Hour-Aware Adaptive Risk Management for Autonomous Memecoin Trading on Solana DEXs: Evidence, Theory, and Design Lessons from a 15-Day Deployment

Hour-Aware Adaptive Risk Management for Autonomous Memecoin Trading on Solana DEXs: Evidence, Theory, and Design Lessons from a 15-Day Deployment Version v4.1 (2026-09-28). Same manuscript as v4; the research-program and competing-interests passages no longer print patent application numbers. No other change. Kamat, Arati Uday. Independent Researcher. ORCID 0009-0000-4781-312X. This record deposits the v4 manuscript PDF. Main revisions from v3:1. A new Section III, "Theoretical Framework", states three predictions from Kyle (1985), Precup, Sutton and Singh (2000), and Bailey and Lopez de Prado (2014).2. A new Section VII, "Generalisable Design Lessons", a paragraph on significance for the field in Section I, and an expanded Section VIII.B.3. Section II, Related Work, expanded from one subsection to four, with 14 additional citations.4. JEL classification codes G11, G12, G14 and G17 added. Two corrections were also made before release: the entry-versus-exit hour recomputation in Section VI.A, and a disclosure of observation-window censoring in Section VI.B. All headline empirical numbers are unchanged from v2 and v3. Companion dataset bundle (concept DOI, always resolves to the latest version): 10.5281/zenodo.20043301.Companion preprints: SSRN abstract 6564803; arXiv 2606.08232. Abstract. We report a 15-day paper-traded deployment of an autonomous memecoin trading system on Solana decentralised exchanges (DEXs), designed as a controlled measurement of three microstructure questions on which classical equity theory offers well-defined predictions but on which the AMM-based Solana venue lacks published empirical measurement: (i) time-of-day return patterns on a 24/7 permissionless venue; (ii) whether decision-time filter stacks are net-positive against the counterfactual returns of the tokens they reject; (iii) whether small-sample cumulative-return statistics on a heavy-tailed venue are structurally robust or fragile. The 190-trade sample (March 29 to April 12, 2026) shows a 40.5 percent win rate, mean per-trade return +0.62 percent, cumulative +117.7 percent, skewness -1.21, excess kurtosis 6.61. Mann-Whitney U on three exploratorily identified worst entry hours yields p = 0.5634 (directional and non-confirmatory). A parallel counterfactual rejection-tracker collected 4,874 forward-sample observations across 184 rejection events; of 48 events observed for at least six hours, 27 (56.25 percent) reached a 50 percent drawdown from reference. Removing the top three trades (1.6 percent of sample) flips cumulative return unprofitable. The three findings connect to Kyle (1985) informed-flow, Precup-Sutton-Singh (2000) off-policy evaluation, and Bailey-Lopez de Prado (2014) deflated-Sharpe predictions. Alongside the trade log and rejection-sample corpus (CC-BY-4.0), the companion bundle deposits audit.py (MIT), an assertion-based reproduction script that exits zero iff every headline number in this manuscript reproduces from the deposited CSVs. The paper's principal contribution is measurement infrastructure and three transferable design lessons that generalise beyond this specific system. Competing interests. The trading system is the subject of two pending U.S. provisional patent applications in the same family (filed 2026-03-30 and 2026-06-25), both Micro Entity. Release of the manuscript does not restrict re-use under this deposit's CC-BY-4.0 licence. Keywords: autonomous trading, memecoin, decentralised exchange, market microstructure, time-of-day effects, counterfactual evaluation, reject inference, fragility, Solana. JEL: G11, G12, G14, G17.