Strategies

This strategy filled two portfolio gaps at once — the first-ever BCH coverage and the first single-bar wick-rejection mechanism — entering long on hammer candles forming as uptrend pullbacks above a 50-SMA. The signal fired cleanly across 89 trades from 2020-2026, but it had negative expectancy (-$439/trade, profit factor 0.53, Sharpe -3.76, -38.8% total return) and lost in every major year, with a doubly adverse profile of a 41.6% win rate and average wins smaller than average losses. The analyst abandoned it at the backtest-review gate on its second iteration, judging it a clean hypothesis-level failure with nothing for optimization to work with, so it never advanced to optimization or risk review.

This strategy exploited the turn-of-the-month anomaly by simply buying SOL around month boundaries, a clean deterministic rule grounded in DCA/index-rebalance flow. It was implemented exactly as specified and showed a spectacular +653% headline — but that came almost entirely from 2021's SOL mania (with two +60% single days), after which it lost money in 2024, 2025, and 2026 as rolling Sharpe fell from +8 to -6, all atop a 74.9% drawdown and ~110% volatility. The analyst abandoned it at the backtest-review gate on its second iteration as a decayed seasonal indistinguishable from long-beta, with no optimizable surface and a holdout sure to land in the negative recent regime, so it never advanced to optimization or risk review.

StockConnectClosureFlowReboundHkeq was the factory's first experiment on Hong Kong equities: it bought a 10-name high-southbound basket on the last HK session of each mainland holiday closure and held through the return of suspended Stock Connect flow, using a point-in-time closure calendar. The mechanism was implemented faithfully — all 350 legs long, entries on the final closed mainland weekday, exits on the 3rd session after resumption — and the initial backtest looked clean on gross numbers (12.61% total return, PF 1.28, 58.6% win rate), which earned an 'optimize' verdict at backtest review. Optimization then exposed the statistics: IS 0.910 vs OOS 0.493, PBO 0.656, deflated Sharpe 0.0157, failed programme FDR, and an OOS record carried by a single window, while the 350 trades reduced to 35 independent events with t = 0.90. The analyst abandoned it after one iteration, noting that HKEQ fees were never actually charged in the backtest and that netting the real ~0.22% round trip puts per-trade return below the venue floor, with no tunable path since the only live parameter is a cliff and Connect suspensions occur roughly 7 times a year by regulation.

The hypothesis staked out a genuinely new price estate for the factory — HKEQ, 174 daily instruments and zero prior experiments — and argued that a 21-session hold on the 6 most relatively oversold HSI blue chips would capture ~0.95%/month against a ~0.30% stamp-duty-heavy round trip. The implementation matched the design (long-only, always invested, ~40-day average holds, turnover suppressed on names that stayed in the bottom-6) and produced an unusually trustworthy sample: 445 single-name trades across the 2018 trade war, 2019 protests, COVID, the 2021-22 China bear and the later recovery. But the edge had the wrong sign: -12.02% total return, profit factor 0.933, Sharpe -0.098, and a 0.109% per-trade return that sat at roughly a third of the round-trip cost the engine never even charged (HKEQ Equity instruments bypass `_apply_fees`, so a manual ~2%/yr haircut would push the true result to about -2.5 to -3%/yr). The analyst abandoned it at backtest review rather than spend hours optimizing three tunables that only reshuffle which losers get bought, noting the Asia-ex-Japan contrarian premium is simply not present at the 21-session horizon in HSI large caps.

This strategy took the factory onto an untouched venue, CNEQ A-shares, with a deliberately simple thesis: buy CSI-300 mega caps that fell >=8% over five sessions without hitting the price limit, hold a fixed five sessions, equal-weight, no regime gate or supplementary data. Optimization results existed and looked economically plausible — 60.19% total return, Sharpe 0.876 over 912 trades, 0.712% average per-trade return, 8.99% max drawdown, and a passing holdout at Sharpe 0.932 on 112 trades — but the robustness layer was much less kind, with walk-forward overfitting flagged (IS 1.600 vs OOS 0.250), PBO 0.606 and failure to survive the programme FDR screen. What actually ended the run was mechanical, not statistical: on iteration 4 the Layer 3 sandbox backtest blew through its 300-second wall-clock limit on the 2400-day smoke window, following iteration 3's zero-trade failure caused by one mis-stamped leg. The pipeline abandoned it before any analyst or risk verdict was recorded.

This strategy expressed a slow directional-trend edge on ETH through weekly Deribit vertical debit spreads, chosen specifically to sidestep the factory's two options graveyards — short-vol blowups and unbounded long-option MTM artifacts. On the full available option-coverage window (~48 weekly cycles, Sep 2025–Sep 2026), it lost 25.0% with a profit factor of 0.925, expectancy of -$521 per cycle, negative Sharpe and a 71.3% drawdown. Notably ETH fell hard (~4500 to ~2000) over the window, giving the directional premise an ideal test, yet the weekly-trend vertical still whipsawed to a loss because the bounded wrapper did not clear premium and spread cost. The analyst abandoned it at the backtest-review stage as negative-expectancy, judging it not worth the optimization spend; optimization, analyst post-opt review, and risk review were never reached.

