Most stacks tune a screener then a separate strategy. KreamEdge evaluates both in one end-to-end loop with a shared signal engine, portfolio-level fitness, and a shortlist-then-joint search so selection and trade management stop drifting apart.
A flat dollar-volume liquidity filter behaves differently in 2010 than in 2026, silently narrowing long backtests to mega-cap names and biasing the universe. This note quantifies the distortion and shows how a liquidity deflator corrects it.
Backtest 332 runs the US-equities book from Backtest 317 and the world-indices book from Backtest 308 on one shared cash account. Over Jan 2016 – May 2026 the blended portfolio compounded at 34.84% CAGR with a 27.13% max drawdown, versus 14.94% and 33.92% for the S&P 500.
Backtest 317 tests a long-only daily-bar systematic strategy on 4,176 US-listed equities from March 2016 to April 2026. It compounds to 30.4% CAGR versus 13.8% for the S&P 500, with a 17.7% max drawdown while holding positions only 78% of the time.
Backtest 308 tests a long-only daily-bar systematic strategy on 1,006 world major-index constituents, now including KOSPI 50, from February 2016 to April 2026. It compounds to 32.7% CAGR versus 14.2% for the S&P 500, with a 14.36% max drawdown.
Comparing fixed fractional, Kelly and sigma-targeting position sizing on a multi-version KreamEdge backtest bench. The bench cannot cleanly isolate a sizing edge.
We built a 3-state SPX percent-rank market-regime gate and tested it on 14 systematic quant backtests. None improved. The base rates and the structural reasons why – plus what to try next.
Une strategie systematique construite sur une liste de 77 ETFs disponibles dans l’assurance vie Linxea Spirit2, avec parametres d’entree et resultats de backtest detailles.
A systematic daily crypto strategy that sidesteps structural bear phases instead of riding them out: 29% market exposure, 1.66 Sharpe, 32% max drawdown over 2018-2026, with a statistically smooth equity curve relative to asset volatility.
A critical reading of the TradingAgents multi-agent LLM trading paper, explaining why backtesting LLM-based trading agents is fundamentally problematic and why most published results should be treated with extreme caution.
Disclaimer. Content on KreamEdge is published for informational and educational purposes only. Backtest results and strategy outputs do not constitute personalised investment advice nor an invitation to buy or sell any financial instrument. Past performance is not indicative of future results. Financial markets involve risk of partial or total capital loss. Each reader is solely responsible for their investment decisions and risk management. Full bilingual disclaimer on the community page.