Closed-form trend-following analytics, reference system implementations, and reproducible futures evidence in Python for quantitative researchers and practitioners
Multi-agent trading platform on an Alpaca paper account: a CLI places orders on request; scheduled routines manage trailing stops, alerts and daily records. Agents on Microsoft Agent Framework. Research uses walk-forward, out-of-sample and multiple-testing checks; no tested signal (MACD+RSI, TSMOM, GEX) has an edge yet. Not financial advice.
Systematic CTA / trend-following research around a supported 17-ETF TSMOM core. New factors, signals and overlays are tested with preregistration, realistic costs, robustness checks and falsification-first research discipline.
Research-backed time-series momentum backtester that tests 12-month trend-following signals, volatility targeting, transaction costs, parameter robustness, and walk-forward evaluation across ETFs.
Rule-based monthly momentum allocation for an analyst-picked basket. Desk study with first-month results, plus a live dashboard to run the strategies on any basket and start date.
Cross-asset trend following: a reproducible research implementation (data, signal, portfolio, costs, backtest, attribution, capacity) with an institutional chart pack.
Systematic quantitative trading strategies with institutional-grade risk metrics, execution simulation, and overfitting controls
Retail implementation of published time-series momentum: long-flat on 17 ETFs with a T-bill leg, run under preregistration with realistic broker costs. Judged "supported" as an implementation (net Sharpe 0.79 at a 25k IBKR account), not a novel edge. Phase 2: IBKR paper trading, three cycles to 2027-01.
AQR Time-Series Momentum (Moskowitz, Ooi, Pedersen 2012) replication with walk-forward GARCH(1,1) volatility-targeting extension applied per asset class.
Quant research library that refuses to print numbers it cannot support: stdlib-only factors (adapted Alpha101, TSMOM, microstructure), honesty-gated Rank-IC, fee-first backtests with tick-level trade explanations. No LLM in the loop. Nothing here trades.
A pre-registered test of time-series momentum across a cross-asset ETF panel: power analysis, size-corrected inference, and a stated detection limit rather than a point estimate
Pre-registered EWMA trend-following study on 10 ETFs, 2008–2026. Decomposes a failed endpoint into sizing and timing components
Personal projects related to quantitative finance
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