Optimization Round 2: Overcorrection (Score: 51)

User

OPTIMIZATION ROUND 2 — Continuation
You are iterating on a previous agent run. Do NOT start from scratch. Build directly on the findings below.

Prior Run History — do NOT repeat strategies without meaningful improvement:

Round 1 — Score: 71/100 (mixed) | Goal: 100%+ avg annual return across ALL regimes
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

PROMISING — massive alpha exists here, but drawdown is too high. Do NOT ignore:
Mean-Reversion Bull Call Spreads (META, NVDA, AMD) [mean-reversion | signals: RSI] on META, NVDA, AMD
2023 Recovery : 500.76%
2024 Trend : 2565.06%
2022 Bear : -78.22% | maxDD: -78.00%
2025 Current : -80.78% | maxDD: -83.00%
→ Note: Achieved +2565% in 2024 but suffered terminal drawdowns (>95%) in 2022 and 2025.
→ Fix ideas: reduce position size to 2-3% of BP, add VIX ceiling (only enter VIX < 20), tighten stop loss to -20%, test single ticker before scaling.

TESTED/FAILED (do NOT recreate these exact configurations):
Refined Momentum Spreads (COP, XOM) [momentum] — Powerful hedge for inflationary bear markets (+80% in 2022) but inconsistent in tech-led bull markets.
Trend-Filtered BPS [hybrid] — Zero trades executed; the combination of VIX and SMA filters was too restrictive for the tested periods.

Direction for Round 2: Test variations of the Iron Condor strategy with stricter entry filters (e.g., only entering when VIX > 20) or tighter stop-losses to reduce the 59% maximum drawdown to a more manageable level for a $25,000 account.

Your goal: Find a strategy averaging 80%+ across ALL regimes (2022, 2023, 2024, 2025) — not just one banner year.
Minimum bar for deployment: avg annual return ≥ 80% AND max drawdown in any single year ≤ 40%.

Look at my watchlist and current market conditions, design a profitable options trading strategy that I should use at Monday at open. My goal is to double my $25,000 Public Portfolio live-trading account this year.

Aurora

Welcome to Optimization Round 2. We have a clear mandate: take the 54% average return from the Round 1 Iron Condors and the massive alpha from the Mean-Reversion Bull Call Spreads, and refine them into a strategy that hits the 80%+ average annual return mark while keeping drawdowns under 40%.

Your goal of doubling a $25,000 account is aggressive, but the Round 1 data shows the alpha exists—we just need to solve for the terminal drawdowns. I will use a research-first approach, leveraging specialized subagents to stress-test these refinements in parallel.

The Core Question

Can we refine the SPY/QQQ Iron Condor and the META/NVDA/AMD Mean-Reversion structures—using VIX-gated entries and tighter stop-losses—to achieve an 80%+ average annual return across all regimes (2022-2025) while maintaining a max drawdown under 40% for a $25,000 account?

Competing Hypotheses

Hypothesis A (Volatility Alpha Refinement): The "Always-On" Iron Condor is robust but bleeds during low-volatility drifts. Restricting entry to VIX > 20 and tightening stop-losses to 20% of credit will preserve the 50%+ returns while cutting the 59% drawdown by half.
Hypothesis B (Risk-Managed Mean Reversion): The META/NVDA/AMD Bull Call Spreads produced terminal drawdowns because of position sizing. Reducing allocation to 2% of buying power and adding a VIX < 20 ceiling will capture the 2000%+ upside years while surviving the 2022/2025 bear regimes.
Hypothesis C (Watchlist-Driven Alpha): Your specific watchlist stocks may offer better risk/reward setups for these refined structures than the generic tech basket, particularly if they are currently in a mean-reversion sweet spot (RSI < 35).

The Execution Plan

Step 1: Context Gathering (Watchlist & Market Regime)
I will fetch your current watchlist and query the market regime (SPY trend, VIX level, and sector RSI) to ground the subagents' research in Monday's opening conditions.
Tools: Fetch User Watchlists, Stock Screener

Step 2: Spawn Specialized Subagents (Parallel Exploration)
I will launch three optionsStrategy subagents to iterate on Round 1 findings in parallel:

Subagent 1 (Volatility Refinement): Refine SPY/QQQ Iron Condors. Test VIX > 20 entry filters and tiered stop-losses (15%, 20%, 25%). initialValue: 25000.
Subagent 2 (Mean-Reversion Refinement): Refine META/NVDA/AMD Bull Call Spreads. Test 2% max allocation, VIX < 20 entry filters, and tight stop-losses. initialValue: 25000.
Subagent 3 (Watchlist Explorer): Research your watchlist stocks and identify which are suitable for the refined structures based on current technicals.
Tool: createSubagents

Step 3: Wait & Synthesize
Monitor subagent progress and aggregate the top 2-3 winners from each track.
Tool: waitForSubagents

Step 4: Goal Feasibility & Eligibility Check
I will calculate the average return across all regimes (2022-2025) for the top candidates. I will explicitly flag the gap if the average return is less than 50% of your 100% goal. I will also check if the winning strategy's filters are satisfied for Monday's open.

Step 5: Attach Monitor & Deploy (Pattern B)
I will use Edit Portfolio to attach a LaunchAgent Portfolio Monitor to the top-performing strategy. This monitor will review your positions weekly and report on regime flips (e.g., SPY crossing below 200-day SMA), ensuring the strategy "reacts if the market turns" as you requested. I will then deploy the augmented portfolio to your Public Portfolio account.
Tool: Edit Portfolio (addStrategies then deploy)

I am starting Step 1 now.

User

Retrieve the user's saved watchlists to identify target symbols for the Round 2 options strategy.

Aurora

Here is your 1 watchlist, in the same order as in the app:

1. All my favorites

META (stock), GOOG (stock), NVDA (stock), BTC-USD (crypto), HOOD (stock), LLY (stock), SPY (stock), QQQ (stock), AMD (stock), AVGO (stock), TSM (stock), ANET (stock), GS (stock), DUOL (stock), XOM (stock), COP (stock), POWL (stock)

User

Provide the current price, 50-day SMA, 200-day SMA, and 14-day RSI for SPY. Also, provide the current level of the VIX. For the following stocks, provide their current 14-day RSI and 30-day Price Standard Deviation: META, GOOG, NVDA, HOOD, LLY, QQQ, AMD, AVGO, TSM, ANET, GS, DUOL, XOM, COP, POWL.

User

Launching 3 subagents to explore strategies in parallel

User

Waiting for subagents to complete...

User

Waiting for subagents to complete...

Aurora

All 3 subagents complete.

Subagent 1: Analyze the user's favorites watchlist (META, GOOG, NVDA, HOOD, LLY, AMD, AVGO, TSM, ANET, GS, DUOL, XOM, COP, POWL). Identify candidates currently in a mean-reversion zone (RSI < 40) or momentum breakout (RSI > 60). Create and backtest bull call spreads on mean-reversion names and long calls on momentum names. Use $25,000 initialValue, 2-3% position sizing, and backtest across 2022-2025 regimes to find a strategy averaging 80%+ return.

Status: completed
Summary:
RSI Options Strategy Analysis: 2022-2026 Performance Review

Designed and tested a dual-regime options strategy for a 14-stock watchlist (including NVDA, META, and LLY) to achieve an 80% average annual return. The approach combined RSI-based mean reversion (RSI < 40) using Bull Call Spreads and momentum breakouts (RSI > 60) using Long Calls and Spreads.

Research & Methodology

We analyzed 14 tickers for current RSI levels and historical signal frequency. Research revealed that while momentum signals (RSI > 60) are frequent in bull markets, mean reversion signals (RSI < 40) are rarer but potentially more potent. We implemented a $25,000 portfolio with 2.5% position sizing and strict 50% profit/30% loss exit rules.

Key Discoveries

The 2022 Edge: The strategy was a standout performer in the 2022 bear market, returning +35.83% while the SPY fell -18.38% (a +54% alpha). This suggests that RSI-based dip buying is a powerful defensive mechanism during high-volatility regimes.

Bull Market Failure: The strategy failed significantly in 2023, 2024, and 2025. The tight 30% stop loss caused the portfolio to be "chopped out" during healthy pullbacks in trending markets. Furthermore, the $25,000 account size proved to be a major constraint; high-priced stocks like LLY ($800+) often require more capital per contract than the 2.5% ($625) allocation allowed, leading to missed trades.

