u/colafroth ·
Reddit — r/algotrading
· May 13, 2026 at 04:24
· ⬆ 15 pts
· 💬 31 comments
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AI Summary
Summary
The post describes the author's manual backtesting process for a price-action strategy across 500+ assets from 2020-2025, splitting data into five separate yearly runs and tuning parameters based on consistency.
The author is seeking to understand the advantages of Walk Forward Analysis (WFA) over their own method, indicating confusion about proper validation techniques in algo trading.
Quality assessment: This is a methodological discussion, not a researched thesis or actionable analysis. It is noise for investment purposes.
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Comments31
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Hey everyone,
I am relatively new to algo trading and I made a strategy purely based on price action and backtests 500+ assets for the 2020-2025 data at least 40+ iterations to tune the parameters and it's doing ok live so far .
Before knowing the Walk Forward Backtest approach. What I did was to split the 5 years into 5 seperate backtests (different 100 assets per year) that run with same parameter. Then at the end I tune each parameter manually based on its performance among 5 different backtests, for example if it provide consistent edge over 4 out of 5 years then I will probably keep it. After each parameter adjustment I'll rerun 5 backtests again to confirm. Then I will strip it out and test other parameters one by one using this approach. Then mix and match parameters as well.
What is the key information I completely missed for WF that it is so good and useful?
Thanks so much guys!