https://blckridge.com/research Published BlackRidge research on systematic trading, artificial intelligence and portfolio risk. en https://blckridge.com/research/correlation-regime-shifts-20261006/ https://blckridge.com/research/correlation-regime-shifts-20261006/ This report examines how the relationship between US stock and bond returns has changed across long-run annual data and a more recent monthly yield proxy. It considers what those measures can and cannot tell investors about preserving capital. Wed, 07 Oct 2026 00:00:00 GMT US stock-bond correlation capital preservation purchasing power annual US returns monthly yield proxy https://blckridge.com/research/portfolio-risk-aggregation-20261005/ https://blckridge.com/research/portfolio-risk-aggregation-20261005/ A descriptive study of U.S. investment-grade, high-yield and private credit. Across 35 monthly returns from November 2023 to September 2026, a hypothetical 50:50 IG/HY mix shows a 2.7% relative volatility reduction against a +1-correlation benchmark. Private-credit annual returns and borrower metrics use separate samples and do not establish default diversification or causal rate effects. Fourteen pages, eleven selected primary sources. Mon, 05 Oct 2026 00:00:00 GMT corporate credit risk aggregation investment grade and high yield portfolio return covariance option-adjusted spread changes private credit direct lending index interest coverage payment in kind https://blckridge.com/research/commodity-market-microstructure-20261004/ https://blckridge.com/research/commodity-market-microstructure-20261004/ A descriptive comparison of 1,473 common-date Brent and WTI spot observations from 2020 to 2025, oil benchmark and contract specifications, European day-ahead market time units, Berlin calendar arithmetic and EPEX annual turnover. The correlation of price levels does not establish hedge effectiveness. Thirteen pages, eight selected primary sources. Mon, 05 Oct 2026 00:00:00 GMT commodity market microstructure Brent and WTI spot prices Platts Dated Brent ICE Brent contract specifications European electricity markets 15-minute market time unit EPEX SPOT turnover https://blckridge.com/research/signal-commoditization-20260929/ https://blckridge.com/research/signal-commoditization-20260929/ Evidence on how published equity signals lose returns before and after publication, with the weakest retention in 2010-2024 calendar returns, when unpublished signals kept about a quarter of their backtest. Twelve pages compare long-run returns, publication cohorts, data types and capacity, with selected primary sources. Tue, 29 Sep 2026 00:00:00 GMT signal commoditization stock return predictors publication decay factor returns strategy capacity https://blckridge.com/research/asymmetric-tail-risk-20260929/ https://blckridge.com/research/asymmetric-tail-risk-20260929/ Loss tails of a put-selling index, the US stock market, the momentum factor and fourteen hedge fund strategy indices against a normal model, 1926 to 2026. The put-seller came within 0.09 of the market's Sharpe ratio, yet its worst 5% of months ran 1.50 times deeper than the normal forecast. At the same 10% volatility, drawdowns ranged from 15% to 60%. 13 pages, 11 direct sources. Tue, 29 Sep 2026 00:00:00 GMT tail risk expected shortfall CVaR position sizing negative skewness put writing drawdown limit leverage and volatility targeting https://blckridge.com/research/covariance-estimation-error-20260929/ https://blckridge.com/research/covariance-estimation-error-20260929/ Walk-forward test of four portfolio constructions on 49 US industries, 1973 to 2026. In the 33 most volatile months realised volatility ran 1.6 to 1.7 times the forecast, and the textbook optimiser underestimated risk in all 33. Rising volatility explains four fifths of the miss, correlation one fifth. 14 pages, 14 direct sources. Tue, 29 Sep 2026 00:00:00 GMT covariance estimation error portfolio risk forecast correlation in market stress Ledoit-Wolf shrinkage hierarchical risk parity value at risk backtest stock-bond correlation https://blckridge.com/research/forward-validation-20260928/ https://blckridge.com/research/forward-validation-20260928/ 208 of 212 published stock-return predictors, 1926 to 2024, compared using reconstructed backtest, forward and post-publication returns, not verified live trading. Pooled returns fell 29.4% in the forward window and 55.3% after publication. A 50/50 blend cut forecast error by 14.5%. 13 research pages, 12 direct sources. Mon, 28 Sep 2026 00:00:00 GMT backtest overfitting forward validation out-of-sample performance factor decay post-publication returns deflated Sharpe ratio systematic equity strategies https://blckridge.com/research/compounding-fee-drag-20260920/ https://blckridge.com/research/compounding-fee-drag-20260920/ How a percentage-based annual management fee transfers most long-horizon compound growth from investor to manager. A 2% fee is 28.6% of a 7% gross return every year. Over 30 years the manager captures 49.8% of total growth, crossing the majority in year 31. 13 pages, 4 direct sources. Sun, 20 Sep 2026 00:00:00 GMT management fees compound growth fee drag wealth transfer expense ratio long-horizon investing https://blckridge.com/research/hedge-fund-strategy-returns-2026/ https://blckridge.com/research/hedge-fund-strategy-returns-2026/ Fourteen hedge fund strategy indices over thirty years, split by interest-rate regime. How much of the return since 2022 comes from the level of rates and how much from the strategy itself. 17 pages, 6 direct sources. Mon, 14 Sep 2026 00:00:00 GMT hedge fund strategies interest rates trend following arbitrage risk-adjusted return managed futures https://blckridge.com/research/artificial-intelligence-quant-trading-2026/ https://blckridge.com/research/artificial-intelligence-quant-trading-2026/ A plain-language guide to the different kinds of AI used in quantitative trading, what each one does, and how they are combined inside an investment system. 18 pages, 17 direct sources. Tue, 01 Sep 2026 00:00:00 GMT artificial intelligence quantitative trading machine learning reinforcement learning portfolio optimization https://blckridge.com/research/quant-trading-ai-report-2026/ https://blckridge.com/research/quant-trading-ai-report-2026/ Has AI reduced hedge fund returns, how are operating models changing, and what now constitutes genuine, defensible alpha? 16 pages, 16 direct sources. Mon, 31 Aug 2026 00:00:00 GMT alpha decay hedge funds quantitative strategies artificial intelligence systematic investing