Quantitative Highlights

Best Period: 2022 (+35.83% Return, 1.23 Sortino)
Worst Period: 2025-2026 (-60.63% Return, -1.91 Sortino)
Average Annual Return: -22.96% (Failed 80% target)

Next Steps

To reach the 80% goal, the strategy requires optimization: 1) Add a Trend Filter (e.g., Price > 50-day SMA) to avoid buying "falling knives," 2) Widen Stop Losses to 50% for high-IV names, and 3) Increase Capital to $100k to ensure feasibility for high-priced tech leaders.

Subagent 2: Refine the META, NVDA, and AMD Bull Call Spread strategy from Round 1. Use an initialValue of $25,000. Implement a strict position sizing rule: max 2% of buying power per position. Add an entry filter for VIX < 20 to avoid high-volatility regimes. Test tight stop-losses (e.g., -20% to -30%). Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ and max drawdown under 40%.

Status: completed
Summary:
Strategy Refinement Report: META, NVDA, AMD Bull Call Spreads

Tested a volatility-aware Bull Call Spread strategy for a $25,000 account across four market regimes (2022-2025). The objective was to achieve an 80% annual return with a max drawdown under 40%.

Methodology

Conducted 28 backtests across 6 experimental portfolios and 1 benchmark. Variables tested included position sizing (2% vs 5%), VIX entry filters (<20 vs <25), and stop-loss levels (-20% to -30%). Research confirmed that while 5-point spreads on these tickers average ~$230, the combination of restrictive filters and high underlying prices created a total execution failure.

Key Discoveries

The Execution Desert: All 6 option portfolios returned 0 trades and 0% total return. The primary bottleneck was the interaction between the $25k account size and the high price of the underlyings (META ~$500, NVDA ~$130). Even at 5% allocation ($1,250), the budget was often insufficient to cover the premium of ATM spreads during the allowed VIX regimes.

Opportunity Cost: While the inactive strategies successfully avoided the -18% drawdown of 2022, they missed the +25% recovery in 2023 and the +24% momentum of 2024 captured by the SPY Benchmark.

Final Verdict

The current strategy is non-functional. To achieve the 80% return target, the strategy must shift from 'over-constrained' to 'opportunistic' by removing macro filters and increasing capital allocation per trade.

Next Steps

Increase position sizing to 10% ($2,500) to ensure high-priced spreads trigger.
Remove the VIX filter and replace it with a trend filter (e.g., Price > 50-day SMA).
Widen the DTE window to 15-60 days to improve contract matching.

Subagent 3: Refine the SPY and QQQ Iron Condor strategy from Round 1. Use an initialValue of $25,000. Test entry filters requiring VIX > 20. Test tiered stop-losses (15%, 20%, 25% of credit received) to reduce the historical 59% maximum drawdown to under 40%. Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ across all regimes.

Status: max_iterations_reached
Summary:
Iron Condor Optimization: From Zero-Trades to Bear-Market Alpha

This project aimed to design a high-growth (80% return) Iron Condor strategy for SPY and QQQ on a $25,000 account while keeping drawdowns under 40%.

Approach

We tested 19 portfolios across three regimes: 2022 (Bear), 2023-2024 (Bull), and 2025 (Current). Initial attempts using VIX-based entry filters (VIX > 15/20) failed to execute any trades, revealing a critical mismatch between restrictive volatility filters and backtester fill logic. We pivoted to an 'Always-On' baseline to verify the structure, which exposed the extreme vulnerability of symmetric Iron Condors to bull market 'melt-ups' (-83% return).

Key Discoveries

What Worked: The 'IC Trend - 25% Stop' emerged as a bear-market masterpiece, returning +90.67% in 2022 with a Sortino of 8.97 and a drawdown of only 12.3%. This proved that tight stop-losses (25% of credit) are the primary driver of risk-adjusted returns in high-volatility regimes.

The Bull Market Solution: To combat the 'Short Call Trap' of 2023-2024, we developed the 'IC Asymmetric - SMA 50 Filter'. By using conservative 10-delta calls against aggressive 25-delta puts, this was the only variation to survive the bull run profitably (+34.1%).

Next Steps

To reach the 80% return goal in all regimes, the Asymmetric model needs further refinement. Recommendations include testing a 'Trend-Exit' (closing calls when price > SMA 50) and tightening profit targets to 20% to increase turnover and win rate.

User

Create a portfolio named 'Round 2 Champion: Asymmetric Alpha' with an initialValue of $25,000.

Strategy 1 (Volatility Hedge): On SPY and QQQ, open an Asymmetric Iron Condor (Short 25-delta Puts / Short 10-delta Calls), 10-point wide spreads, 30-45 DTE. Allocation: 10% of buying power per underlying. Exit: Take profit at 40% of credit, Stop loss at 50% of credit.

Strategy 2 (Tech Momentum): On NVDA, META, and AMD, open a Bull Call Spread (Long 60-delta Call / Short 5% OTM Call), 30-45 DTE. Allocation: 10% of buying power per position. Entry condition: Price > 50-day SMA. Exit: Take profit at 60%, Stop loss at 50%.

This structure combines the bear-market resilience of asymmetric premium selling with the bull-market vertical alpha of tech leaders, using the sizing and filters identified by subagents as necessary for a $25k account.

Aurora

I have synthesized the findings from the subagents to create the Round 2 Champion: Asymmetric Alpha portfolio.

This structure addresses the two primary failure points identified in Round 1:

Execution Failure: By increasing allocation to 10% per position, we ensure the $25,000 account has enough buying power to actually fill spreads on high-priced tech leaders like META and NVDA.
Terminal Drawdown: By using Asymmetric Iron Condors (conservative calls vs. aggressive puts) and tight stop-losses (50% of credit/premium), we protect against the "melt-ups" and "flash crashes" that previously wiped out gains.

User

Backtest the 'Round 2 Champion: Asymmetric Alpha' portfolio (chatPortfolioId: 69d3760a401165fca52893a9) across four distinct market regimes:

2022 Bear Market: 2022-01-01 to 2022-12-31
2023 Recovery: 2023-01-01 to 2023-12-31
2024 Trend: 2024-01-01 to 2024-12-31
Current Regime: 2025-01-01 to 2026-04-06
Benchmark all tests against SPY with an initial value of $25,000.

Aurora

I'll create four backtest configurations for the Round 2 Champion: Asymmetric Alpha portfolio to evaluate its performance across the 2022 bear market, the 2023 recovery, the 2024 trend, and the current 2025-2026 regime.

User

Analyze the backtest results for the 'Round 2 Champion: Asymmetric Alpha' portfolio (chatPortfolioId: 69d3760a401165fca52893a9) for the following periods: 2022 (Bear), 2023 (Recovery), 2024 (Trend), and 2025-present (Current). Summarize the total return, max drawdown, and Sortino ratio for each period, and calculate the average annual return across all four regimes.

Aurora

The analysis of the Round 2 Champion: Asymmetric Alpha portfolio reveals that the strategy failed to meet the performance targets and significantly underperformed the SPY baseline in every tested regime.

1. Backtest Summary and Comparison

The following table compares the "Asymmetric Alpha" portfolio against the SPY baseline across four distinct market environments.

Period	Portfolio Return	SPY Return	Portfolio Max DD	SPY Max DD	Portfolio Sortino
2022 (Bear)	-74.77%	-18.38%	81.35%	24.50%	-1.61
2023 (Recovery)	-56.42%	+26.19%	64.37%	9.97%	-1.86
2024 (Trend)	-69.63%	+25.34%	73.63%	8.41%	-1.07
2025 (Current)	-57.30%	+8.74%	57.30%	18.76%	-1.86

2. Trends

Systemic Underperformance: The portfolio lost more than 50% of its value in every single regime, regardless of whether the broader market was in a bear trend (2022), a recovery (2023), or a strong bull trend (2024).
Terminal Drawdowns: The maximum drawdowns were consistently catastrophic, ranging from 57% to over 81%. This indicates that the risk management (stop-losses) did not prevent capital erosion but rather may have "locked in" losses during normal market volatility.
Negative Risk-Adjusted Returns: The Sortino ratios were negative in every period, meaning the strategy provided no compensation for the downside risk taken.
High Correlation to Losses: Even in years where SPY returned over 25%, the portfolio lost nearly 70%. This suggests the "Tech Momentum" bull call spreads were likely being stopped out prematurely or the "Volatility Hedge" iron condors were being overwhelmed by market moves.

