Source claim (post, 2026-09-22): a quant paper combining a Hidden Markov Model with reinforcement learning 'beat SPY on risk-adjusted returns, with shallower drawdowns across 2004-2025'. The paper is arXiv 2605.27848 (Verma, Putri, Lesupi; independent researchers; dated Nov 2025, posted 2026-05-27; not peer-reviewed; no code). Desk read: its own tables undercut it — a plain monthly equal-weight SPY/TLT/GLD portfolio has the best full-sample Sharpe (0.80 vs 0.52 and 0.58 for the HMM rotations, 0.46 SPY) and ties…
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