Normalized Hull Moving Average Oscillator w/ ConfigurationsThis indicator uniquely uses normalization techniques applied to the Hull Moving Average (HMA) and allows the user to choose between a number of different types of normalization, each with their own advantages. This indicator is one in a series of experiments I've been working on in looking at different methods of transforming data. In particular, this is a more usable example of the power of data transformation, as it takes the Hull Moving Average of Alan Hull and turns it into a powerful oscillating indicator.
The indicator offers multiple types of normalization, each with its own set of benefits and drawbacks. My personal favorites are the Mean Normalization , which turns the data series into one centered around 0, and the Quantile Transformation , which converts the data into a data set that is normally distributed.
I've also included the option of showing the mean, median, and mode of the data over the period specified by the length of normalization. Using this will allow you to gather additional insights into how these transformations affect the distribution of the data series.
Types of Normalization:
1. Z-Score
Overview: Standardizes the data by subtracting the mean and dividing by the standard deviation.
Benefits: Centers the data around 0 with a standard deviation of 1, reducing the impact of outliers.
Disadvantages: Works best on data that is normally distributed
Notes: Best used with a mid-longer length of transformation.
2. Min-Max
Overview: Scales the data to fit within a specified range, typically 0 to 1.
Benefits: Simple and fast to compute, preserves the relationships among data points.
Disadvantages: Sensitive to outliers, which can skew the normalization.
Notes: Best used with mid-longer length of transformation.
3. Mean Normalization
Overview: Subtracts the mean and divides by the range (max - min).
Benefits: Centers data around 0, making it easier to compare different datasets.
Disadvantages: Can be affected by outliers, which influence the range.
Notes: Best used with a mid-longer length of transformation.
4. Max Abs Scaler
Overview: Scales each feature by its maximum absolute value.
Benefits: Retains sparsity and is robust to large outliers.
Disadvantages: Only shifts data to the range , which might not always be desirable.
Notes: Best used with a mid-longer length of transformation.
5. Robust Scaler
Overview: Uses the median and the interquartile range for scaling.
Benefits: Robust to outliers, does not shift data as much as other methods.
Disadvantages: May not perform well with small datasets.
Notes: Best used with a longer length of transformation.
6. Feature Scaling to Unit Norm
Overview: Scales data such that the norm (magnitude) of each feature is 1.
Benefits: Useful for models that rely on the magnitude of feature vectors.
Disadvantages: Sensitive to outliers, which can disproportionately affect the norm. Not normally used in this context, though it provides some interesting transformations.
Notes: Best used with a shorter length of transformation.
7. Logistic Function
Overview: Applies the logistic function to squash data into the range .
Benefits: Smoothly compresses extreme values, handling skewed distributions well.
Disadvantages: May not preserve the relative distances between data points as effectively.
Notes: Best used with a shorter length of transformation. This feature is actually two layered, we first put it through the mean normalization to ensure that it's generally centered around 0.
8. Quantile Transformation
Overview: Maps data to a uniform or normal distribution using quantiles.
Benefits: Makes data follow a specified distribution, useful for non-linear scaling.
Disadvantages: Can distort relationships between features, computationally expensive.
Notes: Best used with a very long length of transformation.
Conclusion
This indicator is a powerful example into how normalization can alter and improve the usability of a data series. Each method offers unique insights and benefits, making this indicator a useful tool for any trader. Try it out, and don't hesitate to reach out if you notice any glaring flaws in the script, room for improvement, or if you just have questions.
Moving Averages
No Lag SupertrendNo Lag Supertrend indicator improves upon the original supertrend by incorporating calculation methods that enhance responsiveness and accuracy. Traditional supertrend indicators often suffer from lag, which can delay signals and affect trading decisions. No Lag Supertrend addresses this issue through the use of KAMA (Kaufman’s Adaptive Moving Average) and Hull ATR (Average True Range) calculations.
Goals of No Lag Supertrend:
- Lag reduction: one of the main issues with traditional supertrend indicators is their lag, which can result in delayed entry and exit signals. By integrating KAMA and Hull ATR, the no lag supertrend minimizes this delay, providing more timely signals.
- Market Noise Filtering: The combined use of KAMA and Hull ATR effectively filters out market noise, ensuring that signals are based on significant price movements rather than minor fluctuations.
- Consistency Across Different Market Conditions: The adaptive nature of KAMA and the smooth responsiveness of Hull ATR ensure that the No Lag Supertrend performs consistently across various market conditions, from trending to volatile markets.
Credits: This code is based on the TradingView supertrend but improved the ATR calculations.
Perfect Order Alert USDJPY/BTCUSD/XAUUSDPerfect Order Alert USDJPY/BTCUSD/XAUUSD 日本語解説は下記
This indicator detects the perfect order of three moving averages and displays on the Panel in an easy-to-understand visual manner whether there is an uptrend, downtrend, or non-trend for each time leg.
This indicator detects perfect orders for the three currency pairs USDJPY/BTCUSD/XAUUSD on the 5-minute, 15-minute, 1-hour, and 4-hour time frames, and displays them on the Panel on the chart, with “▲” for up, “▼” for down, and “ー” for non-trend, so that you can quickly determine the trend. The panel is displayed on the chart.
In order to check for perfect orders without missing them, it is also possible to set up alerts that notify you of all the time frames and currency pairs as well.
Functions
Displaying 4H, 1H, 15M, 5M, up (▲), down (▼), other (-), of USDJPY/BTCUSD/XAUUSD on the panel.
*(By default, 20EMA, 75EMA, and 200EMA are hidden.)
Display position setting of the panel (You can choose from upper left, upper top, upper right, lower left, lower bottom, or lower right).
Panel color and text color change function
The moving average line can be hidden by default.
