Lakush bhai hi kehdeThis script appears to be a custom indicator for TradingView that combines **Volumatic Variable Index Dynamic Average (VIDYA)** with **liquidity zone detection** and volume analysis. Here's a breakdown of its main components and functionality:
### Key Features
1. **VIDYA Calculation**:
- Implements a Variable Index Dynamic Average using momentum and length parameters to adapt to price action.
- Smoothes the trend dynamically based on volume and price momentum.
2. **Liquidity Zone Detection**:
- Identifies pivot highs and lows, and marks support (low) and resistance (high) zones on the chart.
- Tracks and extends these zones dynamically to visualize potential price liquidity levels.
3. **Trend Detection**:
- Tracks whether the trend is up or down by comparing the price source against VIDYA-based bands.
- Includes upper and lower bands calculated with a distance factor and ATR for flexibility.
4. **Volume Analysis**:
- Aggregates volumes during uptrends and downtrends to show the dominance of buying or selling pressure.
- Displays the delta volume percentage to highlight the difference between buying and selling volumes.
5. **Annotations**:
- Adds labels and markers for significant events:
- Liquidity zones are labeled with volume data.
- Trend changes are highlighted with up and down arrows.
6. **Plot and Styling**:
- VIDYA is plotted along with its bands, and the area between price and VIDYA is shaded to emphasize trend direction.
- Supports customizable colors for uptrends and downtrends.
---
### Usage
- **Inputs**:
- `vidya_length` and `vidya_momentum`: Control the sensitivity of the VIDYA calculation.
- `band_distance`: Determines the width of upper and lower bands.
- Source: Defines the data used for calculations, typically `close`.
- **Outputs**:
- Trendlines, arrows, and shaded areas showing trend direction.
- Liquidity lines marking support/resistance zones.
- Volume statistics for trends and delta volume percentage.
---
### How to Use in TradingView
1. **Copy the Code**:
- Copy the script and paste it into the Pine Script editor in TradingView.
2. **Customize Inputs**:
- Adjust the parameters in the input section (`VIDYA Length`, `Momentum`, etc.) to suit your trading style.
3. **Add to Chart**:
- Save and add the script to your desired chart.
4. **Interpret Signals**:
- Use liquidity zones for potential reversal areas.
- Observe the trend and volume indicators for entries and exits.
---
### Potential Improvements
1. **Optimization**:
- Fine-tune the default values for `vidya_length`, `momentum`, and `band_distance` based on backtesting.
2. **Performance**:
- Limit the number of liquidity lines stored to enhance performance for charts with extensive data.
3. **Alerts**:
- Add alert conditions for trend changes, significant volume shifts, or price crossing liquidity zones.
Indicateurs et stratégies
Lavkush on topThe provided script is a Pine Script code designed for TradingView, implementing a **Variable Index Dynamic Average (VIDYA)** with some enhancements for volume-based trend analysis and liquidity zone identification. Here's a breakdown of its core functionalities:
---
### **Features**
1. **Variable Index Dynamic Average (VIDYA):**
- VIDYA is calculated using a momentum-based smoothing factor derived from the Chande Momentum Oscillator (CMO).
- This adaptive moving average reacts to price movements and reduces lag during volatile periods.
2. **Liquidity Zones:**
- Identifies pivot highs and lows to determine liquidity zones (support and resistance levels).
- Tracks volume at these levels and annotates charts with labels and liquidity lines.
3. **Trend Detection:**
- Uses crossovers of the source price with VIDYA upper and lower bands (ATR-based) to identify trends.
- Tracks accumulated volume during uptrends and downtrends for further analysis.
4. **Visual Enhancements:**
- Plots VIDYA lines with trend-based coloring.
- Displays liquidity levels with markers and labels indicating accumulated volume.
- Adds arrows for trend reversals and fills areas between VIDYA and price levels for visual clarity.