3. Summary of Results

The "Round 2 Champion: Asymmetric Alpha" strategy is not viable in its current configuration for a $25,000 account. While the subagents attempted to solve the "zero trade" issue by increasing allocation to 10%, this higher concentration combined with the 50% stop-losses resulted in a "death by a thousand cuts" scenario. The portfolio effectively liquidated itself through consistent losses across all market conditions.

4. Performance Metrics & Average Annual Return

As requested, here are the aggregated metrics for the portfolio:

Average Annual Return: -64.53%
Worst Max Drawdown: 81.35% (2022)
Average Sortino Ratio: -1.60

Conclusion:
You should not use this strategy to double your account. Instead of growth, this portfolio resulted in a near-total loss of capital over the four-year period.

Recommendation for Optimization:
The current failure stems from the interaction between high-priced underlyings and tight stop-losses. I suggest optimizing a "Round 3: Capital Preservation" portfolio that:

Reduces the number of simultaneous strategies to focus on either the Volatility Hedge or the Tech Momentum, but not both at 10% allocation each.
Tests wider stop-losses (e.g., 100% of credit) to avoid being "chopped out" by noise.
Uses lower-priced ETFs (like XLK or XLF) instead of high-priced individual stocks like META to allow for better position sizing on a $25k account.

User

Launching 2 subagents to explore strategies in parallel

User

Waiting for subagents to complete...

User

Waiting for subagents to complete...

Aurora

All 5 subagents complete.

Subagent 1: Analyze the user's favorites watchlist (META, GOOG, NVDA, HOOD, LLY, AMD, AVGO, TSM, ANET, GS, DUOL, XOM, COP, POWL). Identify candidates currently in a mean-reversion zone (RSI < 40) or momentum breakout (RSI > 60). Create and backtest bull call spreads on mean-reversion names and long calls on momentum names. Use $25,000 initialValue, 2-3% position sizing, and backtest across 2022-2025 regimes to find a strategy averaging 80%+ return.

Status: completed
Summary:
RSI Options Strategy Analysis: 2022-2026 Performance Review

Designed and tested a dual-regime options strategy for a 14-stock watchlist (including NVDA, META, and LLY) to achieve an 80% average annual return. The approach combined RSI-based mean reversion (RSI < 40) using Bull Call Spreads and momentum breakouts (RSI > 60) using Long Calls and Spreads.

Research & Methodology

We analyzed 14 tickers for current RSI levels and historical signal frequency. Research revealed that while momentum signals (RSI > 60) are frequent in bull markets, mean reversion signals (RSI < 40) are rarer but potentially more potent. We implemented a $25,000 portfolio with 2.5% position sizing and strict 50% profit/30% loss exit rules.

Key Discoveries

The 2022 Edge: The strategy was a standout performer in the 2022 bear market, returning +35.83% while the SPY fell -18.38% (a +54% alpha). This suggests that RSI-based dip buying is a powerful defensive mechanism during high-volatility regimes.

Bull Market Failure: The strategy failed significantly in 2023, 2024, and 2025. The tight 30% stop loss caused the portfolio to be "chopped out" during healthy pullbacks in trending markets. Furthermore, the $25,000 account size proved to be a major constraint; high-priced stocks like LLY ($800+) often require more capital per contract than the 2.5% ($625) allocation allowed, leading to missed trades.

Quantitative Highlights

Best Period: 2022 (+35.83% Return, 1.23 Sortino)
Worst Period: 2025-2026 (-60.63% Return, -1.91 Sortino)
Average Annual Return: -22.96% (Failed 80% target)

Next Steps

To reach the 80% goal, the strategy requires optimization: 1) Add a Trend Filter (e.g., Price > 50-day SMA) to avoid buying "falling knives," 2) Widen Stop Losses to 50% for high-IV names, and 3) Increase Capital to $100k to ensure feasibility for high-priced tech leaders.

Subagent 2: Refine the META, NVDA, and AMD Bull Call Spread strategy from Round 1. Use an initialValue of $25,000. Implement a strict position sizing rule: max 2% of buying power per position. Add an entry filter for VIX < 20 to avoid high-volatility regimes. Test tight stop-losses (e.g., -20% to -30%). Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ and max drawdown under 40%.

Status: completed
Summary:
Strategy Refinement Report: META, NVDA, AMD Bull Call Spreads

Tested a volatility-aware Bull Call Spread strategy for a $25,000 account across four market regimes (2022-2025). The objective was to achieve an 80% annual return with a max drawdown under 40%.

Methodology

Conducted 28 backtests across 6 experimental portfolios and 1 benchmark. Variables tested included position sizing (2% vs 5%), VIX entry filters (<20 vs <25), and stop-loss levels (-20% to -30%). Research confirmed that while 5-point spreads on these tickers average ~$230, the combination of restrictive filters and high underlying prices created a total execution failure.

Key Discoveries

The Execution Desert: All 6 option portfolios returned 0 trades and 0% total return. The primary bottleneck was the interaction between the $25k account size and the high price of the underlyings (META ~$500, NVDA ~$130). Even at 5% allocation ($1,250), the budget was often insufficient to cover the premium of ATM spreads during the allowed VIX regimes.

Opportunity Cost: While the inactive strategies successfully avoided the -18% drawdown of 2022, they missed the +25% recovery in 2023 and the +24% momentum of 2024 captured by the SPY Benchmark.

Final Verdict

The current strategy is non-functional. To achieve the 80% return target, the strategy must shift from 'over-constrained' to 'opportunistic' by removing macro filters and increasing capital allocation per trade.

Next Steps

Increase position sizing to 10% ($2,500) to ensure high-priced spreads trigger.
Remove the VIX filter and replace it with a trend filter (e.g., Price > 50-day SMA).
Widen the DTE window to 15-60 days to improve contract matching.

Subagent 3: Research macro catalysts and earnings for the week of April 6, 2026. Identify if any of our target stocks (NVDA, META, AMD, SPY, QQQ) have high-impact events (Earnings, FOMC, CPI) that would make an options strategy particularly risky for Monday's open.

Status: completed
Summary:
Researched macro catalysts for the week of April 6, 2026, identifying the April 10 CPI release as the primary risk event. Technical analysis showed SPY and QQQ trading below their 200-day SMAs, signaling a bearish regime. We created and backtested 5 portfolios across three market eras (2022, 2023, 2024-25). Key findings: Macro IV Crush Condors provided massive alpha (+102.5%) in bear markets but lagged in bull trends. Directional debit spreads failed catastrophically when trading against the long-term SMA. The SPY Benchmark remains the most robust choice for the current trending environment, though Iron Condors offer a viable volatility play for the CPI event.

Subagent 4: Explore a 'Regime-Switching' options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. Regime A (SPY < 200 SMA): Trade Asymmetric Iron Condors on SPY and QQQ (Short 25-delta Puts / 10-delta Calls) with 10% allocation and 100% stop-loss (defined risk). Regime B (SPY > 200 SMA): Trade Bull Call Spreads on NVDA, META, and AMD with 10% allocation and 100% stop-loss. Backtest across 2022, 2023, 2024, and 2025. Goal: 80%+ avg annual return, <40% max drawdown.

Status: completed
Summary:
Regime-Switching Options Strategy Analysis: 13 Iterations Complete

Designed and tested a dual-regime options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. The goal was to achieve 80%+ annual returns with <40% max drawdown.

Approach

Tested 8 portfolios across four market regimes (2022-2025). Hypotheses focused on whether asymmetric Iron Condors (Regime A) and Tech Bull Call Spreads (Regime B) could meet the aggressive targets. We iterated through various delta levels, stop-loss thresholds (50%, 75%, 100%), and allocation sizes (5% vs 10%).

Key Discoveries

What Worked: The 'Regime-Switching Champion' configuration proved that moving to 100% Cash during downtrends (Regime A) is the only way to keep drawdowns under 40% for a small account. It achieved a 102.65% return in 2023 with only a 13.6% drawdown.

What Failed: Trading any multi-leg option strategy (ICs or Bear Spreads) when SPY was below the 200 SMA was disastrous. The 'Refined - Bear Regime A' portfolio resulted in a 100% wipeout. Additionally, high-conviction approaches without stop-losses ('Regime-Switching Alpha') suffered 80%+ drawdowns in 2024.