Moving average period change
Moving average color and thickness can be changed.
EMA/SMA switchable
Alert function - One alert can be set for each currency pair and time frame ▲▼, which is very useful.
Perfect Order Alert
You can use it even if you have a free account with only one alert setting.
To use the alert function, go to the Tradingview default alert settings, select “USDJPY/BTCUSD/XAUUSD” for the top item of conditions, and select “Call Alert() function” in the frame just below it!
_* Supplementary explanation: ＿＿＿＿＿＿＿＿＿＿＿＿
Please note that due to the limitation of the script, only 3 currency pairs and 4 time frames are displayed with 12 items (Panels for currency pairs other than USDJPY/BTCUSD/XAUUSD are also created, but they are indicators for other scripts, so if you are interested in other currency pairs, please use those. If you are interested in other currency pairs, please use them.)
Please note that we may change the functions or delete the indicator itself without prior notice.
Translated with DeepL.com (free version)
Reference image of the setting screenReference image of the setting screen
設定画面参考画像
3本の移動平均線のパーフェクトオーダーを検知し、時間足ごとに上昇トレンドか下降トレンドかノントレンドかを視覚的にわかりやすくPanelに表示するインジゲーターです。
このインジゲーターは、USDJPY/BTCUSD/XAUUSDの３通貨ペアの５分足、15分足、１時間足、４時間足のパーフェクトオーダーを検知して、チャートに表示されるPanelに、上昇は「▲」下降は「▼」ノントレンドは「ー」と、すぐに判断できる表示にしてあります。
パーフェクトオーダーを逃さずチェックできるように、それぞれの時間足や通貨ペアも全てを通知してくれるアラート設定が可能なのも特徴です。
機能紹介
・USDJPY/BTCUSD/XAUUSDの4H,1H,15M,5M,の上昇(▲),下降(▼),その他(-),をパネルに表示
※(デフォルトでは20EMA,75EMA,200EMAの３本で非表示にしてあります）
・パネルの表示位置設定（左上、上、右上、左下、下、右下、から選択できます。）
・パネルの色とテキスト色変更機能
・移動平均線表示非表示機能（デフォルトでは表示OFFにしてあります。）
・移動平均線期間変更
・移動平均線色と太さ変更
・EMA/SMA切り替え可能
・アラート機能ー１つのアラート設定で通貨ペアと時間足▲▼一つ一つを細かく教えてくれるので便利。
※パーフェクト オーダーアラート
無料アカウントで１つしかアラート設定できなくても使えます。
アラート機能はTradingviewデフォルトのアラート設定から、条件の一番上の項目を「USDJPY/BTCUSD/XAUUSD」選択、そのすぐ下の枠に「Alert()関数の呼び出し」を選択でOK！
＿※ 補足説明＿＿＿＿＿＿＿＿＿＿＿＿
・スクリプトの制限の為、３通貨ペアと４つの時間足の１２項目で表示させていますのでご了承ください
(USDJPY/BTCUSD/XAUUSD以外の通貨ペアのPanelも作成していますが別スクリプトのインジゲーターになりますので他の通貨ペアも興味がある方はそちらをお使いください）
・予告なしで機能の変更やインジゲーター自体の削除等行う事もあるかもなのでご了承ください。
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin.
Features:
SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length.
BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length.
BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies.
BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets.
Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making.
Inputs:
SOL Ticker: Symbol for Solana (default: BINANCE
).
BTC Ticker: Symbol for Bitcoin (default: BINANCE
).
BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP
.D).
EMA Length: The length of the EMA (default: 20 periods).
Usage:
This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC.
Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
Trend DetectorThe Trend Detector indicator is a powerful tool to help traders identify and visualize market trends with ease. This indicator uses multiple moving averages (MAs) of different timeframes to provide a comprehensive view of market trends, making it suitable for traders of all experience levels.
█ USAGE
This indicator will automatically plot the chosen moving averages (MAs) on your chart, allowing you to visually assess the trend direction. Additionally, a table displaying the trend data for each selected MA timeframe is included to provide a quick overview.
█ FEATURES
1. Customizable Moving Averages: The indicator supports various types of moving averages, including Simple (SMA) , Exponential (EMA) , Smoothed (RMA) , Weighted (WMA) , and Volume-Weighted (VWMA) . You can select the type and length for each MA.
2. Multiple Timeframes: Plot moving averages for different timeframes on a single chart, including fast (short-term) , mid (medium-term) , and slow (long-term) MAs.
3. Trend Detector Table: A customizable table displays the trend direction (Up or Down) for each selected MA timeframe, providing a quick and easy way to assess the market's overall trend.
4. Customizable Appearance: Adjust the colors, frame, border, and text of the Trend Detector Table to match your chart's style and preferences.
5. Wait for Timeframe Close: Option to wait until the selected timeframe closes to plot the MA, which will remove the gaps.
█ CONCLUSION
The Trend Detector indicator is a versatile and user-friendly tool designed to enhance your trading strategy. By providing a clear visualization of market trends across multiple timeframes, this indicator helps you make informed trading decisions with confidence and trade with the market trend. Whether you're a day trader or a long-term investor, this indicator is an essential addition to your trading toolkit.
█ IMPORTANT
This indicator is a tool to aid in your analysis and should not be used as the sole basis for trading decisions. It is recommended to use this indicator in conjunction with other tools and perform comprehensive market analysis before making any trades.
Happy trading!
T3 [RATE OF CHANGE] by SKiNNiEHDeveloped by Tim Tillson, the Tilson Moving Average (T3) is a trend indicator with the advantage of having less lag than other ones. That is, a faster moving average. The T3 moving average is an "indicator of an indicator" as it includes several EMAs of another EMA. Unlike other moving averages, the t3 adds the so-called volume factor, a value between 0 and 1.