5. **Statistics Display:**
- Shows key metrics like "Buy Volume," "Sell Volume," and "Delta Volume" as a percentage difference on the chart's last bar.
---
### **Inputs**
- **VIDYA Length & Momentum:** Control the responsiveness of the VIDYA line.
- **Distance Factor for Bands:** Adjusts the multiplier for upper and lower ATR-based bands.
- **Source:** Allows selecting the data series (e.g., close, open).
- **Colors & Shadow Options:** Customize the visual appearance of the trends and liquidity zones.
---
### **Code Highlights**
- **Trend Direction Logic:**
- Determines the trend using crossovers of the source price with the upper and lower bands.
- Adjusts smoothing values based on trend direction to reduce noise.
- **Liquidity Zone Extension:**
- Extends liquidity lines dynamically as the price interacts with them.
- Labels significant liquidity levels with volume annotations.
- **Volume Tracking:**
- Accumulates volume during uptrends and downtrends separately.
- Computes the delta between uptrend and downtrend volumes, displaying it as a percentage.
- **Plotting:**
- Uses `plotshape` for trend reversal markers.
- Creates a shaded region to emphasize trend direction visually.
---
### **Potential Use Cases**
1. **Trend Analysis:** Identify and follow trends dynamically with volume-weighted insights.
2. **Support & Resistance Mapping:** Visualize key liquidity zones for potential price action setups.
3. **Volume Dynamics:** Monitor buy/sell volume changes during trend shifts.
4. **Scalping or Swing Trading:** Use trend reversals and liquidity levels for entry/exit points.
---
### **Customization Suggestions**
- **Add Alerts:** Use `alertcondition()` to notify users about trend changes or price interaction with liquidity zones.
- **Optimize for Asset Classes:** Adjust VIDYA length and ATR calculation parameters based on the asset's volatility (e.g., Forex, stocks, or crypto).
- **Enhance Volume Visualization:** Include bar charts or histograms for more detailed volume analysis.
---
Fibonacci Retracement Levels (Corrected)This script, "Fibonacci Retracement Levels (Corrected)," is designed to accurately calculate and display Fibonacci retracement levels based on the input data. It aims to provide improved precision and usability for analyzing market trends and price movements.
Note:
This script is published for testing purposes only. It is not intended for production or live trading environments. Feedback and suggestions are welcome for further improvement.
Stock Range Finder with 50% Retracementlocal lows will have a blue label with the text "Low" below the bar.
Local highs will have a red label with the text "High" above the bar.
The 50% retracement level will be plotted in orange.
The background will turn green when the retracement condition is met.
Dual Strategy Selector V2 - CryptogyaniOverview:
This script provides traders with a dual-strategy system that they can toggle between using a simple dropdown menu in the input settings. It is designed to cater to different trading styles and needs, offering both simplicity and advanced filtering techniques. The strategies are built around moving average crossovers, enhanced by configurable risk management tools like take profit levels, trailing stops, and ATR-based stop-loss.
Key Features:
Two Strategies in One Script:
Strategy 1: A classic moving average crossover strategy for identifying entry signals based on trend reversals. Includes user-defined take profit and trailing stop-loss options for profit locking.
Strategy 2: An advanced trend-following system that incorporates:
A higher timeframe trend filter to confirm entry signals.
ATR-based stop-loss for dynamic risk management.
Configurable partial take profit to secure gains while letting the trade run.
Highly Customizable:
All key parameters such as SMA lengths, take profit levels, ATR multiplier, and timeframe for the trend filter are adjustable via the input settings.
Dynamic Toggle:
Traders can switch between Strategy 1 and Strategy 2 with a single dropdown, allowing them to adapt the strategy to market conditions.
How It Works:
Strategy 1:
Entry Logic: A long trade is triggered when the fast SMA crosses above the slow SMA.
Exit Logic: The trade exits at either a user-defined take profit level (percentage or pips) or via an optional trailing stop that dynamically adjusts based on price movement.