The Stop-Loss Paradox: Tighter stops (75%) protected capital in 2022 but caused the strategy to be "shaken out" of the 2024 rally, resulting in a -12% loss while the benchmark was up 25%.

Top Performers

Regime-Switching Champion - Best risk-adjusted balance (Sortino 3.92 in 2023).
Refined - Cash Regime A - Safest bear market performance (-27% return, -30% drawdown).

Next Steps

Optimize the 'Regime-Switching Champion' by testing a trailing stop-loss or a technical exit (e.g., RSI overbought) to avoid being stopped out of bull market rallies prematurely. Consider reducing the DTE exit rule from 7 days to 3 days to allow more time for trades to recover.

Subagent 5: Refine the SPY and QQQ Iron Condor strategy from Round 1. Use an initialValue of $25,000. Test entry filters requiring VIX > 20. Test tiered stop-losses (15%, 20%, 25% of credit received) to reduce the historical 59% maximum drawdown to under 40%. Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ across all regimes.

Status: max_iterations_reached
Summary:
Iron Condor Optimization: From Zero-Trades to Bear-Market Alpha

This project aimed to design a high-growth (80% return) Iron Condor strategy for SPY and QQQ on a $25,000 account while keeping drawdowns under 40%.

Approach

We tested 19 portfolios across three regimes: 2022 (Bear), 2023-2024 (Bull), and 2025 (Current). Initial attempts using VIX-based entry filters (VIX > 15/20) failed to execute any trades, revealing a critical mismatch between restrictive volatility filters and backtester fill logic. We pivoted to an 'Always-On' baseline to verify the structure, which exposed the extreme vulnerability of symmetric Iron Condors to bull market 'melt-ups' (-83% return).

Key Discoveries

What Worked: The 'IC Trend - 25% Stop' emerged as a bear-market masterpiece, returning +90.67% in 2022 with a Sortino of 8.97 and a drawdown of only 12.3%. This proved that tight stop-losses (25% of credit) are the primary driver of risk-adjusted returns in high-volatility regimes.

The Bull Market Solution: To combat the 'Short Call Trap' of 2023-2024, we developed the 'IC Asymmetric - SMA 50 Filter'. By using conservative 10-delta calls against aggressive 25-delta puts, this was the only variation to survive the bull run profitably (+34.1%).

Next Steps

To reach the 80% return goal in all regimes, the Asymmetric model needs further refinement. Recommendations include testing a 'Trend-Exit' (closing calls when price > SMA 50) and tightening profit targets to 20% to increase turnover and win rate.

User

Waiting for subagents to complete...

Aurora

All 5 subagents complete.

Subagent 1: Analyze the user's favorites watchlist (META, GOOG, NVDA, HOOD, LLY, AMD, AVGO, TSM, ANET, GS, DUOL, XOM, COP, POWL). Identify candidates currently in a mean-reversion zone (RSI < 40) or momentum breakout (RSI > 60). Create and backtest bull call spreads on mean-reversion names and long calls on momentum names. Use $25,000 initialValue, 2-3% position sizing, and backtest across 2022-2025 regimes to find a strategy averaging 80%+ return.

Status: completed
Summary:
RSI Options Strategy Analysis: 2022-2026 Performance Review

Designed and tested a dual-regime options strategy for a 14-stock watchlist (including NVDA, META, and LLY) to achieve an 80% average annual return. The approach combined RSI-based mean reversion (RSI < 40) using Bull Call Spreads and momentum breakouts (RSI > 60) using Long Calls and Spreads.

Research & Methodology

We analyzed 14 tickers for current RSI levels and historical signal frequency. Research revealed that while momentum signals (RSI > 60) are frequent in bull markets, mean reversion signals (RSI < 40) are rarer but potentially more potent. We implemented a $25,000 portfolio with 2.5% position sizing and strict 50% profit/30% loss exit rules.

Key Discoveries

The 2022 Edge: The strategy was a standout performer in the 2022 bear market, returning +35.83% while the SPY fell -18.38% (a +54% alpha). This suggests that RSI-based dip buying is a powerful defensive mechanism during high-volatility regimes.

Bull Market Failure: The strategy failed significantly in 2023, 2024, and 2025. The tight 30% stop loss caused the portfolio to be "chopped out" during healthy pullbacks in trending markets. Furthermore, the $25,000 account size proved to be a major constraint; high-priced stocks like LLY ($800+) often require more capital per contract than the 2.5% ($625) allocation allowed, leading to missed trades.

Quantitative Highlights

Best Period: 2022 (+35.83% Return, 1.23 Sortino)
Worst Period: 2025-2026 (-60.63% Return, -1.91 Sortino)
Average Annual Return: -22.96% (Failed 80% target)

Next Steps

To reach the 80% goal, the strategy requires optimization: 1) Add a Trend Filter (e.g., Price > 50-day SMA) to avoid buying "falling knives," 2) Widen Stop Losses to 50% for high-IV names, and 3) Increase Capital to $100k to ensure feasibility for high-priced tech leaders.

Subagent 2: Refine the META, NVDA, and AMD Bull Call Spread strategy from Round 1. Use an initialValue of $25,000. Implement a strict position sizing rule: max 2% of buying power per position. Add an entry filter for VIX < 20 to avoid high-volatility regimes. Test tight stop-losses (e.g., -20% to -30%). Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ and max drawdown under 40%.

Status: completed
Summary:
Strategy Refinement Report: META, NVDA, AMD Bull Call Spreads

Tested a volatility-aware Bull Call Spread strategy for a $25,000 account across four market regimes (2022-2025). The objective was to achieve an 80% annual return with a max drawdown under 40%.

Methodology

Conducted 28 backtests across 6 experimental portfolios and 1 benchmark. Variables tested included position sizing (2% vs 5%), VIX entry filters (<20 vs <25), and stop-loss levels (-20% to -30%). Research confirmed that while 5-point spreads on these tickers average ~$230, the combination of restrictive filters and high underlying prices created a total execution failure.

Key Discoveries

The Execution Desert: All 6 option portfolios returned 0 trades and 0% total return. The primary bottleneck was the interaction between the $25k account size and the high price of the underlyings (META ~$500, NVDA ~$130). Even at 5% allocation ($1,250), the budget was often insufficient to cover the premium of ATM spreads during the allowed VIX regimes.

Opportunity Cost: While the inactive strategies successfully avoided the -18% drawdown of 2022, they missed the +25% recovery in 2023 and the +24% momentum of 2024 captured by the SPY Benchmark.

Final Verdict

The current strategy is non-functional. To achieve the 80% return target, the strategy must shift from 'over-constrained' to 'opportunistic' by removing macro filters and increasing capital allocation per trade.

Next Steps

Increase position sizing to 10% ($2,500) to ensure high-priced spreads trigger.
Remove the VIX filter and replace it with a trend filter (e.g., Price > 50-day SMA).
Widen the DTE window to 15-60 days to improve contract matching.

Subagent 3: Research macro catalysts and earnings for the week of April 6, 2026. Identify if any of our target stocks (NVDA, META, AMD, SPY, QQQ) have high-impact events (Earnings, FOMC, CPI) that would make an options strategy particularly risky for Monday's open.

Status: completed
Summary:
Researched macro catalysts for the week of April 6, 2026, identifying the April 10 CPI release as the primary risk event. Technical analysis showed SPY and QQQ trading below their 200-day SMAs, signaling a bearish regime. We created and backtested 5 portfolios across three market eras (2022, 2023, 2024-25). Key findings: Macro IV Crush Condors provided massive alpha (+102.5%) in bear markets but lagged in bull trends. Directional debit spreads failed catastrophically when trading against the long-term SMA. The SPY Benchmark remains the most robust choice for the current trending environment, though Iron Condors offer a viable volatility play for the CPI event.

Subagent 4: Explore a 'Regime-Switching' options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. Regime A (SPY < 200 SMA): Trade Asymmetric Iron Condors on SPY and QQQ (Short 25-delta Puts / 10-delta Calls) with 10% allocation and 100% stop-loss (defined risk). Regime B (SPY > 200 SMA): Trade Bull Call Spreads on NVDA, META, and AMD with 10% allocation and 100% stop-loss. Backtest across 2022, 2023, 2024, and 2025. Goal: 80%+ avg annual return, <40% max drawdown.

Status: completed
Summary:
Regime-Switching Options Strategy Analysis: 13 Iterations Complete

Designed and tested a dual-regime options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. The goal was to achieve 80%+ annual returns with <40% max drawdown.

