Analysis of the Effectiveness of Adaptive Blocks
In recent months, we have introduced new comparison blocks, Crosses Above/Below Adaptive and IsGreater/IsLower Adaptive, on our codebase server. These advanced comparative blocks in trading strategies evaluate the historical performance of specific signals before confirming their validity. Unlike traditional blocks that analyze only the current market conditions, adaptive blocks examine past data to verify the statistical reliability of a signal.
The objective of this research is to verify whether generating strategies using adaptive blocks yields better results compared to traditional, non-adaptive blocks. As part of the experiment, we designed a method that allows us to compare thousands of strategies and perform statistical analysis on their performance.
Experiment Methodology:
We created 20 custom symmetrical rules for each type of comparative block. (80 in total )
Four build tasks were prepared, each generating strategies based on different conditions:
Crosses Above/Below Base
Crosses Above/Below Adaptive
IsGreater/IsLower Base
IsGreater/IsLower Adaptive
Strategies will be generated randomly without using genetic optimization, with only one filter requiring a minimum of two trades per month.
Hypothesis: Strategies using adaptive blocks should demonstrate better performance, with higher average values in the database (net profit, profit factor, drawdown, stability, and the number of trades) compared to strategies using non-adaptive blocks.
Tested Markets and Parameters:
Markets: GBPUSD, EURJPY, NQ
Platform: MT4
Testing Range: January 1, 2010 – December 31, 2024
System Types: Intraday (closing positions at the end of the US session) and Intraweekly (closing positions no later than Friday).
The results of this experiment will provide a clearer understanding of the effectiveness of adaptive blocks and their contribution to the automated generation of trading strategies.
You can download the Custom Blocks/Conditions here.
Interpretation of Results:
Better Performance of Adaptive Blocks:
Adaptive blocks generally show higher average profit (smaller losses).
The profit factor is consistently higher with adaptive blocks, indicating better strategy efficiency.
Lower Drawdown:
Adaptive blocks have a lower average drawdown, suggesting better risk management.
Stability:
Adaptive blocks demonstrate higher stability (less negative stability values).
Number of Trades:
Adaptive blocks generate fewer trades (Avg. NoT), indicating more cautious and likely better-filtered signals.
Summary:
Adaptive blocks consistently deliver better performance across nearly all tested parameters and markets.
Significant improvements in lower drawdown, higher profit factor, and improved stability.
Adaptive blocks generate fewer trades, indicating stricter signal filtering and reduced market exposure.
Conclusion:
Adaptive blocks prove to be more effective in risk management and achieving better results compared to traditional blocks.Therefore, we will continue to improve such adaptive blocks in the coming months as we aim to demonstrate whether their performance is better compared to traditional blocks.