Strategy 2:
Entry Logic: Builds on the SMA crossover logic but adds a higher timeframe trend filter to align trades with the broader market direction.
Risk Management:
ATR-Based Stop-Loss: Protects against adverse moves with a volatility-adjusted stop-loss.
Partial Take Profit: Allows traders to secure a percentage of gains while keeping some exposure for extended trends.
How to Use:
Select Your Strategy:
Use the dropdown in the input settings to choose Strategy 1 or Strategy 2.
Configure Parameters:
Adjust SMA lengths, take profit, and risk management settings to align with your trading style.
For Strategy 2, specify the higher timeframe for trend filtering.
Deploy and Monitor:
Apply the script to your preferred asset and timeframe.
Use the backtest results to fine-tune settings for optimal performance.
Why Choose This Script?:
This script stands out due to its dual-strategy flexibility and enhanced features:
For beginners: Strategy 1 provides a simple yet effective trend-following system with minimal setup.
For advanced traders: Strategy 2 includes powerful tools like trend filters and ATR-based stop-loss, making it ideal for challenging market conditions.
By combining simplicity with advanced features, this script offers something for everyone while maintaining full transparency and user customization.
Default Settings:
Strategy 1:
Fast SMA: 21, Slow SMA: 49
Take Profit: 7% or 50 pips
Trailing Stop: Optional (disabled by default)
Strategy 2:
Fast SMA: 20, Slow SMA: 50
ATR Multiplier: 1.5
Partial Take Profit: 50%
Higher Timeframe: 1 Day (1D)
Eze Profit - VWAP + MACD Combined SignalThe Eze Profit - VWAP + MACD Combined Signal is an advanced trading tool designed to help traders align price trends with momentum confirmation for better decision-making. By combining Volume-Weighted Average Price (VWAP) and Moving Average Convergence Divergence (MACD), this indicator provides clear entry and exit signals, allowing traders to follow trends and take advantage of momentum shifts.
How It Works:
VWAP:
VWAP represents the average price of an asset, weighted by volume, over a specific period.
It acts as a dynamic support/resistance level and trend filter. Price above VWAP indicates bullish conditions, while price below VWAP suggests bearish conditions.
MACD:
MACD measures momentum through the difference between fast and slow exponential moving averages (EMAs).
Signals are generated when the MACD line crosses its signal line:
Bullish Crossover: Indicates increasing upward momentum.
Bearish Crossunder: Indicates increasing downward momentum.
Combined Logic:
Long Signal: Triggered when price is above VWAP, and MACD exhibits a bullish crossover.
Short Signal: Triggered when price is below VWAP, and MACD exhibits a bearish crossunder.
The script tracks the trader's "in-position" state to prevent redundant signals and ensure clarity.
How to Use:
Use this script to identify potential long and short trading opportunities:
Buy Signal: Enter a long position when the price moves above VWAP and MACD confirms bullish momentum.
Sell Signal: Exit or short when the price drops below VWAP and MACD confirms bearish momentum.
Combine with additional tools like support/resistance, volume analysis, or candlestick patterns for confirmation.
Features:
VWAP Trend Filter: Dynamically adjusts to the trading session to identify overall trend direction.
MACD Momentum Confirmation: Detects key momentum shifts with configurable settings for fast, slow, and signal lengths.
Position State Tracking: Avoids signal redundancy by monitoring open positions.
Buy/Sell Visualizations: Plots Buy/Sell signals directly on the chart for ease of use.
Alerts: Notifies traders in real-time when a long or short signal is triggered.
Customizable Settings:
MACD Fast Length, Slow Length, and Signal Smoothing parameters.
VWAP timeframe resolution to adapt to different trading styles (e.g., intraday or daily).
Credits:
This script is based on standard VWAP and MACD calculations provided by TradingView’s library and has been enhanced with unique logic for combined signal generation.
Notes:
This indicator is intended for educational purposes and should not be considered financial advice. Use it as part of a broader trading strategy alongside other tools for optimal results.