The T3 RATE OF CHANGE by SKiNNiEH is a unique indicator that integrates the T3 moving average with a normalized Rate of Change (RoC) calculation. Unlike traditional T3 moving averages, this indicator provides additional smoothing modes (SINGLE, DOUBLE & TRIPLE) for the T3, whilst enhancing visual feedback of the plotted line by generating a dynamic line thickness, a dynamic line color & brightness and trade entry bars, offering traders a more dynamic view of market conditions without going "overboard" with settings.
How It Works
Visualization
The T3 line varies in thickness and color based on the RoC values, giving traders visual cues about market strength and direction.
Thicker and brighter lines indicate stronger trends, while thinner and duller lines suggest weaker trends.
Rate of Change Filte r
This filter refines trend detection by using the line thickness measurement.
Adjustable from 0 (disabled) to 4, where higher settings only consider stronger trends for signals.
The T3 line turns gray when the filter is triggered or when the RoC is extremely low, signaling a weak or neutral market.
T3 Calculation (mode)
SINGLE
The T3 calculation is applied once to the closing price.
This mode has the least smoothing effect and the least lag. It reacts more quickly to price changes but is less smooth.
DOUBLE
The T3 calculation is applied twice sequentially.
The first T3 calculation smooths the closing price.
The second T3 calculation smooths the result of the first T3 calculation.
This mode provides more smoothing and introduces more lag compared to SINGLE mode. It is smoother but reacts slower to price changes.
TRIPLE
The T3 calculation is applied three times sequentially.
The first T3 calculation smooths the closing price.
The second T3 calculation smooths the result of the first T3 calculation.
The third T3 calculation smooths the result of the second T3 calculation.
This mode provides the most smoothing and introduces the most lag by reacting the slowest to price changes.
Rate of Change (RoC) Calculation
The script calculates the Rate of Change (RoC) for the T3 values based on the selected mode (SINGLE, DOUBLE, TRIPLE). The RoC measures the percentage change between the most recent value and a value in the past. The measurement is then normalized in three different ranges.
Normalization 5: Determines T3 line thickness on a scale from 0 - 5
Normalization 10: Determines T3 color brightness on a scale from 0 - 10
Normalization 100: Determines Rate of Change percentage
Rate of Change Filter
The script uses the RoC filter to refine the trend detection logic. By using the line thickness measurement, a filter can be enabled by setting this input on 1 - 4. As an example, setting this to 4 means that only a line thickness of 5 would be considered for a trade signal. Setting this to 0 disables the filter. The T3 line will turn gray when the filter is triggered, the T3 line can also turn gray without the filter, when the Rate of Change is extremely low.
Trade Signals
A trade signal is printed as a vertical green or red bar when the following conditions are met:
Long:
Closing price is above the T3 line
Rate of Change percentage is above 0
Previous trade signal was a short signal **
Rate of Change is not filtered
Short:
Closing price is below the T3 line
Rate of Change percentage is below 0
Previous trade signal was a long signal **
Rate of Change is not filtered
** Or this is the very first recorded trade signal
It should be noted that the trade signals in this script are trade entry signals, not trade exit signals. Use at your own risk.
Instructions for Use
Setting Up the Indicator
Apply the indicator to your trading chart.
Choose the desired T3 mode (SINGLE, DOUBLE, TRIPLE) based on your need for smoothing and lag.
Set the desired length (lookback period).
Set the desired factor between 0 and 1 (increments of 0.1)
Choose an overall line thickness and brightness that suits your screen and taste preferences.
Apply the Rate of Change filter. Setting this to 0 will disable the filter
Tip: use the trade entry vertical bars as a visual calibration tool the adjust mode, length, factor and filter.
Interpreting Visual Cues
Observe the T3 line's thickness: thicker lines indicate stronger trends, while thinner lines suggest weaker trends.
Observe the T3 line's color and color brightness: green indicates a more bullish trend, while red indicates a more bearish trend. A brighter color suggest a stronger trend. A gray color means the RoC is very low / neutral, or the RoC filter is active.
Observe the T3 line's location relative to price: below price indicates a more bullish trend, above price indicates a more bearish trend. The T3 line distance from price can also be an indication of trend strength.
Observe vertical bars: a vertical bar is printed green when long conditions are met, a vertical bar is printed red when short conditions are met. See the rules that explain the trigger for this bar above.
Alerts
Go to the settings tab, set the condition to T3.RoC.S + LONG or SHORT.
Enter an alert name and message.
Configure your notification preferences in the notifications tab and create the alert
Notifications-tab: Choose your notification preferences
Create the alert.
EMA Cross Fibonacci Entry with RetracementThe EMA Cross Fibonacci Entry with Retracement is a trading strategy that combines two popular technical analysis tools: Exponential Moving Averages (EMAs) and Fibonacci retracement levels. Here's a brief overview of how this strategy typically works:
### Exponential Moving Averages (EMAs)
1. **EMAs Calculation**: EMAs give more weight to recent price data, making them more responsive to price changes. Commonly used periods for EMAs in this strategy are the 50-period and 200-period EMAs.
2. **EMA Cross**: The strategy looks for a "golden cross" (short-term EMA crosses above the long-term EMA) as a potential buy signal, and a "death cross" (short-term EMA crosses below the long-term EMA) as a potential sell signal.
### Fibonacci Retracement Levels
1. **Fibonacci Retracement**: This tool is used to identify potential support and resistance levels based on the Fibonacci sequence. The key retracement levels are 23.6%, 38.2%, 50%, 61.8%, and 78.6%.
2. **Drawing Retracement Levels**: Traders draw Fibonacci retracement levels from a significant peak to a significant trough (or vice versa) to identify potential retracement levels where the price might reverse.