Approach

Tested 8 portfolios across four market regimes (2022-2025). Hypotheses focused on whether asymmetric Iron Condors (Regime A) and Tech Bull Call Spreads (Regime B) could meet the aggressive targets. We iterated through various delta levels, stop-loss thresholds (50%, 75%, 100%), and allocation sizes (5% vs 10%).

Key Discoveries

What Worked: The 'Regime-Switching Champion' configuration proved that moving to 100% Cash during downtrends (Regime A) is the only way to keep drawdowns under 40% for a small account. It achieved a 102.65% return in 2023 with only a 13.6% drawdown.

What Failed: Trading any multi-leg option strategy (ICs or Bear Spreads) when SPY was below the 200 SMA was disastrous. The 'Refined - Bear Regime A' portfolio resulted in a 100% wipeout. Additionally, high-conviction approaches without stop-losses ('Regime-Switching Alpha') suffered 80%+ drawdowns in 2024.

The Stop-Loss Paradox: Tighter stops (75%) protected capital in 2022 but caused the strategy to be "shaken out" of the 2024 rally, resulting in a -12% loss while the benchmark was up 25%.

Top Performers

Regime-Switching Champion - Best risk-adjusted balance (Sortino 3.92 in 2023).
Refined - Cash Regime A - Safest bear market performance (-27% return, -30% drawdown).

Next Steps

Optimize the 'Regime-Switching Champion' by testing a trailing stop-loss or a technical exit (e.g., RSI overbought) to avoid being stopped out of bull market rallies prematurely. Consider reducing the DTE exit rule from 7 days to 3 days to allow more time for trades to recover.

Subagent 5: Refine the SPY and QQQ Iron Condor strategy from Round 1. Use an initialValue of $25,000. Test entry filters requiring VIX > 20. Test tiered stop-losses (15%, 20%, 25% of credit received) to reduce the historical 59% maximum drawdown to under 40%. Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ across all regimes.

Status: max_iterations_reached
Summary:
Iron Condor Optimization: From Zero-Trades to Bear-Market Alpha

This project aimed to design a high-growth (80% return) Iron Condor strategy for SPY and QQQ on a $25,000 account while keeping drawdowns under 40%.

Approach

We tested 19 portfolios across three regimes: 2022 (Bear), 2023-2024 (Bull), and 2025 (Current). Initial attempts using VIX-based entry filters (VIX > 15/20) failed to execute any trades, revealing a critical mismatch between restrictive volatility filters and backtester fill logic. We pivoted to an 'Always-On' baseline to verify the structure, which exposed the extreme vulnerability of symmetric Iron Condors to bull market 'melt-ups' (-83% return).

Key Discoveries

What Worked: The 'IC Trend - 25% Stop' emerged as a bear-market masterpiece, returning +90.67% in 2022 with a Sortino of 8.97 and a drawdown of only 12.3%. This proved that tight stop-losses (25% of credit) are the primary driver of risk-adjusted returns in high-volatility regimes.

The Bull Market Solution: To combat the 'Short Call Trap' of 2023-2024, we developed the 'IC Asymmetric - SMA 50 Filter'. By using conservative 10-delta calls against aggressive 25-delta puts, this was the only variation to survive the bull run profitably (+34.1%).

Next Steps

To reach the 80% return goal in all regimes, the Asymmetric model needs further refinement. Recommendations include testing a 'Trend-Exit' (closing calls when price > SMA 50) and tightening profit targets to 20% to increase turnover and win rate.

User

Waiting for subagents to complete...

Aurora

All 5 subagents complete.

Subagent 1: Analyze the user's favorites watchlist (META, GOOG, NVDA, HOOD, LLY, AMD, AVGO, TSM, ANET, GS, DUOL, XOM, COP, POWL). Identify candidates currently in a mean-reversion zone (RSI < 40) or momentum breakout (RSI > 60). Create and backtest bull call spreads on mean-reversion names and long calls on momentum names. Use $25,000 initialValue, 2-3% position sizing, and backtest across 2022-2025 regimes to find a strategy averaging 80%+ return.

Status: completed
Summary:
RSI Options Strategy Analysis: 2022-2026 Performance Review

Designed and tested a dual-regime options strategy for a 14-stock watchlist (including NVDA, META, and LLY) to achieve an 80% average annual return. The approach combined RSI-based mean reversion (RSI < 40) using Bull Call Spreads and momentum breakouts (RSI > 60) using Long Calls and Spreads.

Research & Methodology

We analyzed 14 tickers for current RSI levels and historical signal frequency. Research revealed that while momentum signals (RSI > 60) are frequent in bull markets, mean reversion signals (RSI < 40) are rarer but potentially more potent. We implemented a $25,000 portfolio with 2.5% position sizing and strict 50% profit/30% loss exit rules.

Key Discoveries

The 2022 Edge: The strategy was a standout performer in the 2022 bear market, returning +35.83% while the SPY fell -18.38% (a +54% alpha). This suggests that RSI-based dip buying is a powerful defensive mechanism during high-volatility regimes.

Bull Market Failure: The strategy failed significantly in 2023, 2024, and 2025. The tight 30% stop loss caused the portfolio to be "chopped out" during healthy pullbacks in trending markets. Furthermore, the $25,000 account size proved to be a major constraint; high-priced stocks like LLY ($800+) often require more capital per contract than the 2.5% ($625) allocation allowed, leading to missed trades.

Quantitative Highlights

Best Period: 2022 (+35.83% Return, 1.23 Sortino)
Worst Period: 2025-2026 (-60.63% Return, -1.91 Sortino)
Average Annual Return: -22.96% (Failed 80% target)

Next Steps

To reach the 80% goal, the strategy requires optimization: 1) Add a Trend Filter (e.g., Price > 50-day SMA) to avoid buying "falling knives," 2) Widen Stop Losses to 50% for high-IV names, and 3) Increase Capital to $100k to ensure feasibility for high-priced tech leaders.

Subagent 2: Refine the META, NVDA, and AMD Bull Call Spread strategy from Round 1. Use an initialValue of $25,000. Implement a strict position sizing rule: max 2% of buying power per position. Add an entry filter for VIX < 20 to avoid high-volatility regimes. Test tight stop-losses (e.g., -20% to -30%). Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ and max drawdown under 40%.

Status: completed
Summary:
Strategy Refinement Report: META, NVDA, AMD Bull Call Spreads

Tested a volatility-aware Bull Call Spread strategy for a $25,000 account across four market regimes (2022-2025). The objective was to achieve an 80% annual return with a max drawdown under 40%.

Methodology

Conducted 28 backtests across 6 experimental portfolios and 1 benchmark. Variables tested included position sizing (2% vs 5%), VIX entry filters (<20 vs <25), and stop-loss levels (-20% to -30%). Research confirmed that while 5-point spreads on these tickers average ~$230, the combination of restrictive filters and high underlying prices created a total execution failure.

Key Discoveries

The Execution Desert: All 6 option portfolios returned 0 trades and 0% total return. The primary bottleneck was the interaction between the $25k account size and the high price of the underlyings (META ~$500, NVDA ~$130). Even at 5% allocation ($1,250), the budget was often insufficient to cover the premium of ATM spreads during the allowed VIX regimes.

Opportunity Cost: While the inactive strategies successfully avoided the -18% drawdown of 2022, they missed the +25% recovery in 2023 and the +24% momentum of 2024 captured by the SPY Benchmark.

Final Verdict

The current strategy is non-functional. To achieve the 80% return target, the strategy must shift from 'over-constrained' to 'opportunistic' by removing macro filters and increasing capital allocation per trade.

Next Steps

Increase position sizing to 10% ($2,500) to ensure high-priced spreads trigger.
Remove the VIX filter and replace it with a trend filter (e.g., Price > 50-day SMA).
Widen the DTE window to 15-60 days to improve contract matching.

Subagent 3: Research macro catalysts and earnings for the week of April 6, 2026. Identify if any of our target stocks (NVDA, META, AMD, SPY, QQQ) have high-impact events (Earnings, FOMC, CPI) that would make an options strategy particularly risky for Monday's open.