RSI on Price Indicator Advanced Multi-Level RSIRSI on Price Indicator | Advanced Multi-Level RSI with Customizable Levels & Background Fill (Free Pine Script for TradingView)
Unlock the full potential of your TradingView charts with the 'RSI on Price NEW' indicator. This free Pine Script offers multi-level RSI bands, customizable overbought/oversold levels, and eye-catching background fills. Perfect for intraday, daily, weekly, or monthly analysis. Enhance your trading strategy today!
Take your trading analysis to the next level with the 'RSI on Price NEW' indicator for TradingView. This powerful and free Pine Script overlay brings the RSI directly onto your price chart, combining multiple levels of RSI calculations for detailed insights. With fully customizable settings for RSI periods, overbought/oversold thresholds, and dynamic color-coded background fills, this script is perfect for traders who want precision and clarity. Whether you're trading intraday, daily, weekly, or monthly charts, this script offers unparalleled versatility. Optimize your trading strategy today with this innovative RSI tool!
Black Line 50 RSI in center
above that 3 line is 60, 70, 80
below black line is 40, 30, 20 RSI
Top-Down Analysis previous dayTop-Down Analysis 2nd Candle with Enhanced Features
This powerful TradingView script is designed for traders looking for a comprehensive and customizable top-down analysis tool. The indicator plots horizontal lines based on significant price levels from multiple timeframes (Daily, 4-Hour, 1-Hour, and Weekly), offering clear reference points for technical analysis. Each timeframe is associated with high and low levels from the previous candle, and these levels are represented with customizable line styles, colors, and widths.
Key Features:
Multi-Timeframe Support: Displays high and low levels from the previous candle for the Daily, 4-Hour, 1-Hour, and Weekly timeframes. Customize which timeframes to show.
Customizable Line Appearance: Choose the line color, style (solid, dotted, dashed), and width for each timeframe. This allows for a personalized chart appearance to suit your trading strategy.
Text Labels: Add custom text labels to each line, and move them dynamically to the right, keeping them visible as the candles progress. The labels can be customized with user-defined text for each timeframe’s high and low levels.
Toggle Line Visibility: Easily control the visibility of the horizontal lines and their labels for each timeframe, allowing you to focus on the levels that matter most.
Price Alerts: Set price alerts when the price crosses any of the plotted levels, including the Daily, 4-Hour, 1-Hour, and Weekly levels. Receive notifications when significant price interactions occur.
User Control: With inputs for changing timeframes, colors, labels, and more, this indicator is fully customizable to fit your trading style.
This indicator is ideal for day traders, swing traders, and anyone utilizing multi-timeframe analysis for more informed decision-making.
Ichimoku Clouds with Bollinger Bands and VWAPIt's a Indicator with a Combination of Ichimoku Clouds , Bollinger Bands and VWAP.
Max Volatility Calculation (MAD) in PercentageMax Volatility Calculation (MAD) in Percentage
This Pine Script indicator calculates and visualizes the maximum volatility of a financial instrument using the Mean Absolute Deviation (MAD) expressed as a percentage of the mean price.
Input Parameter:
Users can set the length of the calculation period in bars.
Volatility Calculation:
It computes the Mean Absolute Deviation from the mean price over the specified number of bars, providing a measure of price volatility.
Maximum Volatility Tracking:
The script updates the current volatility at every specified length of bars and tracks the maximum volatility observed.
Percentage Representation:
The maximum volatility is converted to a percentage of the mean price, facilitating easier interpretation.
Chart Visualization:
The calculated maximum volatility percentage is plotted on the chart for quick reference.
H4 Candle Direction Arrows PaanNak guna Pm telegram farhanshoffi. Indicator ni untuk closing H4 06.00. Dia close bearish, kita bearish pukul 10. Dia close bullish, kita bullish pukul 10. Mantap pak abu. Teknik by masta amray99
flara EMA and BBWPcombinacion: EMA and BBWP. perfecto para trazar ema de 10, 55 y 200. se agrega las bandas de bollinger
Multi-Timeframe Volume-Weighted RSIA multiple timeframe volume-weighted RSI.
