u/Prabuddha-Peramuna ·
Reddit — r/algotrading
· July 19, 2026 at 17:39
· ⬆ 16 pts
· 💬 18 comments
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AI Summary
Summary
The author introduces a proprietary concept called Fair Value Accumulation (FVA), which uses volume-weighted POC logic to identify institutional "coiled spring" zones before impulsive moves (FVA Expansion).
He criticizes subjective visual patterns like Fair Value Gaps and argues for systematic, data-driven models, referencing his previously published Volatility Expansion Index (VEI).
The post is a high-level pitch for a quantitative framework without specific backtest results, code, or trade examples; it serves as a conceptual discussion rather than actionable research.
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Lately, it seems like the entire trading space is obsessed with Fair Value Gaps (FVG). While they are highly visual, they are often subjective and lack the statistical edge required for long-term survival.
As a quantitative researcher and algorithmic developer, I’ve moved away from eye-balled patterns and toward pure systematic logic. This has led me to develop a concept I call **Fair Value Accumulation (FVA)**.
I’ve spent significant time refining a quantitative algorithm to strip away market noise and identify what I call FVA Pockets (Fair Value Accumulation).
These are specific zones identified by my algorithm (the red dot clusters in the attached chart) where high-volume, institutional-grade activity is concentrated. Instead of treating these as static lines, I view them as "coiled springs" where the market is accumulating value before a major move.
My algorithm filters price/volume data to highlight these high-conviction zones. It isn't just about price; it’s about where the volume too.
The market rarely stays in an FVA Pocket for long. When it breaks out, it typically triggers an " FVA Expansion " a high-velocity, impulsive move that confirms the dominant institutional direction.
I do not front run the zone. I wait for the algorithm to flag the FVA Pocket, then I look for the FVA Expansion to confirm the move before entering to ride the impulse.
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If the industry relies on visual patterns, the edge is already gone. Real potential lies in math and logic. Earlier this year, I introduced the **Volatility Expansion Index (VEI)** to the public, a concept that was subsequently tested and verified by Kevin J. Davey and featured in *Technical Analysis of Stocks & Commodities* magazine.
**Volatility Expansion Index (VEI)**
[https://www.reddit.com/r/algotrading/comments/1phv4zz/the\_signal\_i\_use\_to\_detect\_hidden\_instability\_in/](https://www.reddit.com/r/algotrading/comments/1phv4zz/the_signal_i_use_to_detect_hidden_instability_in/)
I mention VEI to prove a point, **Quantitative researchers and Algo traders have more to contribute to this industry than any other group.**
I am not releasing the code or the specific math behind FVA. My goal here to challenge the community. My FVA algorithm works by identifying "coiled springs" clusters of high volume, institutional-grade positioning that precede impulsive **FVA Expansions**. It is a systematic, data driven approach that completely outperforms the predictive accuracy of standard FVG models.
Stop looking at the market through the lens of what you can see. Start looking at it through the lens of what the data is *doing*.
We need to stop obsessing over retail patterns and start building models that rely on volume weighted POC logic and statistical significance. Use your intelligence. Build your own tools. The market is math, not a picture, and it’s time we treated it that way.