研究迴圈報告 — Run #22

研究主題:sell QQQ/SPY put credit spread or naked put, optimal DTE 6-80 days, optimal delta, profit target, stop loss · 產生時間:2026-03-12 09:57:18 UTC

總輪次
10
總假說數
35
已確認
0
已拒絕
0
待驗證
35
最高信心
0.9200

執行摘要

本次研究迴圈共進行 10 輪, 產生 35 個假說, 其中 0 個通過驗證、 0 個被拒絕、 35 個待驗證。

總耗時 0 秒, 消耗 0 tokens。

各輪摘要

輪次Agent 數Agents假說數耗時Tokens
R13optimizer, researcher, risk-auditor 10
R23optimizer, researcher, risk-auditor 5
R33optimizer, researcher, risk-auditor 5
R43optimizer, researcher, risk-auditor 5
R53optimizer, researcher, risk-auditor 5
R63optimizer, researcher, risk-auditor 5
R72devil, risk-auditor 0
R82devil, risk-auditor 0
R92portfolio-mgr, risk-auditor 0
R102portfolio-mgr, risk-auditor 0

輪次評分(Keep/Discard Gate)

輪次綜合分數SharpeDrawdown樣本量決策改善%
R1 0.1596 0.0000 0.5000 0.0000 KEEP
R2 0.6115 1.0000 0.0000 1.0000 KEEP 283.15%
R3 0.8857 1.0000 1.0000 1.0000 KEEP 44.84%
R4 0.1956 0.0000 0.5000 0.0000 DISCARD -77.92%
R5 0.2214 0.0000 0.0000 1.0000 DISCARD -75.00%
R6 0.5059 0.6660 0.0000 1.0000 DISCARD -42.88%
R7 0.1250 0.0000 0.5000 0.0000 DISCARD -85.89%
R8 0.1250 0.0000 0.5000 0.0000 DISCARD -85.89%
R9 0.1250 0.0000 0.5000 0.0000 DISCARD -85.89%
R10 0.1250 0.0000 0.5000 0.0000 DISCARD -85.89%

假說清單

Round 1 (10 假說)

狀態維度信心假說
pending 0.0000 Selling puts at 30-45 DTE and closing at 50% profit yields higher risk-adjusted returns than 7-14 DTE or 60-80 DTE strategies, because theta decay accelerates most in the 30-45 DTE window while gamma risk remains manageable.
pending 0.0000 Selling puts at 5-8% OTM (strike/spot ≈ 0.92-0.95, ~0.20 delta proxy) provides the best risk/reward tradeoff compared to deeper OTM (10-15%, ~0.10 delta) or closer ATM (2-5%, ~0.30 delta).
pending 0.0000 Buying a protective put $5 (QQQ) or $5 (SPY) below the short strike reduces max loss by 70-85% while only reducing premium by 25-40%, resulting in superior risk-adjusted returns.
pending 0.0000 Closing at 50% of max profit yields the best Sharpe ratio by reducing time in trade (and therefore gamma/gap risk), even though it leaves premium on the table.
pending 0.0000 QQQ short puts generate 15-25% higher premium than SPY at equivalent moneyness due to higher implied volatility, but SPY provides better risk-adjusted returns due to broader diversification and lower tail risk.
pending 0.0000 Selling puts at 30-45 DTE and closing at 50% profit yields higher risk-adjusted returns than 7-14 DTE or 60-80 DTE strategies, because theta decay accelerates most in the 30-45 DTE window while gamma risk remains manageable.
pending 0.0000 Selling puts at 5-8% OTM (strike/spot ≈ 0.92-0.95, ~0.20 delta proxy) provides the best risk/reward tradeoff compared to deeper OTM (10-15%, ~0.10 delta) or closer ATM (2-5%, ~0.30 delta).
pending 0.0000 Buying a protective put $5 (QQQ) or $5 (SPY) below the short strike reduces max loss by 70-85% while only reducing premium by 25-40%, resulting in superior risk-adjusted returns.
pending 0.0000 Closing at 50% of max profit yields the best Sharpe ratio by reducing time in trade (and therefore gamma/gap risk), even though it leaves premium on the table.
pending 0.0000 QQQ short puts generate 15-25% higher premium than SPY at equivalent moneyness due to higher implied volatility, but SPY provides better risk-adjusted returns due to broader diversification and lower tail risk.

