Research
Every strategy at InfiQuant begins as a statistical hypothesis, validated with rigorous out-of-sample testing against real NSE tick data. Our research focuses on structural market phenomena — not pattern matching.
Waitlist members receive one data-driven insight every Friday — real patterns in Indian derivatives backed by numbers, not opinions.
Research Areas
Topics covered in our Friday Research series. Full analysis with methodology, data, and results is available to waitlist members.
Analysis of 104 weekly BankNifty expiries showing statistically significant IV compression patterns and their correlation with directional moves in the final 90 minutes.
Systematic study of PCR divergences across Nifty weekly options as predictive indicators for short-term directional bias, validated out-of-sample.
CUSUM-based regime change detection applied to India VIX and realized volatility, with implications for options selling strategies in different regimes.
How the term structure of implied volatility skew evolves intraday on expiry days, and what systematic patterns emerge across strike distances.
Statistical analysis of intraday momentum persistence in BankNifty futures across different market regimes, time windows, and session segments.
Measuring real-world execution costs in Indian F&O markets: bid-ask spreads, slippage, and impact cost across different strike moneyness levels.
Sample Insights
Friday Insight #14
We analyzed 104 weekly BankNifty expiries from January 2024 to December 2025 to identify statistically significant intraday patterns on expiry days.
Key finding: When BankNifty ATM implied volatility compresses below 13% during the first half of the trading session (9:15–12:30), there is a 2.3x increase in directional moves exceeding 200 points in the final 90 minutes (14:00–15:30), compared to days where IV remains above 13%.
This pattern held across both bullish and bearish regimes. The effect was strongest on weeks with low preceding realized volatility (5-day HV below the 25th percentile), suggesting that IV compression on expiry days acts as a “coiled spring” effect.
Methodology: We computed ATM IV using the midpoint of the closest strike straddle, sampled at 15-minute intervals. Directional moves were measured as the absolute difference between the 12:30 and 15:15 BankNifty spot price. Statistical significance was confirmed via a two-sample t-test (p < 0.01) and validated out-of-sample on January–March 2026 data.
Friday Insight #11
We studied 312 trading sessions (Jan 2024–Dec 2025) where the Nifty put-call ratio (PCR) diverged from the prevailing trend by more than 1.5 standard deviations within the first 90 minutes of trading.
Key finding: When PCR spikes above 1.35 while Nifty spot is falling, there is a 68% probability of a reversal exceeding 50 points within the same session. The signal strengthens further when combined with India VIX above its 20-day moving average.
Methodology: PCR computed using total open interest across all active Nifty weekly strikes. Divergence measured against 20-session rolling mean. Significance validated via bootstrap resampling (10,000 iterations, p < 0.01).
Friday Insight #8
We analyzed 520 trading days of India VIX data to identify statistically reliable mean-reversion windows and their implications for short options strategies.
Key finding: When India VIX exceeds its 50-day EMA by more than 30%, it reverts to within 10% of the EMA within 5.2 trading days on average(median: 4 days). Options premium sellers entering during these spikes captured 2.1x the theta decay of normal-volatility entries.
Methodology: VIX regime classified using CUSUM change-point detection. Mean-reversion half-life estimated via Ornstein-Uhlenbeck model. Results confirmed out-of-sample on Q1 2026 data.
These are condensed previews. Full analysis including entry/exit parameters, position sizing, risk-adjusted returns, and complete out-of-sample results is available to waitlist members via the Friday Research series.
Methodology
Our research is grounded in statistical hypothesis testing. We do not use technical indicators, chart patterns, or discretionary signals. Every claim is backed by data with proper sample sizes, significance tests, and out-of-sample validation.
We focus on structural market phenomena: volatility clustering, regime changes, microstructure patterns, and options pricing dynamics specific to Indian markets. Our tick-level data spans 4+ years across all NSE F&O instruments.
All research explicitly accounts for transaction costs, slippage, and impact cost. We do not publish results that ignore execution realities.
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Research insights are for educational purposes only. Not investment advice.