Strategies

The Research Lead turned a SuperMind A-share 反包 screen (an MA20 re-cross in an MA20 > MA120 uptrend after a five-MA squeeze) into a long-only test on 32 CNEQ large caps with standard exits and sizing. After a sizing fix in iteration 1, the backtest review sent it to optimization despite a thin edge and a large shortfall against the equal-weight basket. Optimization lifted per-trade returns to 0.62% with a 10.2% drawdown, but walk-forward OOS Sharpe was only 0.20, results swung across windows and years, and the strategy was positive in just 4 of 9 calendar years. The analyst abandoned it after 2 iterations on that hard year-consistency failure, and it never reached risk review or paper trading.

The Research Lead proposed a Hyperliquid daily panel that buys volume-confirmed down-shock days across 22 large perps and holds each position for two days, capped at 8 concurrent legs. Trading only began in mid-2023 because Hyperliquid has no real volume before then. The backtest-review analyst sent it to optimization. Walk-forward OOS was significant (t 2.58), and the 450-day holdout was positive but inconclusive (Sharpe 0.60, t 0.72) and statistically consistent with OOS. After one iteration the analyst promoted it with a low-confidence caveat about edge decay, and it is now in paper trading.

SolBookDepthElephantSurge15m was the fourth iteration of a hypothesis that trades alongside large newly posted resting orders on SOL. An earlier version never fired, so this one triggered on the elephant appearing rather than being pulled. The fix worked mechanically: there were about 160 trades a year, longs and shorts were balanced, and sizing followed the 1% ATR-risk rule. But the strategy lost money net of costs: -13.2% on the development period and -33.96% over the full backtest, with both sides losing and drawdown above the 20% limit. The analyst abandoned it at backtest review before optimization, so the analyst, risk and promotion stages were not reached; the verdict covers only this bar-level version, not the literal one-tick penny jump.

This run ported Chaos's TqSdk RSI(6) 35/65 re-cross demo to DOT on Hyperliquid daily bars. It changed two literal bugs in the source, evaluation on the forming candle and a nanosecond-based time stop, so the rules could fire at all. After 3 iterations the code traded as intended, but it lost money after costs: an average trade of -0.249% of notional, Sharpe -0.21 and a 54% drawdown on the reviewed period, and -44% over the full backtest. The backtest review abandoned it before optimization, because the 1% close-checked stop was inside DOT's daily noise and was fixed by the contract. The verdict covers only this port, not RSI re-cross reversal in general.

BnbDailyTsMomFundingCarryVetoLS tested whether the ETH funding-carry-veto time-series momentum design works on BNB, a heavily under-tested major. The initial backtest cleared the fee floor easily, and the backtest review sent it to optimization while flagging the losing short leg, the 42.9% drawdown and the profit concentrated in 2021. Walk-forward validation then showed almost no out-of-sample edge (pooled Sharpe 0.07, 1 of 4 windows positive), and no parameter set met the 25% drawdown limit. After one iteration the analyst abandoned it, finding no legitimate iteration path.

NvdaHeikinAshiPyramid ported a published Heikin-Ashi pyramiding rule to NVDA daily bars, with sizing as a share of equity and fills at the next open. Over 4 iterations it got past an earlier problem where the strategy never entered a trade. The final backtest traded actively (338 trades) but lost 79.73% with a negative Sharpe and a drawdown near 95%. At the backtest review the analyst confirmed the code matched the contract and abandoned the strategy for negative expectancy, so it never reached optimization, analysis or risk review.

This strategy carried the dual-timeframe momentum confluence archetype, already promoted on ADA and BTC, over to BNB as a long-short 4H/1D trend follower with an ATR trailing exit. After one iteration it backtested to +88.7% over about 6.7 years (Sharpe 0.77, 460 trades, 0.68% per trade). It also passed sensitivity checks with no cliffs and had a positive holdout (Sharpe ~1.06, t 1.24). The analyst promoted it even though pooled walk-forward OOS was essentially zero (Sharpe 0.038) and the edge depends on trend regimes, waiving a marginal profit-factor soft floor. It is now in paper trading; live trading is blocked until protective orders can rest at the exchange.