### Combining EMA Cross with Fibonacci Retracement
1. **Identify EMA Cross**: First, traders look for an EMA cross. For example, a golden cross where a shorter EMA (e.g., 50 EMA) crosses above a longer EMA (e.g., 200 EMA) suggests a bullish trend.
2. **Wait for Retracement**: After identifying a cross, traders wait for the price to retrace to a Fibonacci level. The key levels to watch are 38.2%, 50%, and 61.8%.
3. **Entry Point**: The entry point is when the price retraces to a Fibonacci level and shows signs of reversal (e.g., bullish candlestick patterns, support at Fibonacci levels). This is typically when traders enter a long position.
4. **Confirmation with EMA**: Ensure that the EMAs support the trend. For a buy entry, the short-term EMA should remain above the long-term EMA.
### Example of a Bullish Entry
1. **Golden Cross**: 50 EMA crosses above 200 EMA.
2. **Retracement**: Price retraces to the 38.2% Fibonacci level.
3. **Entry Signal**: At the 38.2% level, a bullish candlestick pattern (e.g., hammer) forms, indicating potential support.
4. **Entry Point**: Enter a long position at the close of the bullish candlestick.
### Risk Management
1. **Stop Loss**: Place a stop loss below the next Fibonacci retracement level or below the recent swing low to limit potential losses.
2. **Take Profit**: Set a take profit target based on a risk-reward ratio, previous resistance levels, or further Fibonacci extensions.
### Conclusion
The EMA Cross Fibonacci Entry with Retracement strategy is a systematic approach to identifying entry points in a trending market. By combining the responsiveness of EMAs with the predictive power of Fibonacci retracement levels, traders aim to enter trades at optimal points, increasing their chances of success while managing risk effectively.
Multiple Non-Linear Regression [ChartPrime]This indicator is designed to perform multiple non-linear regression analysis using four independent variables: close, open, high, and low prices. Here's a breakdown of its components and functionalities:
Inputs:
Users can adjust several parameters:
Normalization Data Length: Length of data used for normalization.
Learning Rate: Rate at which the algorithm learns from errors.
Smooth?: Option to smooth the output.
Smooth Length: Length of smoothing if enabled.
Define start coefficients: Initial coefficients for the regression equation.
Data Normalization:
The script normalizes input data to a range between 0 and 1 using the highest and lowest values within a specified length.
Non-linear Regression:
It calculates the regression equation using the input coefficients and normalized data. The equation used is a weighted sum of the independent variables, with coefficients adjusted iteratively using gradient descent to minimize errors.
Error Calculation:
The script computes the error between the actual and predicted values.
Gradient Descent: The coefficients are updated iteratively using gradient descent to minimize the error.
// Compute the predicted values using the non-linear regression function
predictedValues = nonLinearRegression(x_1, x_2, x_3, x_4, b1, b2, b3, b4)
// Compute the error
error = errorModule(initial_val, predictedValues)
// Update the coefficients using gradient descent
b1 := b1 - (learningRate * (error * x_1))
b2 := b2 - (learningRate * (error * x_2))
b3 := b3 - (learningRate * (error * x_3))
b4 := b4 - (learningRate * (error * x_4))
Visualization:
Plotting of normalized input data (close, open, high, low).
The indicator provides visualization of normalized data values (close, open, high, low) in the form of circular markers on the chart, allowing users to easily observe the relative positions of these values in relation to each other and the regression line.
Plotting of the regression line.
Color gradient on the regression line based on its value and bar colors.
Display of normalized input data and predicted value in a table.
Signals for crossovers with a midline (0.5).
Interpretation:
Users can interpret the regression line and its crossovers with the midline (0.5) as signals for potential buy or sell opportunities.
This indicator helps users analyze the relationship between multiple variables and make trading decisions based on the regression analysis. Adjusting the coefficients and parameters can fine-tune the model's performance according to specific market conditions.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
-----
MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
-----
(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
Moving avg with regMoving avg with reg
A Moving avg with reg is a series of moving averages plotted on the same chart, each with different time periods. This visual tool helps traders identify the underlying trend and potential reversal points in the market. By observing the interaction and spacing between the moving averages, traders can gauge the market's strength and momentum.
Key Points:
Trend Identification: Multiple moving averages help confirm the direction of the trend. If the shorter-period moving averages are above the longer-period ones, it indicates an uptrend, and vice versa.
Reversal Signals: When shorter-period moving averages cross longer-period ones, it may signal a potential trend reversal.
Market Strength: The spacing between the moving averages indicates the strength of the trend. Wider spacing suggests a strong trend, while narrow spacing may indicate a weakening trend.
Regression Line
A Regression Line, specifically the Linear Regression Indicator (LRI), is a statistical tool used to determine the direction and strength of a trend by fitting a straight line to the price data over a specified period. This line minimizes the distance between itself and the actual price points, providing a clear visual representation of the trend.
Key Points:
Trend Direction: The slope of the regression line indicates the direction of the trend. A positive slope suggests an uptrend, while a negative slope indicates a downtrend.
Price Deviations: The distance between the actual price and the regression line can highlight overbought or oversold conditions. Large deviations may suggest a potential correction.
Predictive Power: By extending the regression line, traders can make predictions about future price movements based on the current trend.
Stochastic Biquad Band Pass FilterThis indicator combines the power of a biquad band pass filter with the popular stochastic oscillator to provide a unique tool for analyzing price movements.
The Filter Length parameter determines the center frequency of the biquad band pass filter, affecting which frequency band is isolated. Adjusting this parameter allows you to focus on different parts of the price movement spectrum.