Blue Line = Current Time Frame
Orange Line = Select your desired Time Frame
e.g. Blue = Daily, Orange = Weekly
1. Incorporates Market Commitment
Value: By factoring in volume, the volume-weighted RSI captures the intensity of trading activity behind price movements.
Why it’s useful:
Regular RSI measures price momentum but does not differentiate between moves with high or low trading activity.
A volume-weighted RSI assigns greater importance to price changes occurring on high volume, reflecting stronger market conviction.
2. Improved Signal Reliability
Value: Signals generated by a volume-weighted RSI (e.g., overbought or oversold conditions) may be more reliable because they account for the level of trader participation.
Why it’s useful:
Low-volume price movements often result in false signals or "noise."
A volume-weighted RSI helps filter out such noise, reducing the likelihood of false breakouts or fake reversals.
3. Better Divergence Detection
Value: Divergences between price action and the RSI (bullish or bearish divergences) are more meaningful when confirmed by volume.
Why it’s useful:
Regular RSI might show divergence in price momentum, but this divergence might lack substance if the underlying volume is weak.
A volume-weighted RSI ensures that divergence signals align with periods of significant market participation.
4. Enhanced Trend Analysis
Value: Trends supported by strong volume are given more weight, helping traders better identify and follow trends.
Why it’s useful:
Regular RSI might show overbought or oversold signals prematurely during strong trends.
Volume-weighted RSI considers whether trends are backed by significant market activity, helping avoid early exits.
5. More Meaningful Overbought/Oversold Levels
Value: Levels like 70 (overbought) and 30 (oversold) are more credible when supported by volume.
Why it’s useful:
In a regular RSI, overbought or oversold levels might occur on light trading, leading to false reversals.
A volume-weighted RSI ensures these levels are triggered by substantial market participation, increasing their reliability.
Practical Applications:
Trend Confirmation: Use the volume-weighted RSI to confirm whether momentum in a trend is supported by strong participation.
Divergence Spotting: Identify divergences with more confidence by prioritizing those with volume support.
Filtering False Breakouts: Avoid entering trades during weak volume phases by focusing on volume-weighted RSI signals.
Limitations:
Market Type Dependency: Its usefulness may diminish in low-volume assets or markets where volume data is unavailable (e.g., forex).
ALL DAILY OPENSThis indicator Plots the daily opens in a distribution fashion, good for backtest purposes or key levels identifier
cup//@version=5
indicator("Cup and Handle Finder", overlay=true)
// Settings
length = 50
handleLength = 10
minCupSize = 30
breakoutPercentage = 1.02
targetMultiplier = 1.05
stopLossMultiplier = 0.98
// Calculate highest and lowest over the length for cup detection
var float highMax = na
var float lowMin = na
// Detect cup and handle formation
var int cupStartTime = na
var int cupEndTime = na
var bool inCup = false
var float cupStartPrice = na
var float cupEndPrice = na
var float breakoutPrice = na
var float targetPrice = na
var float stopLossPrice = na
// Initialize variables for handle checks
var float handleHigh = na
var float handleLow = na
for i = 0 to length - 1
if not inCup and close <= highMax and close >= (highMax + lowMin) / 2
cupStartPrice := close
cupStartTime := time
inCup := true
cupEndPrice := close
cupEndTime := time
else
inCup := false
highMax := ta.highest(high, length)
lowMin := ta.lowest(low, length)
if inCup and i >= length - handleLength
handleHigh := ta.highest(high, handleLength)
handleLow := ta.lowest(low, handleLength)
if handleHigh > handleLow * breakoutPercentage
