anitrade_contributed_codebase

Certainly! Here's a comprehensive list of the indicators from the specified GitHub repositories, along with brief descriptions of their functionalities:

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📁 20131015MT4BU/indicators

1. 2MAs.mq4:Displays two moving averages on the chart to identify trend direction and potential crossover points

2. 2MAsOnChart.mq4:Similar to 2MAs.mq4, this indicator plots two moving averages directly on the chart for visual analysis of trend changes

3. A.mq4:A generic indicator; specific functionality is unclear without further details

4. AMA.mq4:Implements the Adaptive Moving Average, adjusting the moving average based on market volatility to provide a smoother trend line

5. ASI-myMod.mq4:A modified version of the Accumulative Swing Index, used to evaluate long-term trends and potential reversals

6. ASI.mq4:Calculates the standard Accumulative Swing Index to assess market strength and trend direction

7. ATR.mq4:Computes the Average True Range to measure market volatility, aiding in setting stop-loss levels

8. ATRoverSD.mq4:Compares the ATR to the standard deviation to assess volatility relative to price dispersion

9. AZ_gFIR.mq4:Applies a generalized Finite Impulse Response (FIR) filter to smooth price data and identify underlying trends

10. A_Simple2_ind.mq4:A simple custom indicator; specific functionality is unclear without further details

11. A_Slope_Overshoot_To_BW_Ratio.mq4:Calculates the ratio of slope overshoot to bandwidth to assess market momentum and potential trend strength

12. A_Z_gFIR.mq4:Applies a zero-phase generalized FIR filter to eliminate phase distortion while smoothing price data

13. A_i_7BAS_Acc_Jrk_ADX.mq4:Combines acceleration, jerk, and Average Directional Index (ADX) indicators to identify changes in market momentum and strength

14. A_i_ASI_and_VWpriceTyp.mq4:Integrates the Accumulative Swing Index with volume-weighted price types to provide insights into market strength and price levels

15. A_i_BB7BASlp_Acc.mq4:Combines Bollinger Bands with acceleration to identify volatility and momentum shifts

16. A_i_BB_ADX.mq4:Integrates Bollinger Bands with ADX to assess volatility and trend strength

17. A_i_Hi_range_and_vol.mq4:Analyzes high range and volume data to identify potential breakout points

18. A_i_MAsCompare.mq4:Compares multiple moving averages to assess trend alignment and potential crossover points

19. A_i_N_Bar_Reg_Slope.mq4:Calculates the slope of a linear regression line over a specified number of bars to indicate trend direction and strength

20. A_i_SMA_HL.mq4:Calculates the Simple Moving Average of the high and low prices to provide a smoothed view of price action

21. A_i_SMApaddedATR.mq4:Combines SMA with a padded ATR to adjust for volatility, offering a dynamic moving average that adapts to market conditions

22. A_i_Slp5Btyp_prc.mq4:Analyzes the slope of a price series over five bars to identify short-term trends and potential price momentum shifts

23. A_i_Slp5Bvwp.mq4:Evaluates the slope of a volume-weighted price over five bars to provide insights into the strength of price movements, considering both price and volume

24. A_i_Variance-Ratio.mq4:Measures the variance of price changes relative to the variance of a random walk to assess the predictability of price movements

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📁 cTrader_VS/Indicators

1. AhilSignal Generates trading signals based on a combination of technical indicators; specific methodology is not detaile.

2. BollingerBandsSignal Provides buy/sell signals when price crosses Bollinger Bands, indicating potential overbought or oversold condition.

3. ChandelierExitMod Implements a modified Chandelier Exit strategy to set trailing stop-loss levels based on volatilit.

4. ChandelierSignal Generates trading signals using the Chandelier Exit indicator, which sets stop-loss levels based on AT.

5. Kaufman_Efficiency_Ratio Calculates the efficiency ratio to measure the strength of a trend, helping to filter out market nois.

6. LR Applies linear regression analysis to price data to identify trend direction and strengt.

7. LRFMAnormThld Combines Linear Regression Filter Moving Average with a normalized threshold to generate trading signal.

8. LRFMAnormThld_wParabSARdir Enhances LRFMAnormThld by incorporating Parabolic SAR direction for more refined signal.

9. LRF_Direction Determines market direction using a Linear Regression Filter to smooth price dat.

10. LRF_PSAR_Trend Combines Linear Regression Filter with Parabolic SAR to identify trend direction and potential reversal.

11. LRSwBB_signal Generates signals based on Linear Regression Slope with Bollinger Bands - detect extreme trend slope