The Bandwidth (BW) controls the width of the frequency band in octaves. It represents the bandwidth between -3 dB frequencies for the band pass filter. A narrower bandwidth results in a more focused filtering effect, isolating a tighter range of frequencies.
The %K Length parameter sets the period for the stochastic calculation, determining the range over which the stochastic values are calculated.
The %K Smoothing parameter applies a simple moving average to the %K values to smooth out the oscillator line.
The %D Length parameter sets the period for the %D line, which is a simple moving average of the %K line, providing a signal line for the oscillator.
Key Features of the Stochastic Biquad Band Pass Filter
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. In this implementation, the biquad filter is configured as a band pass filter, which allows frequencies within a specified band to pass while attenuating frequencies outside this band. This is particularly useful in trading to isolate specific price movements, making it easier to detect patterns and trends within a targeted frequency range.
The stochastic oscillator is a popular momentum indicator that shows the location of the close relative to the high-low range over a set number of periods. Combining it with a biquad band pass filter enhances its effectiveness by focusing on specific frequency bands of price movements.
By incorporating this stochastic biquad band pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into specific frequency bands of price movements, leading to more informed trading decisions.
Biquad Band Pass FilterThis indicator utilizes a biquad band pass filter to isolate and highlight a specific frequency band in price data, helping traders focus on price movements within a targeted frequency range.
The Length parameter determines the center frequency of the filter, affecting which frequency band is isolated. Adjusting this parameter allows you to focus on different parts of the price movement spectrum.
The Bandwidth (BW) controls the width of the frequency band in octaves. It represents the bandwidth between -3 dB frequencies for the band pass filter. A narrower bandwidth results in a more focused filtering effect, isolating a tighter range of frequencies.
Key Features of Biquad Filters
Biquad filters are a type of digital filter that provides a combination of low-pass, high-pass, band-pass, and notch filtering capabilities. In this implementation, the biquad filter is configured as a band pass filter, which allows frequencies within a specified band to pass while attenuating frequencies outside this band. This is particularly useful in trading to isolate specific price movements, making it easier to detect patterns and trends within a targeted frequency range.
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. The customizable length and bandwidth allow for flexible adaptation to different trading strategies and market conditions. Designed for real-time charting, the biquad filter operates efficiently without significant lag, ensuring timely analysis.
By incorporating this biquad band pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into specific frequency bands of price movements, leading to more informed trading decisions.
Biquad High Pass FilterThis indicator utilizes a biquad high pass filter to filter out low-frequency components from price data, helping traders focus on high-frequency movements and detect rapid changes in trends.
The Length parameter determines the cutoff frequency of the filter, affecting how quickly the filter responds to changes in price. A shorter length allows the filter to react more quickly to high-frequency movements.
The Q Factor controls the sharpness of the filter. A higher Q value results in a more precise filtering effect by narrowing the frequency band. However, be cautious when setting the Q factor too high, as it can induce resonance, amplifying certain frequencies and potentially making the filter less effective by introducing unwanted noise.
Key Features of Biquad Filters
Biquad filters are a type of digital filter that provides a combination of low-pass, high-pass, band-pass, and notch filtering capabilities. In this implementation, the biquad filter is configured as a high pass filter, which allows high-frequency signals to pass while attenuating lower-frequency components. This is particularly useful in trading to highlight rapid price movements, making it easier to spot short-term trends and patterns.
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. The customizable length and Q factor allow for flexible adaptation to different trading strategies and market conditions. Designed for real-time charting, the biquad filter operates efficiently without significant lag, ensuring timely analysis.
By incorporating this biquad high pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into rapid price movements, leading to more informed trading decisions.
Biquad Low Pass FilterThis indicator utilizes a biquad low pass filter to smooth out price data, helping traders identify trends and reduce noise in their analysis.
The Length parameter acts as the length of the moving average, determining the smoothness and responsiveness of the filter. Adjusting this parameter changes how quickly the filter reacts to price changes.
The Q Factor controls the sharpness of the filter. A higher Q value results in a narrower frequency band, enhancing the precision of the filter. However, be cautious when setting the Q factor too high, as it can induce resonance, amplifying certain frequencies and potentially making the filter less effective by introducing noise.
Key Features of Biquad Filters
Biquad filters are a type of digital filter that provides a combination of low-pass, high-pass, band-pass, and notch filtering capabilities. In this implementation, the biquad filter is configured as a low pass filter, which allows low-frequency signals to pass while attenuating higher-frequency noise. This is particularly useful in trading to smooth out price data, making it easier to spot underlying trends and patterns.
Biquad filters are known for their smooth response and minimal phase distortion, making them ideal for technical analysis. The customizable length and Q factor allow for flexible adaptation to different trading strategies and market conditions. Designed for real-time charting, the biquad filter operates efficiently without significant lag, ensuring timely analysis.
By incorporating this biquad low pass filter into your trading toolkit, you can enhance your chart analysis with clearer insights into price movements, leading to more informed trading decisions.
Strategy SEMA SDI WebhookPurpose of the Code:
The strategy utilizes Exponential Moving Averages (EMA) and Smoothed Directional Indicators (SDI) to generate buy and sell signals. It includes features like leverage, take profit, stop loss, and trailing stops. The strategy is intended for backtesting and automating trades based on the specified indicators and conditions.
Key Components and Functionalities:
1.Strategy Settings:
Overlay: The strategy will overlay on the price chart.
Slippage: Set to 1.
Commission Value: Set to 0.035.
Default Quantity Type: Percent of equity.
Default Quantity Value: 50% of equity.
Initial Capital: Set to 1000 units.
Calculation on Order Fills: Enabled.
Process Orders on Close: Enabled.
2.Date and Time Filters:
Inputs for enabling/disabling start and end dates.