This run took the NR7 failed-downside-break reversal, already promoted on Bybit, OKX, Binance spot and Hyperliquid, and applied it unchanged to 13 US index and sector ETFs to see if it works outside crypto. The trigger fired about as often as predicted, but the backtest's average trade lost money (about -0.04% of notional), with a Sharpe of -0.12 and a drawdown of 26-30%, twice the pre-registered 15% limit. The analyst abandoned it at backtest review, after one iteration and without optimization: the losses were broad across names and years, costs were not the cause, and tuning would only fit noise. The breadth test answered its question: the edge looks crypto-specific, and this verdict covers only the ETF version, not the crypto panels.

This strategy re-ran an earlier BTC 5-factor composite that was abandoned for deflated-Sharpe reasons, this time with every parameter hard-coded so that no search took place. The full-sample backtest returned +128% with Sharpe 1.23 and an 8.5% drawdown over 253 trades, mostly uncorrelated with BTC. Out-of-sample windows, the holdout and a breadth replay on six other majors were all positive. Formal significance stayed inconclusive, so the analyst promoted it with a low-confidence label, and it is now in paper trading; live release waits on a venue-side protective stop.

PinkfishFollowTrendEtfSleeves ported the open-source pinkfish Follow-Trend rule to 8 ETF sleeves on USEQ, keeping the source's parameters and changing only execution, sizing and venue. Across 6 iterations it made +184.4% with Sharpe 0.63 and a 12.6% max drawdown, stayed out of the market in 2008, and earned 1.17% per trade, far above the cost floor. Its out-of-sample evidence was positive but just short of significance (pooled t 1.94, holdout t 1.60), its Calmar ratio was below the floor and it had a drawdown that lasted about 969 days. The analyst recommended promotion and it is now in paper trading with a low-confidence label.

This strategy ported QuantRocket's DemoMLStrategy onto the nine Select Sector SPDRs. It used a numpy logistic 'beats the median' classifier to pick the top 3 ETFs each month. The backtest was profitable in absolute terms (+241.4%, Sharpe 0.37, average trade 1.01%, well above costs), but over the development period it grew 2.42x against 4.30x for an equal-weight basket of the same ETFs, with a larger 62.8% drawdown and a signal IC indistinguishable from noise. The analyst abandoned it at backtest review after one iteration, concluding that tuning could not create the missing selection skill, so optimization and later stages were never reached.

BtcSpotDualTimeframeMomentumConfluenceLong carried the factory's best-performing futures momentum strategy over to BTC spot as a long-only, unleveraged strategy, kept the parameters from the source optimisation, and went to cash whenever the 4-hour and daily momentum disagreed or both pointed down. Over 8.5 years it returned +69.9% on 309 trades with Sharpe 0.86, a 12.4% max drawdown and a 1.04% average net trade, with low beta (0.08) to BTC. The analyst promoted it on a profitable holdout, robust parameters and limits that held, while noting that significance was not established, the signal had no forecasting power, and two of five pre-registered predictions were missed (win rate and profit factor). After one iteration it is now in paper trading.

This hypothesis turned an FMZ-style inventory-preserving LTC spot arbitrage between Binance and OKX into a research proposal. Over 3 iterations, the developer found that the catalog only had bars for the two LTC spot venues, with no quote ticks or order-book deltas, and that the runner seeds spot accounts with USDT only. Rather than test a different mechanism with a bar-close proxy, the developer wrote code that fails loudly, and every synthetic verification scenario failed at setup. The run was abandoned in the verification loop and never reached backtesting, optimization, analyst review or risk review.

VolatilityManagedQqqExposure scaled QQQ exposure inversely to trailing realized vol, citing a pre-study with Sharpe 0.72 and about 22% drawdown. Over two iterations, the full backtest produced Sharpe 0.57, a 637% total return over 264 trades and a 45.3% drawdown from the 2000-02 bear market. That drawdown was well above the pre-registered 25%, and the information ratio against buy-and-hold was slightly negative (-0.09). The analyst still sent it to optimization, where no candidate passed inner validation in any of the 7 nested walk-forward windows, so it was abandoned without reaching the analyst or risk review.