The strategy proposed a dollar-neutral long/short book on 30 USEQ large caps ranked by a vol-scaled MAX score, betting that stocks with recent jackpot-shaped single-day pops underperform over the following month, on the commission-free venue where the factory's usual fee-edge killer does not apply. Across 8 iterations the developer reworked the rotation logic — most recently converting to a full-book rotation so the realized equity curve and the mark-to-market series would reconcile — but the code itself records five prior backtests on the 31.5-year panel, every one with a profit factor below 1 and a coin-flip win rate, plus a 108-configuration pre-cost grid that was negative in every denominator, vol-window and n_side/hold variant. This run produced no backtest report of its own and was terminated at the coding stage after three consecutive timeouts, so backtest review, optimization, analyst and risk review never ran. The developer's own recommendation in the final code was ABANDON, on the grounds that the lottery-demand premium is arbitraged out of heavily institutionally-owned mega caps.

This strategy sought genuine diversification by trading laddered long-term momentum on lower-volatility TRX daily — requiring price above its 30- and 60-day-ago levels, a >8% monthly return, and a 200-SMA uptrend, with an ATR trailing stop. It was implemented correctly over 31 trades, but the +26.6% headline was an illusion: unrealized open-position MTM (32.7%) exceeded the total, leaving a roughly -6% realized record with profit factor 0.952, negative expectancy, a 61.7% drawdown, and a positive year carried entirely by one +66.8% day. The analyst abandoned it at the backtest-review gate on its second iteration as a premise failure — an outlier-and-paper-gain artifact with no realized edge and too sparse to validate — so it never advanced to optimization or risk review.

This strategy replicated the promoted LINK and ATOM daily multi-week trend-continuation mechanism on Filecoin (FIL) for portfolio diversification, using a 200-SMA regime filter and a 30/80 EMA momentum stack calibrated for a handful of trend-riding entries per year. Instead, the backtest lost roughly two-thirds of capital (-68.8% return, Sharpe -0.519, 79% max drawdown) across 175 trades and betrayed its own design, firing ~30 entries a year with ~1-day average holds as the logic whipsawed in FIL's choppy, largely bearish regimes. The reviewer identified the binding problem as structural — a long-only trend-follower applied to an asset that fell ~98% from its 2021 high has no uptrend edge for optimization to recover — and abandoned it at the backtest-review gate after five iterations, before spending any time on optimization or analysis.

The strategy set out to capture ETH's multi-week trends with the simplest possible structure — a 2-parameter daily dual-SMA crossover — on the thesis that minimal parameters mean minimal overfitting. Its base backtest looked headline-strong (+369% return) but rested on a weak 0.33 Sharpe whose confidence interval straddled zero, and the analyst cleared it to optimize mainly to cheaply test that thin edge. Optimization confirmed the fear: the sensitivity grid was a flat ~0.33 plateau sitting entirely below the best-of-225 luck bar, the deflated Sharpe collapsed to 0.10, the holdout failed, and the walk-forward was overfit with a negative OOS window — revealing the return was outlier-carried by a single +235% day in 2021 rather than a durable trend edge. After 3 iterations it was abandoned, a recurring pattern for modest single-asset ETH daily trend edges that are too small and too outlier-concentrated to clear multiple-testing correction.

InjFourHourVolumeBreakoutLong applied the proven FourHourVolumeBreakoutLong family — a volume-surge, breakout, green-bar long — to INJ 4H futures, expecting the ~30-60 trades/year to support valid walk-forward. It ran correctly (145 trades, no drops, leverage sized as designed) but had no edge on INJ: -57.8% return, Sharpe -2.57, profit factor 0.71, negative expectancy, a 61.4% drawdown, and negative years across most of 2022–2026, with an 11% commission-of-gross drag from rapid ~4-hour churn. The reviewer abandoned it at the backtest-review gate without optimization, judging a deeply negative Sharpe with PF below 1 across four years an absence of edge that tuning could only overfit. The decisive lesson was asset-selectivity: INJ simply does not exhibit the volume-confirmed breakout-continuation edge the family captures elsewhere, and its fast-churn fees dominate.

EthFundingPriceDivergenceSqueezeContinuationLS reframed funding not as a carry/valuation signal but as a positioning-trap tell, going with the ETH trend only when funding disagreed with it and trailing winners to build large per-trade returns. In backtest across 1645 trades it did the reverse of its thesis: per-trade capture was just 0.079% against high turnover, yielding profit_factor 0.92, -30.0% total return, Sharpe 0.286, and a 47.6% drawdown, negative in 5 of 7 years. The analyst abandoned it at backtest review on iteration 2 as a clear fee_edge death, never advancing to optimization since total return was negative and PF was below 1.0. The core lesson: the funding-divergence trap delivered no continuation edge, and the intended large-capture design instead produced tiny capture with heavy, mostly-short turnover.