Round 2 (5 假說)

狀態維度信心假說
pending strike_selection 0.7500 For QQQ/SPY 30-45 DTE put selling, the 5-8% OTM strike zone delivers the highest risk-adjusted returns (Sharpe > 1.0) compared to 2-5% OTM (too much gamma risk) and 10-15% OTM (insufficient premium after transaction costs). The 5-8% zone sits at the liquidity/premium sweet spot: avg bid $4.78, avg s...
pending strike_selection 0.7000 For put credit spreads, $5-10 wide spreads on QQQ (approximately 1.5-3% of underlying) maximize return-on-risk because the long put at this width costs only 20-30% of the short put premium while capping max loss at $500-1000. Wider spreads ($20-50) show declining credit/width ratio (12.7% vs 19.0%) ...
pending strike_selection 0.5500 Selecting strikes based on highest open interest/volume concentration (rather than fixed % OTM) improves fill quality and reduces slippage by 30-50%, resulting in 0.3-0.5 higher Sharpe ratio vs fixed-distance methods. Market makers provide tighter spreads at volume-concentrated strikes.
pending strike_selection 0.6000 A regime-adaptive strike selection that widens OTM distance during high-VIX regimes (use put premium as VIX proxy: when 30DTE ATM put costs >4% of underlying, shift from 5% to 10% OTM) reduces max drawdown by 40-60% while sacrificing only 15-20% of annual return, because extreme premium environments...
pending strike_selection 0.5000 SPX weekly options (5-7 DTE) at 2-3% OTM deliver higher premium per unit of risk than QQQ monthly options (30-45 DTE) at 5-8% OTM, due to SPX's superior liquidity, $0.05 tick size, and faster theta decay in the final week, despite higher intraday gamma risk.

Round 3 (5 假說)

狀態維度信心假說
pending expiration_choice 0.8200 21 DTE is the optimal sweet spot for QQQ put selling: highest risk-adjusted Sharpe proxy (0.318) with 89% win rate, best premium-per-sqrt(DTE) efficiency, and manageable tail risk (P5 = -$6.49 vs -$33.92 for 60 DTE)
pending expiration_choice 0.8800 7 DTE weekly puts have the highest win rate (96.6%) but worst risk-adjusted returns due to extreme negative skew: occasional catastrophic losses (-$34.51 worst) dwarf the tiny average premium ($0.47)
pending expiration_choice 0.7500 50% profit target exit on 30 DTE puts dramatically improves capital efficiency: 93% of trades hit 50% profit within median 9 days, effectively converting a 30-day trade into a 9-day trade with halved risk exposure
pending expiration_choice 0.8000 Friday expirations offer superior liquidity (avg volume 666 vs 325-425 for other days) and tighter effective spreads (4.03% vs 4.13-6.35%), making them optimal for put selling entry/exit
pending expiration_choice 0.8500 60+ DTE puts are suboptimal for selling: lowest Sharpe proxy (0.091), lowest win rate (82.1%), and worst tail risk (P5=-$33.92), despite collecting highest absolute premium ($6.48). The variance risk premium decays faster than theta at longer tenors.

Round 4 (5 假說)

狀態維度信心假說
pending position_sizing 0.7800 Quarter-Kelly (f*/4) position sizing with 21 DTE 5-8% OTM QQQ naked puts delivers superior risk-adjusted returns (Sharpe > 1.2) compared to fixed fractional sizing, because full Kelly oversizes given the negative skew of option selling (occasional 5-10x losses vs typical 0.3-0.5x gains). With empiri...
pending position_sizing 0.7200 Volatility-scaled position sizing (reduce allocation by 50% when ATM put premium exceeds 2x its 60-day median) reduces max drawdown by 40-60% while sacrificing only 10-20% of CAGR, because high-premium environments (VIX spikes) signal elevated tail risk that is not adequately compensated by the extr...
pending position_sizing 0.8000 Limiting maximum concurrent positions to 3-5 (instead of allowing unlimited overlapping entries) improves risk-adjusted returns by preventing portfolio-level correlation blow-ups. With 21 DTE trades closing in median 9 days (at 50% PT), a systematic daily entry could accumulate 5-10 overlapping shor...
pending position_sizing 0.5500 Anti-martingale sizing (increase allocation by 25% after each consecutive win, reset to base after any loss) outperforms fixed sizing by 15-30% CAGR because put selling has 85-90% win rates, creating long winning streaks (5-15 consecutive wins) where geometric compounding amplifies returns. The asym...
pending position_sizing 0.6500 Margin-regime-aware sizing (using Reg-T margin rules: naked put margin = max(20% of underlying - OTM amount, 10% of strike) + premium) reveals that the effective capital requirement is 3-5x higher than premium-based sizing suggests, making the true return-on-capital for naked put selling 5-8% annual...

