Inverted Fair Value Gap (iFVG): a systematic test

Inverted Fair Value Gap (iFVG) is a refinement of the standard Fair Value Gap concept popularized by ICT and SMC traders. The premise: a regular FVG that gets violated and then re-respected as resistance/support “inverts” into a higher-probability setup. The marketing claims this filtration step substantially improves edge. The quantitative test asks: does it?

Mechanical definition

For this test, iFVG is defined as: (1) a 3-candle FVG pattern forms (imbalance between candle 1 high/low and candle 3 low/high), (2) price returns through the FVG zone, violating it, (3) on subsequent retest from the opposite side, the FVG zone now acts as resistance/support, (4) entry is taken on the second retest with stop beyond the FVG and target at structural levels.

Results vs regular FVG

What the numbers say

iFVG shows meaningful improvement over standard FVG: higher win rate (~6pp), better profit factor (+0.15-0.17), better R:R. The catch is trade count: iFVG produces about 30% of the trade frequency of standard FVG. The filter is real but expensive in opportunity terms.

The statistical significance problem

At 67 trades over 12 months on MNQ, the iFVG sample is below the 100-trade minimum for statistical confidence (see how long should you backtest). The reported 64% win rate could plausibly be 55% or 73% — the confidence interval is wide. To validate iFVG honestly, you'd want 200+ trades, which means 2-3 years of data on a single instrument.

Combined with portfolio approach

The opportunity-cost concern eases substantially in a portfolio context. iFVG running alongside other uncorrelated strategies (mean reversion, opening range breakout) provides selective filtering without leaving capital idle. The strategy contributes high-quality setups when it triggers, while other strategies fill the gaps when iFVG conditions don't exist.

What this implies

The iFVG refinement appears to genuinely add value over base FVG. The improvement is small in absolute terms (5-7pp WR, 0.15 PF) but consistent across instruments. For traders running mechanical FVG-based strategies, the iFVG filter is worth implementing. For traders running it as a standalone strategy on a single instrument, sample size will be a persistent problem — 2-3 years of data is needed before drawing confident conclusions.

The Puravida Edge methodology uses similar reversal-filter logic (price action structure breaks combined with volatility confirmation) in mechanized form, validated via 1500-path Monte Carlo stress testing. See Fair Value Gaps backtested honestly for the broader FVG analysis.

FAQ

What is an Inverted Fair Value Gap (iFVG)?

An iFVG forms when a regular Fair Value Gap (3-candle imbalance pattern) gets violated by price, then retested from the opposite side where it now acts as resistance or support. The setup represents a sentiment shift in the gap zone and is taught as a higher-probability filter than entering on the original FVG.

Does iFVG actually work better than regular FVG?

In mechanical testing, yes — iFVG shows ~6pp higher win rate and ~0.15-0.17 better profit factor than standard FVG entries across MNQ and NAS instruments. The improvement is real but small in absolute terms, and iFVG produces only about 30% of the trade frequency of regular FVG.

Can iFVG be used as a standalone strategy?

On a single instrument, sample size will be a persistent problem — iFVG typically produces 50-70 trades per year, below the 100-trade minimum for statistical confidence. It works better as one component of a diversified strategy portfolio, where its selective filtering complements higher-frequency systems.