Alpha Generation

Systematic Strategies

Our portfolio is constructed from diverse, uncorrelated alpha sources designed to perform across varying market regimes.

Core Pillars

Algorithmic Frameworks

We categorize our strategies by their underlying mathematical premise and holding period.

Statistical Arbitrage

Exploiting temporary pricing inefficiencies between co-integrated assets. We use Kalman Filters to dynamically estimate hedge ratios.

  • Market: Equities (Nifty 50)
  • Type: Mean Reversion
  • Horizon: Intraday to Multi-day

Machine Learning Swing

Using Gradient Boosting (XGBoost) models to predict directional moves based on Option Chain flows and Volatility Skew.

  • Market: Bank Nifty Options
  • Type: Directional / Trend
  • Horizon: Weekly Swing

Intraday Momentum

Parsing tick-level data and Order Book (Level 2) imbalances to capture short-term liquidity voids and momentum bursts.

  • Market: Index Futures
  • Type: Momentum / Scalp
  • Horizon: Minutes
Unified Execution

One Infrastructure, Multiple Alphas

While our strategies differ in logic, they share a common robust execution backbone. This centralized risk layer ensures that no single strategy can compromise the firm's capital base.

View Research Methodology

Portfolio Correlation Matrix

StatArb
MLSwing
HFT
StatArb
1.0
0.12
0.05
MLSwing
0.12
1.0
-0.03
HFT
0.05
-0.03
1.0

*Hypothetical correlation based on backtested returns.