Filters to execute strategy only within specified date range.
3.Leverage and Quantity:
Leverage: Adjustable leverage input (default 3).
USD Percentage: Adjustable percentage of equity to use for trades (default 50%).
Initial Capital: Calculated based on leverage and percentage of equity.
4.Take Profit, Stop Loss, and Trailing Stop:
Inputs for enabling/disabling take profit, stop loss, and trailing stop.
Adjustable parameters for take profit percentage (default 25%), stop loss percentage (default 4.8%), and trailing stop percentage (default 1.9%).
Calculations for take profit, stop loss, trailing price, and maximum profit tracking.
5.EMA Calculations:
Fast and slow EMAs.
Smoothed versions of the fast and slow EMAs.
6.SDI Calculations:
Directional movement calculation for positive and negative directional indicators.
Difference between the positive and negative directional indicators, smoothed.
7.Buy/Sell Conditions:
Long (Buy) Condition: Positive DI is greater than negative DI, and fast EMA is greater than slow EMA.
Short (Sell) Condition: Negative DI is greater than positive DI, and fast EMA is less than slow EMA.
8.Strategy Execution:
If buy conditions are met, close any short positions and enter a long position.
If sell conditions are met, close any long positions and enter a short position.
Exit conditions for long and short positions based on take profit, stop loss, and trailing stop levels.
Close all positions if outside the specified date range.
Usage:
This strategy is used to automate trading based on the specified conditions involving EMAs and SDI. It allows backtesting to evaluate performance based on historical data. The strategy includes risk management through take profit, stop loss, and trailing stops to protect gains and limit losses. Traders can customize the parameters to fit their specific trading preferences and risk tolerance. Differently, it can perform leverage analysis and use it as a template.
By using this strategy, traders can systematically execute trades based on technical indicators, helping to remove emotional bias and improve consistency in trading decisions.
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Internal Bar Strength IBS [Anan]This indicator calculates and displays the Internal Bar Strength (IBS) along with its moving average. The IBS is a measure that represents where the closing price is relative to the high-low range of a given period.
█ Main Formula
The core of this indicator is the Internal Bar Strength (IBS) calculation. The basic IBS formula is:
ibs = (close - low) / (high - low)
I enhanced the original formula by incorporating a user-defined length parameter. This modification allows for greater flexibility in analysis and interpretation. The extended version enables users to adjust the indicator's length according to their specific needs or market conditions. Notably, setting the length parameter to 1 reproduces the behavior of the original formula, maintaining backward compatibility while offering expanded functionality:
ibs = (close - ta.lowest(low, ibs_length)) / (ta.highest(high, ibs_length) - ta.lowest(low, ibs_length))
Where:
- `close` is the closing price of the current bar
- `lowest low` is the lowest low price over the specified IBS length
- `highest high` is the highest high price over the specified IBS length
█ Key Features
- Calculates IBS using a user-defined length
- Applies a moving average to the IBS values
- Offers multiple moving average types
- Includes optional Bollinger Bands or Donchian Channel overlays
- Visualizes bull and bear areas
█ Inputs
- IBS Length: The period used for IBS calculation
- MA Type: The type of moving average applied to IBS (options: SMA, EMA, SMMA, WMA, VWMA, Bollinger Bands, Donchian)
- MA Length: The period used for the moving average calculation
- BB StdDev: Standard deviation multiplier for Bollinger Bands
█ How to Use and Interpret
1. IBS Line Interpretation:
- IBS values range from 0 to 1
- Values close to 1 indicate the close was near the high, suggesting a bullish sentiment
- Values close to 0 indicate the close was near the low, suggesting a bearish sentiment
- Values around 0.5 suggest the close was near the middle of the range
2. Overbought/Oversold Conditions:
- IBS values above 0.8 (teal zone) may indicate overbought conditions
- IBS values below 0.2 (red zone) may indicate oversold conditions
- These zones can be used to identify potential reversal points
3. Trend Identification:
- Consistent IBS values above 0.5 may indicate an uptrend
- Consistent IBS values below 0.5 may indicate a downtrend
4. Using Moving Averages:
- The yellow MA line can help smooth out IBS fluctuations
- Crossovers between the IBS and its MA can signal potential trend changes
5. Bollinger Bands/Donchian Channel:
- When enabled, these can provide additional context for overbought/oversold conditions
- IBS touching or exceeding the upper band may indicate overbought conditions
- IBS touching or falling below the lower band may indicate oversold conditions
Remember that no single indicator should be used in isolation. Always combine IBS analysis with other technical indicators, price action analysis, and broader market context for more reliable trading decisions.
SD Distance Mean BetaThe "SD Distance Mean Indicator" is a currently a developing tool designed to enhance trading precision by dynamically adjusting to market conditions. This indicator provides insights into price deviations from the mean, helping traders make inf OANDA:XAUUSD ormed decisions based on significant price movements.
Key Features:
Adaptive Length Adjustment:
The indicator dynamically adjusts the calculation period based on the Average True Range (ATR). This allows it to respond to different market conditions, using a shorter length during consolidations and a longer length during trends.
Standardized Distance Calculation:
The indicator calculates the distance of the current price from the mean and standardizes it using the standard deviation. This standardized distance is then smoothed to reduce noise and provide clearer signals.
Dynamic Standard Deviation (SD) Levels:
SD levels are adjusted dynamically based on ATR, providing a more accurate representation of price volatility. These levels are further smoothed to minimize wiggling on shorter timeframes like the 30-minute chart.
Visual Cues for Trading Signals:
The indicator plots multiple SD levels (+1, +2, +3, +4 and their negatives) and highlights significant price movements. When the standardized distance line hits or exceeds these levels, it signals potential overbought or oversold conditions.
