volatility-targeting

Deterministic, drawdown-controlled ETF allocation framework (Convex Core) — reproducibility companion to the research paper: model engine, report code, tests, and computed result artifacts. Hypothetical/backtested; not investment advice.

When does risk-managed momentum add value? A reproducible, out-of-sample, bootstrap-tested study - independent research, 2026.

Patent Moat Index: a 130/30 long-short equity strategy ranking U.S. stocks by patent value intensity, with sector-neutral ranking, 12% target-vol scaling, and a 10-month SMA macro filter. 45-year backtest (1980-2024) cuts max drawdown from -49% to -13% with significant FF5 alpha. UNC Kenan-Flagler Alpha Competition 2026.

Synthetic-data public demo of a master portfolio governor and multi-sleeve risk controller.

Synthetic defensive multi-asset allocation and volatility targeting demo.

Adaptive multi-asset allocation in MATLAB using momentum, risk parity, maximum diversification, minimum variance and volatility targeting.

Quantitative trading strategy leveraging a GARCH(1,1) model for dynamic volatility targeting on the Nasdaq-100 (QQQ)

Time-series momentum + vol-targeting lifts Sharpe and halves max DD.