Update to LONA™

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    "description": "Create, backtest, optimize and walk-forward test trading strategies with LONA™. Describe your logic in plain language, or bring your own Python code. Read, edit and version your strategies.\n\nSTRATEGIES\n• Turn ideas into Python strategies with immutable versioning.\n• Create and maintain your own strategy code.\n\nMARKET DATA\n• US and China stocks and ETFs, crypto, forex and mutual funds, with daily and intraday data where available.\n• Split- and dividend-adjusted equity data.\n• Use LONA™ datasets or upload your own OHLCV CSV.\n\nBACKTESTING\n• Interactive candlestick charts, equity and drawdown curves, per-symbol statistics and a full trade log.\n• Buy & Hold and benchmark comparisons.\n\nOPTIMIZATION\n• Sweep parameter grids and compare combinations by performance metric.\n• Day-of-Week and Time-of-Day tests block new entries on a selected weekday or UTC time slot; existing positions can still exit.\n• Explore results with interactive 2D and 3D charts.\n\nWALK-FORWARD ANALYSIS\n• Test optimized parameters on historical data not used during optimization to help assess robustness and detect overfitting.\n• Rolling and anchored windows: optimize in-sample, then test out-of-sample.\n• Review stitched out-of-sample equity and drawdown, window schedules, efficiency ratios and the share of profitable windows.\n\nMETRICS\nRealized P&L, total return, CAGR, annualized Sharpe ratio, maximum drawdown, return volatility, Calmar ratio, recovery factor, profit factor, payoff ratio, expectancy, average trade, win rate and average bars held.\n\nHistorical simulations only. LONA™ does not place live trades or connect to brokerage accounts. Nothing it shows is investment advice.",
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        "Does 'Sell in May and go away' actually work? Backtest it on SPY since 2000 against staying invested",
        "Backtest long-only Turtle-style Bitcoin breakouts, optimize 10–60-day entries, then test a holdout period vs buy-and-hold."
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