Round 5 (5 假說)

狀態維度信心假說
pending exit_rules 0.8200 H1: A combo exit rule (50% profit target + 2x premium stop loss + close at 7 DTE remaining) applied to 21 DTE 5% OTM QQQ/SPY naked puts will achieve Sharpe > 1.2 and reduce max drawdown by 50-70% vs hold-to-expiry, because each component addresses a distinct risk: the profit target captures theta de...
pending exit_rules 0.7200 H2: VIX-regime-conditional exit rules (tighter stops when implied volatility is elevated: 1.5x stop when ATM put premium > 2x its 60-day median, vs 2.5x stop in normal regimes) will improve Sharpe by 0.2-0.4 vs fixed stops, because elevated IV regimes produce both larger premiums AND larger adverse ...
pending exit_rules 0.6200 H3: A trailing stop mechanism (after 40% of premium is captured, set a floor at 25% profit — i.e., if the position moves from 40% profit back to only 25% profit, close immediately) will outperform a fixed 50% profit target by capturing more premium on positions that decay quickly while protecting ga...
pending exit_rules 0.7000 H4: Rolling losing positions to the next monthly expiry (when a 21 DTE put is at a loss with 7 DTE remaining, close and re-sell at 21 DTE at the same or wider OTM distance) destroys risk-adjusted returns compared to simply taking the loss and re-entering fresh, because rolling locks in a loss AND re...
pending exit_rules 0.5800 H5: For the 50% profit target exit rule, the optimal implementation uses mid-price (bid+ask)/2 rather than bid for the exit trigger, improving fill accuracy. But more importantly, adding a 'time decay floor' — never close before day 3 even if 50% target is hit on day 1-2 — will improve Sharpe by fil...

Round 6 (5 假說)

狀態維度信心假說
pending regime_filter 0.9200 SMA200 trend filter is the single most powerful regime filter: only sell QQQ naked puts when price is above the 200-day simple moving average. This filter improves Sharpe from 0.297 to 0.971 (3.3x improvement), raises win rate from 88.6% to 94.0%, and reduces max loss from -30.2% to -12.6%. In 2022,...
pending regime_filter 0.8800 The optimal composite regime filter combines SMA200 + 20-day momentum > -8%: Sharpe=0.964, WR=93.9%, excluding only 25.6% of days. Adding ATM premium thresholds (1.5x or 2x of 60-day median) provides negligible incremental benefit because the SMA200 filter already captures most regime shifts. The mo...
pending regime_filter 0.7200 February is the single worst calendar month for put selling (Sharpe=-0.334, mean PnL=-2.58%), driven by Feb 2020 crash (-18.2% mean loss) and Feb 2022/2025 drawdowns. A seasonal overlay that avoids February when QQQ is below SMA200 eliminates the worst tail events with minimal opportunity cost. Howe...
pending regime_filter 0.8200 ATM put premium as a vol regime proxy: when ATM premium exceeds 2x its 60-day median, expected PnL is strongly negative (Sharpe=-0.479, WR=64.4%). This captures VIX-spike-equivalent events using options-market data directly. However, this filter fires too rarely (only 3.9% of days) to be a primary f...
pending regime_filter 0.8500 The 2022 bear market was fundamentally untradeable for naked put selling regardless of filters — even the 11 days QQQ was above SMA200 in early Jan 2022 had Sharpe=-0.968 because the 21-day forward returns were negative. This confirms that regime filters work by AVOIDING entire bear market periods, ...

負面結果(已排除的方向)

輪次維度方法失敗原因分數
R4 position_sizing Quarter-Kelly (f*/4) position sizing with 21 DTE 5-8% OTM QQQ naked puts delivers superior risk-adjusted returns (Sharpe > 1.2) compared to fixed fractional sizing, because full Kelly oversizes given ... Composite score 0.1956 below baseline 0.1956
R5 exit_rules H1: A combo exit rule (50% profit target + 2x premium stop loss + close at 7 DTE remaining) applied to 21 DTE 5% OTM QQQ/SPY naked puts will achieve Sharpe > 1.2 and reduce max drawdown by 50-70% vs h... Composite score 0.2214 below baseline 0.2214
R6 regime_filter SMA200 trend filter is the single most powerful regime filter: only sell QQQ naked puts when price is above the 200-day simple moving average. This filter improves Sharpe from 0.297 to 0.971 (3.3x imp... Composite score 0.5059 below baseline 0.5059
R7 volatility_surface Round 7 research on volatility_surface Composite score 0.1250 below baseline 0.1250
R8 correlation Round 8 research on correlation Composite score 0.1250 below baseline 0.1250
R9 entry_timing Round 9 research on entry_timing Composite score 0.1250 below baseline 0.1250
R10 strike_selection Round 10 research on strike_selection Composite score 0.1250 below baseline 0.1250

錯誤日誌摘要

最近錯誤

方法評分

Agent方法成功率提出數確認數樣本數
researchergeneral0.00%505
researchergeneral0.00%10010
researcherstrike_selection0.00%505
researcherexpiration_choice0.00%505
researcherposition_sizing0.00%505
researcherexit_rules0.00%505
researcherregime_filter0.00%505

建議與後續行動