FmzAtomMeanAmplitude transplanted the FMZ mean-amplitude framework to ATOM Hyperliquid 4-hour trading with fixed 50% equity sizing and bar-close exits. After one iteration, its 313-position backtest over 950 days returned -62.526%, with Sharpe -1.071 and 70.548% maximum drawdown. Backtest review abandoned it for negative expectancy and severe modeled execution-cost drag, without proceeding to optimization or risk review. The rejection applies to this authorized adaptation, not the source strategy on its original commodity market.

HlSpotConfirmedShockFollowThrough built on and bet that sharp 24h moves on six Hyperliquid alt perps would continue when Binance spot confirmed them. Over 945 days of data it fired about as often as predicted (444 legs) but lost money everywhere: -29.9% total return, Sharpe -1.41, -0.925% average per trade and a 33.9% drawdown, with a third of trades stopped out. In iteration 1 the backtest-review gate abandoned it for negative expectancy before optimization. The rejection covers only this operationalization, not on its original instruments.

This strategy tested whether ETH volatility accelerating faster than BTC's made ETH options cheap, buying a weekly reverse iron condor when the relative-acceleration signal cleared its threshold. After 2 iterations the backtest still produced zero option trades, so it had no return, Sharpe or per-trade figures to judge. The pipeline abandoned it for options_no_option_trades: 0 of 395 periods were entered, mostly blocked with no recorded reason and otherwise by the readiness gates. No backtest review, optimization, analyst or risk-officer review took place.

EthVolumeConfirmedMomentumLS_HL traded ETH 4H momentum on Hyperliquid only when a volume surge confirmed the move, aiming to keep the factory's selective-filter principle while using volume instead of a second timeframe as the confirmation. Its backtest looked strong (+55% over 988 days, Sharpe 1.95, 3.27% average trade return, 5.55% drawdown), and after one iteration the analyst sent it to optimization. Optimization left the final-parameter Sharpe nearly unchanged (1.942, 54 trades), but pooled walk-forward OOS Sharpe was about zero, the holdout was positive but not significant, and sensitivity analysis flagged cliffs in the volume threshold. The analyst therefore recommended promotion as a low-confidence, not-statistically-proven candidate, and the strategy is now paper trading.

Original autonomous research: test whether a recent increase in ETH realized volatility predicts continued terminal dispersion that weekly option prices understate. Sell one lower-strike call, buy two center-strike calls, and sell one upper-strike call, all at one expiry with equally spaced strikes. This reverse butterfly earns a credit and benefits from ending outside the central loss region; it is not an unbounded long straddle. Extend RollingOptionsStrategy directly. ETH-PERPETUAL.DERIBIT supplies the untraded 4-HOUR primary clock; ETHUSD.HYPERLIQUID supplies synchronized 4-HOUR signal returns only. Discover historical ETH weekly calls with rolling_options, dte_target=7, offsets -0.08/0/+0.08, then validate actual strike geometry. Every resolved full option id must be appended to instruments/extra_instruments and the persisted execution contract before verification. The listed reference instruments are clocks and signal sources, never substitute trades. Market decisions fill at the signal close, the supported continuous-market equivalent of next-bar-open execution. No hedge-mode, atomic spread fills, selectable same-bar policy, or exchange-hosted protection is required. Use all available overlapping actual option history without an arbitrary lookback cap. Fee assumptions are conservative research budgets, checked against the underlying-notional fee basis in [Deribit Fees](https://support.deribit.com/hc/en-us/articles/25944746248989-Fees).

Across four iterations, LinkBybitBollChannel960 implemented frozen BollChannel rules with a 960-bar initialization replay. The supplied backtest lost 56.57% across 2,564 closed trades, with a Sharpe of -1.745. The abandonment review cites different metrics but likewise records negative expectancy and rejects optimization. This rejects the specified LINK/Bybit implementation, not the source strategy generally.

After three iterations, the strategy tested frozen Binance donor patterns on three Hyperliquid targets. The full backtest produced 5.40% net return and Sharpe 0.341 across 658 closed positions. The decisive development-period review abandoned it because average net notional trade return was only 0.0161% across 434 positions, below the 0.15% floor. No optimization or withheld-period result was assessed, so the rejection concerns this specific operationalization and basket.