Quantitative Research
From hypotheses to evidence.
Original quantitative research, empirical market microstructure studies, systematic strategy backtests, and AI-driven alpha signal discovery developed in-house at Alphigma.
While Core outlines our established quantitative concepts and institutional foundations, Research represents Alphigma’s active empirical investigations, experimental prototypes, and backtest results.
6 Focus Areas
Research TracksPurged CPCV
Validation ProtocolTick-Level US Equities
Empirical UniversePremarket Gap-Fade Strategy
Testing the relationship between premarket momentum, liquidity imbalances, and intraday mean reversion in large-cap equities.
“Overextended premarket price gaps driven by low-volume retail participants systematically revert towards VWAP within the first 45 minutes of the regular session.”
Evidence: Simulated over 7 years of institutional tick-level order book data with realistic market impact and borrow cost penalties.
Backtest Sharpe Ratio
2.41
Max Drawdown
6.8%
Win Rate
64.2%
Profit Factor
1.84
Active Investigations & Studies
Explore our 6 primary research placeholders spanning alpha signals, systematic execution, empirical market dynamics, and deep learning architectures.
Cross-Asset Momentum & Factor Decay Dynamics
Testing the velocity of factor decay across liquid equities under varying volatility regimes, identifying optimal signal rebalancing intervals.
Premarket Gap-Fade Strategy
Testing the relationship between premarket momentum, liquidity imbalances, and intraday mean reversion in large-cap equities.
Empirical Liquidity & Volatility Clustering in Extended Hours
Empirical study of market behavior, bid-ask spread expansion, and volatility transmission during pre-market and after-hours sessions.
Temporal Graph Neural Networks for Multi-Asset Lead-Lag Detection
Combining dynamic graph embeddings and temporal transformers to model latent supply-chain propagation and cross-asset price lead-lag.
Reinforcement Learning for Execution Horizon Optimization
Experimental prototype exploring PPO agents for adaptive execution timing under stochastic fill rates and inventory penalties.
Combinatorial Purged Cross-Validation in Overlapping Financial Time Series
Formal Alphigma technical report on mitigating data leakage, serial correlation, and variance inflation in institutional backtesting frameworks.
Collaborate on Quantitative Research
Alphigma partners with quantitative hedge funds, academic institutions, and technology providers for joint factor research, backtest validation, and dataset evaluation.