Customizable Smoothing: The smoothing length for both the standardized distance and SD levels can be customized to suit different trading strategies and timeframes. Default values are set to provide a balance between responsiveness and stability.
Usage:
Identifying Reversals : The indicator helps in spotting potential reversal points. When the smoothed standardized distance line hits +2 SD or -2 SD and rebounds, it signals a possible price reversal back towards the mean.
Confirming Trends: Dynamic SD levels provide a clear visual representation of price volatility, helping traders confirm trend strength and potential breakout points.
Enhancing Precision: By dynamically adjusting to market conditions, the indicator enhances trading precision, making it suitable for various market environments.
This script is an essential addition to any trader's toolkit, offering a blend of adaptability, precision, and visual clarity to support more informed trading decisions.
Settings:
Short Length: Period length used during consolidations.
Long Length: Period length used during trends.
ATR Length: Length for ATR calculation.
ATR Threshold: Threshold value to switch between short and long lengths.
Smoothing Length: Length for smoothing the standardized distance.
SD Smoothing Length: Length for smoothing the dynamic SD levels.
By using this indicator, traders can leverage its adaptive capabilities to navigate various market conditions effectively and enhance their trading performance on XAUUSD and other assets.
Moving Average Trend Meter [UkutaLabs]█ OVERVIEW
The Moving Average Trend Meter is a powerful trading indicator that visualizes current market strength. This indicator uses a series of four EMAs (Exponential Moving Averages) to determine short, medium and long term market strength. Each of the three rows of boxes corresponds to an EMA, with the top being the fast, the middle being the medium and the bottom being the slow. Depending on whether each EMA is above or below the source EMA, its corresponding row will be colored accordingly, with the boxes appearing green if the source is above it or red if it is below.
This indicator also displays when the strength of the market is transitioning between bullish and bearish, indicating that there may be an upcoming reversal.
The purpose of this script is to simplify the trading experience of users by providing an easier way to visualize current market strength using a series of EMAs.
█ USAGE
This indicator provides an easy to understand method of visualizing the current market strength based on the positioning of four EMAs. By default, the period for these EMAs are selected based on key Fibonacci levels, and the period of each one can be customized in the indicator settings.
Depending on whether or not the source EMA is above or below each of the other three EMAs, the boxes of the corresponding rows will be colored to indicate the current strength of the market.
If all three boxes are drawn the same color, a dot of the same color will be drawn above the boxes.
█ SETTINGS
Configuration
• Source EMA: Determines the period of the source EMA.
• Fast EMA: Determines the period of the fast EMA.
• Med EMA: Determines the period of the medium EMA.
• Slow EMA: Determines the period of the slow EMA.
Colors
• Bullish Color: Determines the color of boxes when the source EMA is above the respective EMA.
• Bearish Color: Determines the color of boxes when the source EMA is below the respective EMA.
• Bullish Transition Color: Determines the color of boxes when the current bar closes above the respective EMA while the source is below it.
• Bearish Transition Color: Determines the color of boxes when the current bar closes below the respective EMA while the source is above it.
Heiken Ashi Ribbon [UkutaLabs]█ OVERVIEW
The Heiken Ashi Ribbon is a powerful trading tool that creates a strong ribbon that indicates market strength. This ribbon is created using four moving averages that use Heiken Ashi values (high, low, open and close) as its input values.
The ribbon will also be colored green, red or grey depending on whether or not its direction aligns with current market strength.
█ USAGE
The Heiken Ashi Ribbon is created using a series of four moving averages that uses values from the Heiken Ashi bars as its inputs. The user has the ability to select whether the moving averages are EMAs or SMAs, as well as the ability to control the period of the moving averages.
If the moving average calculated using the Heiken Ashi Open is below the moving average calculated using the Heiken Ashi Close, the ribbon will be colored green, indicating a bullish trend. If the moving average calculated using the Heiken Ashi Open is above the moving average calculated using the Heiken Ashi Open, the ribbon will be colored red, indicating a bearish trend.
This indicator also uses a series of hidden EMAs to determine market strength. If these EMAs do not align with the direction of the Heiken Ashi Ribbon, the Ribbon will instead be colored grey, indicating uncertainty in the market, as well as a possible reversal.
█ SETTINGS
Configuration
• Moving Average Type: Determines whether or not the Heiken Ashi Moving Averages will be drawn as EMAs or SMAs.
• Moving Average Period: Determines the period of the Heiken Ashi Moving Averages.
Moving Average
• Moving Average Input: Determines the input values for the hidden EMAs.
GMMA Toolkit [QuantVue]The GMMA Toolkit is designed to leverage the principles of the Guppy Multiple Moving Average (GMMA). This indicator is equipped with multiple features to help traders identify trends, reversals, and periods of market compression.
The Guppy Multiple Moving Average (GMMA) is a technical analysis tool developed by Australian trader and author Daryl Guppy in the late 1990s.
It utilizes two sets of Exponential Moving Averages (EMAs) to capture both short-term and long-term market trends. The short-term EMAs represent the activity of traders, while the long-term EMAs reflect the behavior of investors.
By analyzing the interaction between these two groups of EMAs, traders can identify the strength and direction of trends, as well as potential reversals.
Due to the nature of GMMA, charts can become cluttered with numerous lines, making analysis challenging.
However, this indicator simplifies visualization by using clouds to represent the short-term and long-term EMA groups, determined by filling the area between the maximum and minimum EMAs in each group.
The GMMA Toolkit goes a step further and includes an oscillator that measures the difference between the average short-term and long-term EMAs, providing a clear visual representation of trend strength and direction.
The farther the oscillator is from the 0 level, the stronger the trend. It is plotted on a separate panel with values above zero indicating bullish conditions and values below zero indicating bearish conditions.