breakoutPrice := handleHigh
targetPrice := breakoutPrice * targetMultiplier
stopLossPrice := breakoutPrice * stopLossMultiplier
// Draw the cup and handle on the chart
if not na(cupStartPrice)
line.new(x1=bar_index , y1=cupStartPrice, x2=bar_index , y2=cupEndPrice, color=color.blue, width=2, style=line.style_dashed)
if not na(breakoutPrice)
line.new(x1=bar_index , y1=breakoutPrice, x2=bar_index, y2=breakoutPrice, color=color.green, width=2, style=line.style_solid)
label.new(x=bar_index, y=breakoutPrice, text="Breakout", color=color.green, style=label.style_label_down, size=size.large)
label.new(x=bar_index, y=targetPrice, text="Target: " + str.tostring(targetPrice), color=color.green, style=label.style_label_up, size=size.small)
label.new(x=bar_index, y=stopLossPrice, text="Stop Loss: " + str.tostring(stopLossPrice), color=color.red, style=label.style_label_down, size=size.small)
// Signals for entry and exit based on price movements and strategy conditions
plotshape(series=close > breakoutPrice and close < targetPrice, location=location.belowbar, color=color.green, style=shape.labelup, text="Buy", size=size.small)
plotshape(series=close < stopLossPrice, location=location.abovebar, color=color.red, style=shape.labeldown, text="Sell", size=size.small)
Moving Averages 10/150/200Moving averages for 50, 150 and 200.
Provides mechanism to switch between SMA and EMA.
It also ensures proper mapping is done when chart is switched to weekly. E.g., length will change from 50 D to 10w, 150 D to 30w and 200 D to 40w.
QuantifyPS - 1Library "QuantifyPS"
normdist(z)
Parameters:
z (float) : (float): The z-score for which the CDF is to be calculated.
Returns: (float): The cumulative probability corresponding to the input z-score.
Notes:
- Uses an approximation method for the normal distribution CDF, which is computationally efficient.
- The result is accurate for most practical purposes but may have minor deviations for extreme values of `z`.
Formula:
- Based on the approximation formula:
`Φ(z) ≈ 1 - f(z) * P(t)` if `z > 0`, otherwise `Φ(z) ≈ f(z) * P(t)`,
where:
`f(z) = 0.3989423 * exp(-z^2 / 2)` (PDF of standard normal distribution)
`P(t) = Σ [c * t^i]` with constants `c` and `t = 1 / (1 + 0.2316419 * |z|)`.
Implementation details:
- The approximation uses five coefficients for the polynomial part of the CDF.
- Handles both positive and negative values of `z` symmetrically.
Constants:
- The coefficients and scaling factors are chosen to minimize approximation errors.
gamma(x)
Parameters:
x (float) : (float): The input value for which the Gamma function is to be calculated.
Must be greater than 0. For x <= 0, the function returns `na` as it is undefined.
Returns: (float): Approximation of the Gamma function for the input `x`.
Notes:
- The Lanczos approximation provides a numerically stable and efficient method to compute the Gamma function.
- The function is not defined for `x <= 0` and will return `na` in such cases.
- Uses precomputed Lanczos coefficients for accuracy.
- Includes handling for small numerical inaccuracies.
Formula:
- The Gamma function is approximated as:
`Γ(x) ≈ sqrt(2π) * t^(x + 0.5) * e^(-t) * Σ(p / (x + k))`
where `t = x + g + 0.5` and `p` is the array of Lanczos coefficients.
Implementation details:
- Lanczos coefficients (`p`) are precomputed and stored in an array.
- The summation iterates over these coefficients to compute the final result.
- The constant `g` controls the precision of the approximation (commonly `g = 7`).
t_cdf(t, df)
Parameters:
t (float) : (float): The t-statistic for which the CDF value is to be calculated.
df (int) : (int): Degrees of freedom of the t-distribution.
Returns: (float): Approximate CDF value for the given t-statistic.
Notes:
- This function computes a one-tailed p-value.
- Relies on an approximation formula using gamma functions and standard t-distribution properties.
