Research
Institutional-grade quantitative research across systematic macro, market microstructure, signal design, and regime detection.
Liquidity Regimes and Price Discovery in Gold Spot Markets
We examine how liquidity regimes in gold spot markets shift across sessions, measuring bid-ask spreads, order flow toxicity, and price impact across London, Comex, and Shanghai Gold Exchange venues. Our findings suggest that regime-conditional execution substantially reduces slippage in systematic strategies.
Why Execution Assumptions Distort Backtests
Most quantitative backtests assume instantaneous fills at mid-price. We measure the real-world gap between these assumptions and realized execution across equities, futures, and FX, finding that naive backtests overstate returns by 40–180 basis points annually for medium-frequency strategies.
Regime-Sensitive Model Design for Macro Portfolios
We present a framework for designing systematic macro models that adapt to macroeconomic regimes. Using yield curve signals, credit spreads, and volatility surface dynamics, we classify environments into four regimes and demonstrate that regime-conditional positioning improves risk-adjusted returns.
Signal Decay and Research Hygiene in Quantitative Finance
Quantitative signals degrade over time as markets adapt and competition increases. We study the half-life of common signal families and propose a framework for research hygiene that includes systematic signal monitoring, decay detection, and graceful deprecation.