Status: completed
Summary:
Researched macro catalysts for the week of April 6, 2026, identifying the April 10 CPI release as the primary risk event. Technical analysis showed SPY and QQQ trading below their 200-day SMAs, signaling a bearish regime. We created and backtested 5 portfolios across three market eras (2022, 2023, 2024-25). Key findings: Macro IV Crush Condors provided massive alpha (+102.5%) in bear markets but lagged in bull trends. Directional debit spreads failed catastrophically when trading against the long-term SMA. The SPY Benchmark remains the most robust choice for the current trending environment, though Iron Condors offer a viable volatility play for the CPI event.

Subagent 4: Explore a 'Regime-Switching' options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. Regime A (SPY < 200 SMA): Trade Asymmetric Iron Condors on SPY and QQQ (Short 25-delta Puts / 10-delta Calls) with 10% allocation and 100% stop-loss (defined risk). Regime B (SPY > 200 SMA): Trade Bull Call Spreads on NVDA, META, and AMD with 10% allocation and 100% stop-loss. Backtest across 2022, 2023, 2024, and 2025. Goal: 80%+ avg annual return, <40% max drawdown.

Status: completed
Summary:
Regime-Switching Options Strategy Analysis: 13 Iterations Complete

Designed and tested a dual-regime options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. The goal was to achieve 80%+ annual returns with <40% max drawdown.

Approach

Tested 8 portfolios across four market regimes (2022-2025). Hypotheses focused on whether asymmetric Iron Condors (Regime A) and Tech Bull Call Spreads (Regime B) could meet the aggressive targets. We iterated through various delta levels, stop-loss thresholds (50%, 75%, 100%), and allocation sizes (5% vs 10%).

Key Discoveries

What Worked: The 'Regime-Switching Champion' configuration proved that moving to 100% Cash during downtrends (Regime A) is the only way to keep drawdowns under 40% for a small account. It achieved a 102.65% return in 2023 with only a 13.6% drawdown.

What Failed: Trading any multi-leg option strategy (ICs or Bear Spreads) when SPY was below the 200 SMA was disastrous. The 'Refined - Bear Regime A' portfolio resulted in a 100% wipeout. Additionally, high-conviction approaches without stop-losses ('Regime-Switching Alpha') suffered 80%+ drawdowns in 2024.

The Stop-Loss Paradox: Tighter stops (75%) protected capital in 2022 but caused the strategy to be "shaken out" of the 2024 rally, resulting in a -12% loss while the benchmark was up 25%.

Top Performers

Regime-Switching Champion - Best risk-adjusted balance (Sortino 3.92 in 2023).
Refined - Cash Regime A - Safest bear market performance (-27% return, -30% drawdown).

Next Steps

Optimize the 'Regime-Switching Champion' by testing a trailing stop-loss or a technical exit (e.g., RSI overbought) to avoid being stopped out of bull market rallies prematurely. Consider reducing the DTE exit rule from 7 days to 3 days to allow more time for trades to recover.

Subagent 5: Refine the SPY and QQQ Iron Condor strategy from Round 1. Use an initialValue of $25,000. Test entry filters requiring VIX > 20. Test tiered stop-losses (15%, 20%, 25% of credit received) to reduce the historical 59% maximum drawdown to under 40%. Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ across all regimes.

Status: max_iterations_reached
Summary:
Iron Condor Optimization: From Zero-Trades to Bear-Market Alpha

This project aimed to design a high-growth (80% return) Iron Condor strategy for SPY and QQQ on a $25,000 account while keeping drawdowns under 40%.

Approach

We tested 19 portfolios across three regimes: 2022 (Bear), 2023-2024 (Bull), and 2025 (Current). Initial attempts using VIX-based entry filters (VIX > 15/20) failed to execute any trades, revealing a critical mismatch between restrictive volatility filters and backtester fill logic. We pivoted to an 'Always-On' baseline to verify the structure, which exposed the extreme vulnerability of symmetric Iron Condors to bull market 'melt-ups' (-83% return).

Key Discoveries

What Worked: The 'IC Trend - 25% Stop' emerged as a bear-market masterpiece, returning +90.67% in 2022 with a Sortino of 8.97 and a drawdown of only 12.3%. This proved that tight stop-losses (25% of credit) are the primary driver of risk-adjusted returns in high-volatility regimes.

The Bull Market Solution: To combat the 'Short Call Trap' of 2023-2024, we developed the 'IC Asymmetric - SMA 50 Filter'. By using conservative 10-delta calls against aggressive 25-delta puts, this was the only variation to survive the bull run profitably (+34.1%).

Next Steps

To reach the 80% return goal in all regimes, the Asymmetric model needs further refinement. Recommendations include testing a 'Trend-Exit' (closing calls when price > SMA 50) and tightening profit targets to 20% to increase turnover and win rate.

User

Waiting for subagents to complete...

Aurora

All 5 subagents complete.

Subagent 1: Analyze the user's favorites watchlist (META, GOOG, NVDA, HOOD, LLY, AMD, AVGO, TSM, ANET, GS, DUOL, XOM, COP, POWL). Identify candidates currently in a mean-reversion zone (RSI < 40) or momentum breakout (RSI > 60). Create and backtest bull call spreads on mean-reversion names and long calls on momentum names. Use $25,000 initialValue, 2-3% position sizing, and backtest across 2022-2025 regimes to find a strategy averaging 80%+ return.

Status: completed
Summary:
RSI Options Strategy Analysis: 2022-2026 Performance Review

Designed and tested a dual-regime options strategy for a 14-stock watchlist (including NVDA, META, and LLY) to achieve an 80% average annual return. The approach combined RSI-based mean reversion (RSI < 40) using Bull Call Spreads and momentum breakouts (RSI > 60) using Long Calls and Spreads.

Research & Methodology

We analyzed 14 tickers for current RSI levels and historical signal frequency. Research revealed that while momentum signals (RSI > 60) are frequent in bull markets, mean reversion signals (RSI < 40) are rarer but potentially more potent. We implemented a $25,000 portfolio with 2.5% position sizing and strict 50% profit/30% loss exit rules.

Key Discoveries

The 2022 Edge: The strategy was a standout performer in the 2022 bear market, returning +35.83% while the SPY fell -18.38% (a +54% alpha). This suggests that RSI-based dip buying is a powerful defensive mechanism during high-volatility regimes.

Bull Market Failure: The strategy failed significantly in 2023, 2024, and 2025. The tight 30% stop loss caused the portfolio to be "chopped out" during healthy pullbacks in trending markets. Furthermore, the $25,000 account size proved to be a major constraint; high-priced stocks like LLY ($800+) often require more capital per contract than the 2.5% ($625) allocation allowed, leading to missed trades.

Quantitative Highlights

Best Period: 2022 (+35.83% Return, 1.23 Sortino)
Worst Period: 2025-2026 (-60.63% Return, -1.91 Sortino)
Average Annual Return: -22.96% (Failed 80% target)

Next Steps

To reach the 80% goal, the strategy requires optimization: 1) Add a Trend Filter (e.g., Price > 50-day SMA) to avoid buying "falling knives," 2) Widen Stop Losses to 50% for high-IV names, and 3) Increase Capital to $100k to ensure feasibility for high-priced tech leaders.

Subagent 2: Refine the META, NVDA, and AMD Bull Call Spread strategy from Round 1. Use an initialValue of $25,000. Implement a strict position sizing rule: max 2% of buying power per position. Add an entry filter for VIX < 20 to avoid high-volatility regimes. Test tight stop-losses (e.g., -20% to -30%). Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ and max drawdown under 40%.

Status: completed
Summary:
Strategy Refinement Report: META, NVDA, AMD Bull Call Spreads

Tested a volatility-aware Bull Call Spread strategy for a $25,000 account across four market regimes (2022-2025). The objective was to achieve an 80% annual return with a max drawdown under 40%.

Methodology

Conducted 28 backtests across 6 experimental portfolios and 1 benchmark. Variables tested included position sizing (2% vs 5%), VIX entry filters (<20 vs <25), and stop-loss levels (-20% to -30%). Research confirmed that while 5-point spreads on these tickers average ~$230, the combination of restrictive filters and high underlying prices created a total execution failure.

Key Discoveries

The Execution Desert: All 6 option portfolios returned 0 trades and 0% total return. The primary bottleneck was the interaction between the $25k account size and the high price of the underlyings (META ~$500, NVDA ~$130). Even at 5% allocation ($1,250), the budget was often insufficient to cover the premium of ATM spreads during the allowed VIX regimes.

Opportunity Cost: While the inactive strategies successfully avoided the -18% drawdown of 2022, they missed the +25% recovery in 2023 and the +24% momentum of 2024 captured by the SPY Benchmark.