The inclusion of the oscillator in the GMMA Toolkit allows traders to identify earlier buy and sell signals based on the GMMA oscillator crossing the zero line compared to traditional crossover methods.
Lastly, the GMMA Toolkit features compression dots that indicate periods of market consolidation.
By measuring the spread between the maximum and minimum EMAs within both short-term and long-term groups, the indicator identifies when these spreads are significantly narrower than average by comparing the current spread to the average spread over a lookback period.
This visual cue helps traders anticipate potential breakout or breakdown scenarios, enhancing their ability to react to imminent trend changes.
By simplifying the visualization of the Guppy Multiple Moving Averages with clouds, providing earlier buy and sell signals through the oscillator, and highlighting periods of market consolidation with compression dots, this toolkit offers traders insightful tools for navigating market trends and potential reversals.
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Filtered MACD with Backtest [UAlgo]The "Filtered MACD with Backtest " indicator is an advanced trading tool designed for the TradingView platform. It combines the Moving Average Convergence Divergence (MACD) with additional filters such as Moving Average (MA) and Average Directional Index (ADX) to enhance trading signals. This indicator aims to provide more reliable entry and exit points by filtering out noise and confirming trends. Additionally, it includes a comprehensive backtesting module to simulate trading strategies and assess their performance based on historical data. The visual backtest module allows traders to see potential trades directly on the chart, making it easier to evaluate the effectiveness of the strategy.
🔶 Customizable Parameters :
Price Source Selection: Users can choose their preferred price source for calculations, providing flexibility in analysis.
Filter Parameters:
MA Filter: Option to use a Moving Average filter with types such as EMA, SMA, WMA, RMA, and VWMA, and a customizable length.
ADX Filter: Option to use an ADX filter with adjustable length and threshold to determine trend strength.
MACD Parameters: Customizable fast length, slow length, and signal smoothing for the MACD indicator.
Backtest Module:
Entry Type: Supports "Buy and Sell", "Buy", and "Sell" strategies.
Stop Loss Types: Choose from ATR-based, fixed point, or X bar high/low stop loss methods.
Reward to Risk Ratio: Set the desired take profit level relative to the stop loss.
Backtest Visuals: Display entry, stop loss, and take profit levels directly on the chart with
colored backgrounds.
Alerts: Configurable alerts for buy and sell signals.
🔶 Filtered MACD : Understanding How Filters Work with ADX and MA
ADX Filter:
The Average Directional Index (ADX) measures the strength of a trend. The script calculates ADX using the user-defined length and applies a threshold value.
Trading Signals with ADX Filter:
Buy Signal: A regular MACD buy signal (crossover of MACD line above the signal line) is only considered valid if the ADX is above the set threshold. This suggests a stronger uptrend to potentially capitalize on.
Sell Signal: Conversely, a regular MACD sell signal (crossunder of MACD line below the signal line) is only considered valid if the ADX is above the threshold, indicating a stronger downtrend for potential shorting opportunities.
Benefits: The ADX filter helps avoid whipsaws or false signals that might occur during choppy market conditions with weak trends.
MA Filter:
You can choose from various Moving Average (MA) types (EMA, SMA, WMA, RMA, VWMA) for the filter. The script calculates the chosen MA based on the user-defined length.
Trading Signals with MA Filter:
Buy Signal: A regular MACD buy signal is only considered valid if the closing price is above the MA value. This suggests a potential uptrend confirmed by the price action staying above the moving average.
Sell Signal: Conversely, a regular MACD sell signal is only considered valid if the closing price is below the MA value. This suggests a potential downtrend confirmed by the price action staying below the moving average.
Benefits: The MA filter helps identify potential trend continuation opportunities by ensuring the price aligns with the chosen moving average direction.
Combining Filters:
You can choose to use either the ADX filter, the MA filter, or both depending on your strategy preference. Using both filters adds an extra layer of confirmation for your signals.
🔶 Backtesting Module
The backtesting module in this script allows you to visually assess how the filtered MACD strategy would have performed on historical data. Here's a deeper dive into its features:
Backtesting Type: You can choose to backtest for buy signals only, sell signals only, or both. This allows you to analyze the strategy's effectiveness in different market conditions.
Stop-Loss Types: You can define how stop-loss orders are placed:
ATR (Average True Range): This uses a volatility measure (ATR) multiplied by a user-defined factor to set the stop-loss level.
Fixed Point: This allows you to specify a fixed dollar amount or percentage value as the stop-loss.
X bar High/Low: This sets the stop-loss at a certain number of bars (defined by the user) above/below the bar's high (for long positions) or low (for short positions).
Reward-to-Risk Ratio: Define the desired ratio between your potential profit and potential loss on each trade. The backtesting module will calculate take-profit levels based on this ratio and the stop-loss placement.
🔶 Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Moving Average Exponential-DonCHI-SUPERTRENDThe "Moving Average Exponential-DonCHI-SUPERTREND" is a trading strategy or indicator that combines three distinct technical analysis tools:
Moving Average Exponential (EMA): This is a type of moving average that gives more weight to recent prices, making it more responsive to price changes compared to a simple moving average.
Donchian Channels (DonCHI): These are bands that are plotted above and below the recent price highs and lows. They help identify the current price volatility and potential breakout points.
SUPERTREND: This is a trend-following indicator that uses the average true range (ATR) to determine the direction of the trend. It provides signals similar to moving averages but with less lag.
Consecutive Closes Above/Below 3 SMA with Z-Score BandsA simple indicator that measures consecutive closes above & below the 3-period simple moving average. An upper and lower Z-score has been calculated to indicate where the 4 standard deviations of the last 60 bars sits.
Useful for identifying directional runs in price.
