Know if your backtest is a real edge or overfit noise. Runs bar-permutation MCPT, Deflated Sharpe, PBO/CSCV, Hansen SPA, Romano-Wolf StepM, a stationary bootstrap and an out-of-sample split on your own returns — no market feed, no API keys.
"Shortform Hook Doctor is an AI assistant specialized in evaluating and prescribing high-retention video hooks, visual cues, and audio directions for TikToks, Reels, and Shorts."
A historical backtesting and validation-research protocol for algorithmic trading strategies: it treats your entry/exit/TP-SL/capital/leverage as fixed test inputs, stress-tests them with real costs and anti-overfit gates (plateau rule, walk-forward, random control, per-year robustness), and reports a research verdict (VALIDATION GATES PASSED / FAILED / INSUFFICIENT EVIDENCE). Analysis only: never deployment, sizing, leverage, or allocation advice.
Know if a betting record is luck or skill. Paste any betting history — get a full statistical audit: ROI with 95% confidence interval, the probability a losing bettor would show the same record, drawdown analysis, risk of ruin, and curation red flags. Retrospective analysis only — never predictions.
Keep a permanent, hash-chained ledger of public forecasts and see who has actually earned weight. Add calls before they resolve, add outcomes later, and get hit rate with confidence intervals, calibration, and naive versus track-record-weighted consensus on open questions. Edited or removed entries are detected. Offline deterministic script; calls recorded after the answer was known earn no weight.
Backtests a trend-following, pullback-entry strategy on Binance USDⓈ-M perpetuals (1h) with an out-of-sample split, funding, a strict-fill check, a random-direction significance test and buy & hold comparison. For research and education only: no trading, no buy/sell recommendations, not financial advice.
Computes historical win-rates and expected returns for 2X Leveraged & -2X Inverse ETFs based on 5-year index drawdowns (KOSPI, S&P500, NASDAQ). Eliminates emotional trading with objective statistical backtesting.
Audit and manage local AI Skills across Codex, Claude Code, and project workspaces. See what is actually active, detect duplicates and variants, compare changes over time, and generate an offline interactive management map. Read-only by default; every real change requires your approval.
