Bullish reversal or strengthening
• Converging Lines with Green Crossing Below Red --> Interpret as Bearish reversal or weakening.
• Diverging Lines with Red Above Green --> Interpret as Bearish Sentiment
• Converging Lines with Red Crossing Below Green --> Interpret as Bullish reversal or weakening bearish trend.
Current limitations :
• Under settings -> Styles, the plotted lines don't allow the colors to be changed. A bug I'm trying to figure out.
Bugs?
Kindly report any issues you run into and I'll try to fix them promptly.
Thank you!
