Abstract: World Journal of Applied Mathematics and Statistics

Abstract:
In this paper, we introduce the Degree of Fair Value Gaps—a new quantitative metric that measures structural imbalances in financial markets. By analyzing tick data during FVG formation periods and calculating regression slopes, we establish an inverse relationship between FVG steepness (degree) and subsequent price reaction strength. Our framework includes: 1. Algorithmic FVG detection 2. Degree calculation methodology 3. Statistical validation across 4 asset classes (32,202 FVG events) 4. Trading strategy implementation. Results demonstrate that FVGs with degrees ≤ 0.00015 price units/second generate 3.2× stronger reactions than steeper FVGs (p < 0.001). This research bridges technical analysis and market microstructure theory, providing traders with a robust tool for assessments of liquidity voids and open price range. Refer to https://github.com/ aryan1ko/fvg-degree-study/ for full python implementation