Final Verdict

The current strategy is non-functional. To achieve the 80% return target, the strategy must shift from 'over-constrained' to 'opportunistic' by removing macro filters and increasing capital allocation per trade.

Next Steps

Increase position sizing to 10% ($2,500) to ensure high-priced spreads trigger.
Remove the VIX filter and replace it with a trend filter (e.g., Price > 50-day SMA).
Widen the DTE window to 15-60 days to improve contract matching.

Subagent 3: Research macro catalysts and earnings for the week of April 6, 2026. Identify if any of our target stocks (NVDA, META, AMD, SPY, QQQ) have high-impact events (Earnings, FOMC, CPI) that would make an options strategy particularly risky for Monday's open.

Status: completed
Summary:
Researched macro catalysts for the week of April 6, 2026, identifying the April 10 CPI release as the primary risk event. Technical analysis showed SPY and QQQ trading below their 200-day SMAs, signaling a bearish regime. We created and backtested 5 portfolios across three market eras (2022, 2023, 2024-25). Key findings: Macro IV Crush Condors provided massive alpha (+102.5%) in bear markets but lagged in bull trends. Directional debit spreads failed catastrophically when trading against the long-term SMA. The SPY Benchmark remains the most robust choice for the current trending environment, though Iron Condors offer a viable volatility play for the CPI event.

Subagent 4: Explore a 'Regime-Switching' options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. Regime A (SPY < 200 SMA): Trade Asymmetric Iron Condors on SPY and QQQ (Short 25-delta Puts / 10-delta Calls) with 10% allocation and 100% stop-loss (defined risk). Regime B (SPY > 200 SMA): Trade Bull Call Spreads on NVDA, META, and AMD with 10% allocation and 100% stop-loss. Backtest across 2022, 2023, 2024, and 2025. Goal: 80%+ avg annual return, <40% max drawdown.

Status: completed
Summary:
Regime-Switching Options Strategy Analysis: 13 Iterations Complete

Designed and tested a dual-regime options strategy for a $25,000 account using the SPY 200-day SMA as a master switch. The goal was to achieve 80%+ annual returns with <40% max drawdown.

Approach

Tested 8 portfolios across four market regimes (2022-2025). Hypotheses focused on whether asymmetric Iron Condors (Regime A) and Tech Bull Call Spreads (Regime B) could meet the aggressive targets. We iterated through various delta levels, stop-loss thresholds (50%, 75%, 100%), and allocation sizes (5% vs 10%).

Key Discoveries

What Worked: The 'Regime-Switching Champion' configuration proved that moving to 100% Cash during downtrends (Regime A) is the only way to keep drawdowns under 40% for a small account. It achieved a 102.65% return in 2023 with only a 13.6% drawdown.

What Failed: Trading any multi-leg option strategy (ICs or Bear Spreads) when SPY was below the 200 SMA was disastrous. The 'Refined - Bear Regime A' portfolio resulted in a 100% wipeout. Additionally, high-conviction approaches without stop-losses ('Regime-Switching Alpha') suffered 80%+ drawdowns in 2024.

The Stop-Loss Paradox: Tighter stops (75%) protected capital in 2022 but caused the strategy to be "shaken out" of the 2024 rally, resulting in a -12% loss while the benchmark was up 25%.

Top Performers

Regime-Switching Champion - Best risk-adjusted balance (Sortino 3.92 in 2023).
Refined - Cash Regime A - Safest bear market performance (-27% return, -30% drawdown).

Next Steps

Optimize the 'Regime-Switching Champion' by testing a trailing stop-loss or a technical exit (e.g., RSI overbought) to avoid being stopped out of bull market rallies prematurely. Consider reducing the DTE exit rule from 7 days to 3 days to allow more time for trades to recover.

Subagent 5: Refine the SPY and QQQ Iron Condor strategy from Round 1. Use an initialValue of $25,000. Test entry filters requiring VIX > 20. Test tiered stop-losses (15%, 20%, 25% of credit received) to reduce the historical 59% maximum drawdown to under 40%. Backtest across 2022, 2023, 2024, and 2025-present. Aim for an average annual return of 80%+ across all regimes.

Status: max_iterations_reached
Summary:
Iron Condor Optimization: From Zero-Trades to Bear-Market Alpha

This project aimed to design a high-growth (80% return) Iron Condor strategy for SPY and QQQ on a $25,000 account while keeping drawdowns under 40%.

Approach

We tested 19 portfolios across three regimes: 2022 (Bear), 2023-2024 (Bull), and 2025 (Current). Initial attempts using VIX-based entry filters (VIX > 15/20) failed to execute any trades, revealing a critical mismatch between restrictive volatility filters and backtester fill logic. We pivoted to an 'Always-On' baseline to verify the structure, which exposed the extreme vulnerability of symmetric Iron Condors to bull market 'melt-ups' (-83% return).

Key Discoveries

What Worked: The 'IC Trend - 25% Stop' emerged as a bear-market masterpiece, returning +90.67% in 2022 with a Sortino of 8.97 and a drawdown of only 12.3%. This proved that tight stop-losses (25% of credit) are the primary driver of risk-adjusted returns in high-volatility regimes.

The Bull Market Solution: To combat the 'Short Call Trap' of 2023-2024, we developed the 'IC Asymmetric - SMA 50 Filter'. By using conservative 10-delta calls against aggressive 25-delta puts, this was the only variation to survive the bull run profitably (+34.1%).

Next Steps

To reach the 80% return goal in all regimes, the Asymmetric model needs further refinement. Recommendations include testing a 'Trend-Exit' (closing calls when price > SMA 50) and tightening profit targets to 20% to increase turnover and win rate.

User

Create a portfolio named 'Round 2 Hybrid: Regime Master' with an initialValue of $25,000.

Strategy 1 (Bear Regime): When Price(SPY) < SimpleMovingAverage(SPY, 200), open an Iron Condor on SPY and QQQ (Short 5% OTM / Long 8% OTM), 7-10 DTE. Allocation: 15% of buying power per underlying. Entry: Mondays at open. Exit: Take profit at 50% of credit, Stop loss at 50% of credit.

Strategy 2 (Bull Regime): When Price(SPY) > SimpleMovingAverage(SPY, 200), open a Bull Call Spread on NVDA, META, and AMD (Long 70-delta Call / Short 50-delta Call), 30-45 DTE. Allocation: 10% of buying power per position. Exit: Take profit at 60%, Stop loss at 50%.

This hybrid strategy uses the bear-market alpha of IV-crush condors (+102% in 2022) and the bull-market vertical alpha of tech leaders (+102% in 2023), gated by the 200-day SMA trend filter.

User

Backtest the 'Round 2 Hybrid: Regime Master' portfolio (chatPortfolioId: 69d38385401165fca52bc083) across four regimes:

2022 Bear Market: 2022-01-01 to 2022-12-31
2023 Recovery: 2023-01-01 to 2023-12-31
2024 Trend: 2024-01-01 to 2024-12-31
Current Regime: 2025-01-01 to 2026-04-06
Benchmark against SPY with an initial value of $25,000.

Aurora

I'll create the backtest configurations for the Round 2 Hybrid: Regime Master portfolio across the four requested market regimes.

Since your strategies include time-specific execution rules ("Minutes After Market Open < 30"), I have set the backtest interval to Minute to ensure accurate simulation of Monday morning entries. Because intraday backtests are limited to 1-year durations, I have split the "Current Regime" (2025–2026) into two separate configurations.

User

Analyze the backtest results for the 'Round 2 Hybrid: Regime Master' portfolio (chatPortfolioId: 69d38385401165fca52bc083) for the periods 2022 (Bear), 2023 (Recovery), 2024 (Trend), and 2025-present (Current). Summarize the total return, max drawdown, and Sortino ratio for each period, and calculate the average annual return across all regimes.

Aurora

The analysis of the Round 2 Champion: Asymmetric Alpha and Round 2 Hybrid: Regime Master portfolios shows that both strategies failed to meet your performance targets and significantly underperformed the SPY baseline across all tested regimes.

1. Backtest Summary and Comparison

The following table summarizes the performance of both portfolios against the SPY baseline.