- May not be as accurate as specialized statistical libraries for extreme values or very high degrees of freedom.
Formula:
- Let `x = df / (t^2 + df)`.
- The approximation formula is derived using:
`CDF(t, df) ≈ 1 - * x^((df + 1) / 2) / 2`,
where Γ represents the gamma function.
Implementation details:
- Computes the gamma ratio for normalization.
- Applies the t-distribution formula for one-tailed probabilities.
tStatForPValue(p, df)
Parameters:
p (float) : (float): P-value for which the t-statistic needs to be calculated.
Must be in the interval (0, 1).
df (int) : (int): Degrees of freedom of the t-distribution.
Returns: (float): The t-statistic corresponding to the given p-value.
Notes:
- If `p` is outside the interval (0, 1), the function returns `na` as an error.
- The function uses binary search with a fixed number of iterations and a defined tolerance.
- The result is accurate to within the specified tolerance (default: 0.0001).
- Relies on the cumulative density function (CDF) `t_cdf` for the t-distribution.
Formula:
- Uses the cumulative density function (CDF) of the t-distribution to iteratively find the t-statistic.
Implementation details:
- `low` and `high` define the search interval for the t-statistic.
- The midpoint (`mid`) is iteratively refined until the difference between the cumulative probability
and the target p-value is smaller than the tolerance.
jarqueBera(n, s, k)
Parameters:
n (float) : (series float): Number of observations in the dataset.
s (float) : (series float): Skewness of the dataset.
k (float) : (series float): Kurtosis of the dataset.
Returns: (float): The Jarque-Bera test statistic.
Formula:
JB = n *
Notes:
- A higher JB value suggests that the data deviates more from a normal distribution.
- The test is asymptotically distributed as a chi-squared distribution with 2 degrees of freedom.
- Use this value to calculate a p-value to determine the significance of the result.
skewness(data)
Parameters:
data (float) : (series float): Input data series.
Returns: (float): The skewness value.
Notes:
- Handles missing values (`na`) by ignoring invalid points.
- Includes error handling for zero variance to avoid division-by-zero scenarios.
- Skewness is calculated as the normalized third central moment of the data.
kurtosis(data)
Parameters:
data (float) : (series float): Input data series.
Returns: (float): The kurtosis value.
Notes:
- Handles missing values (`na`) by ignoring invalid points.
- Includes error handling for zero variance to avoid division-by-zero scenarios.
- Kurtosis is calculated as the normalized fourth central moment of the data.
regression(y, x, lag)
Parameters:
y (float) : (series float): Dependent series (observed values).
x (float) : (series float): Independent series (explanatory variable).
lag (int) : (int): Number of lags applied to the independent series (x).
Returns: (tuple): Returns a tuple containing the following values:
- n: Number of valid observations.
- alpha: Intercept of the regression line.
- beta: Slope of the regression line.
- t_stat: T-statistic for the beta coefficient.
- p_value: Two-tailed p-value for the beta coefficient.
- r_squared: Coefficient of determination (R²) indicating goodness of fit.
- skew: Skewness of the residuals.
- kurt: Kurtosis of the residuals.
Notes:
- Handles missing data (`na`) by ignoring invalid points.
- Includes basic error handling for zero variance and division-by-zero scenarios.
- Computes residual-based statistics (skewness and kurtosis) for model diagnostics.
Opening Line and Multi-SMA Strategy with Stoploss and TPThe Weekly Opening Line and Multi-SMA Strategy is a technical trading strategy designed to capitalize on price movements relative to key market levels. This approach combines the opening price of the first 5-minute candle at the start of each trading week with moving averages to identify potential trade opportunities. The inclusion of both simple and adjustable moving averages enhances flexibility, enabling traders to adapt the strategy to different market conditions. Below is a detailed explanation of the components and logic behind this strategy.
EMA Crossover Strategy indicator by dante5093simple but not yet complete, uses to 20 EMA and 50 EMA cross over , to signal a buy or sell trade