Backtest Period	Portfolio Name	Portfolio Return	SPY Return	Max Drawdown	Sortino Ratio
2022 (Bear)	Asymmetric Alpha	-74.77%	-18.38%	81.35%	-1.61
2022 (Bear)	Regime Master	-44.72%	-18.40%	50.67%	-1.53
2023 (Recovery)	Asymmetric Alpha	-56.42%	+26.19%	64.37%	-1.86
2023 (Recovery)	Regime Master	-59.63%	+26.19%	71.14%	-0.72
2024 (Trend)	Asymmetric Alpha	-69.63%	+25.34%	73.63%	-1.07
2024 (Trend)	Regime Master	-45.64%	+25.24%	55.85%	-1.57
2025 (Full Year)	Regime Master	-63.14%	+17.84%	67.72%	-0.14
2025-26 (Current)	Asymmetric Alpha	-57.30%	+8.74%	57.30%	-1.86
2026 (YTD)	Regime Master	-3.66%	-7.66%	31.14%	0.34

2. Trends

Terminal Capital Erosion: Both portfolios suffered from "death by a thousand cuts." Despite win rates often exceeding 50%, the average trade return was deeply negative (e.g., -101% for Regime Master in 2022). This indicates that when the 50% stop-loss was hit, it wiped out multiple winning trades.
Regime Master's Defensive Spark: The only period of outperformance occurred in the 2026 YTD period, where the Regime Master lost -3.66% compared to SPY's -7.66%. This suggests the Bear Regime (Iron Condors) provided some protection during the recent downturn, but not enough to offset previous years' losses.
Concentration Risk: The 10-15% allocation per position proved too aggressive for a $25,000 account. A few consecutive losses at these sizing levels created drawdowns from which the account could not mathematically recover.

3. Summary of Results

The strategies are currently non-viable for your goal of doubling a $25,000 account.

Asymmetric Alpha Average Annual Return: -64.53%
Regime Master Average Annual Return: -53.28% (excluding partial 2026)
Max Drawdown: Both portfolios exceeded the 40% limit in every full-year test, reaching as high as 81.35%.

The "Asymmetric" and "Regime-Switching" logic, while theoretically sound, was undermined by the interaction between high-priced tech stocks (META, NVDA) and tight stop-losses. The portfolio was essentially "shaken out" of every major rally while capturing the full brunt of every pullback.

4. How is this portfolio? (Answering your question)

In its current state, this portfolio is high-risk and low-reward.

It failed to achieve the 80% return target and violated the 40% drawdown limit significantly. You should not live-trade this configuration. The data suggests that the current stop-loss levels (50%) are too tight for the volatility of the underlying assets, and the position sizing (10-15%) is too large for a $25,000 account to survive the variance of options trading.

Optimization Suggestion

I recommend we move to Optimization Round 3, focusing exclusively on the Regime Master portfolio. We should optimize the following parameters:

Position Sizing: Reduce allocation to 3-5% to ensure the account can survive a string of losses.
Stop-Loss: Test wider stop-losses (e.g., 100% or 150% of credit) or remove them entirely for the defined-risk spreads to allow the trades room to breathe.
Underlying Selection: Replace high-priced individual stocks with lower-volatility ETFs (like XLK or SMH) to reduce the impact of single-stock "gap downs."

Would you like me to begin the Round 3 optimization with these adjustments?

User

Create an options portfolio named 'Round 2 Final: Sovereign Alpha' with an initialValue of $25,000.

Strategy 1 (Bear Regime - IV Crush): When Price(SPY) < SimpleMovingAverage(SPY, 200), open an Iron Condor on SPY and QQQ. Short legs at 5% OTM, Long legs at 8% OTM. 7-10 Days to Expiration (DTE). Allocation: 15% of buying power per underlying. Entry: Mondays at open (Day 1). Exit: Take profit at 50% of credit received, Stop loss at 50% of credit received. Max 1 spread per underlying.

Strategy 2 (Bull Regime - Tech Alpha): When Price(SPY) > SimpleMovingAverage(SPY, 200), open a Bull Call Spread on NVDA, META, and AMD. Long leg at 70-delta, Short leg at 50-delta. 30-45 Days to Expiration (DTE). Allocation: 5% of buying power per position. Exit: Take profit at 75% of premium paid, Stop loss at 75% of premium paid. Exit if DTE <= 7. Max 1 spread per underlying.

This hybrid strategy combines the 102% Bear-market alpha of IV-crush condors with the 102% Bull-market alpha of tech vertical spreads, using the 5-15% sizing and 75% risk targets identified by subagents as optimal for a $25k account.

User

Backtest the 'Round 2 Final: Sovereign Alpha' portfolio (chatPortfolioId: 69d39156401165fca52ec364) across four market regimes:

2022 Bear Market: 2022-01-01 to 2022-12-31
2023 Recovery: 2023-01-01 to 2023-12-31
2024 Trend: 2024-01-01 to 2024-12-31
Current Regime: 2025-01-01 to 2026-04-06
Benchmark all tests against SPY with an initial value of $25,000.

Aurora

I'll create backtest configurations for the Round 2 Final: Sovereign Alpha portfolio across the four requested market regimes.

Since the strategy uses intraday timing ("Minutes After Market Open"), I have set the interval to Minute. Because intraday backtests are limited to 1-year durations, I have split the 2025–2026 period into two separate runs.

User

Analyze the backtest results for the 'Round 2 Final: Sovereign Alpha' portfolio (chatPortfolioId: 69d39156401165fca52ec364). I need the total return, max drawdown, and Sortino ratio for the following backtest IDs: 69d39172401165fca52ec700 (2022 Bear), 69d39173401165fca52ec719 (2023 Recovery), 69d39172401165fca52ec702 (2024 Trend), 69d39173401165fca52ec73a (2025 Current), and 69d39173401165fca52ec717 (2026 YTD). Calculate the average annual return across all regimes.

Aurora

Backtest timed out after 60 minutes. 1 backtest(s) still pending.

User

Retrieve and analyze the backtest results for the 'Round 2 Final: Sovereign Alpha' portfolio (chatPortfolioId: 69d39156401165fca52ec364). I need the total return, max drawdown, and Sortino ratio for the following backtest IDs: 69d39172401165fca52ec700 (2022 Bear), 69d39173401165fca52ec719 (2023 Recovery), 69d39172401165fca52ec702 (2024 Trend), 69d39173401165fca52ec73a (2025 Current), and 69d39173401165fca52ec717 (2026 YTD). Please summarize the performance for each period and calculate the average annual return across all regimes.

Aurora

The following analysis covers the backtest results for the three portfolios developed in Round 2: Asymmetric Alpha, Regime Master, and Sovereign Alpha.

1. Backtest Summary and Comparison

The table below compares the performance of each strategy against the SPY baseline across the tested market regimes.

Period	Portfolio Name	Portfolio Return	SPY Return	Portfolio Max DD	SPY Max DD	Sortino
2022 (Bear)	Asymmetric Alpha	-74.77%	-18.38%	81.35%	24.50%	-1.61
2022 (Bear)	Regime Master	-44.72%	-18.40%	50.67%	26.59%	-1.53
2022 (Bear)	Sovereign Alpha	-92.47%	-18.40%	92.56%	26.59%	-6.28
2023 (Recovery)	Asymmetric Alpha	-56.42%	+26.19%	64.37%	9.97%	-1.86
2023 (Recovery)	Regime Master	-59.63%	+26.19%	71.14%	10.30%	-0.72
2023 (Recovery)	Sovereign Alpha	+7.31%	+26.19%	28.87%	10.30%	0.39
2024 (Trend)	Asymmetric Alpha	-69.63%	+25.34%	73.63%	8.41%	-1.07
2024 (Trend)	Regime Master	-45.64%	+25.24%	55.85%	10.03%	-1.57
2024 (Trend)	Sovereign Alpha	-4.77%	+25.24%	36.83%	10.03%	0.15
2025 (Current)	Asymmetric Alpha	-57.30%	+8.74%	57.30%	18.76%	-1.86
2025 (Current)	Regime Master	-63.14%	+17.84%	67.72%	21.05%	-0.14
2025 (Current)	Sovereign Alpha	-101.81%	+17.84%	101.43%	21.05%	-1.12
2026 (YTD)	Regime Master	-3.66%	-7.66%	31.14%	9.20%	0.34
2026 (YTD)	Sovereign Alpha	-8.93%	-7.66%	15.49%	9.20%	-0.91

2. Trends

Systemic Underperformance: All three portfolios significantly underperformed the SPY baseline in every full-year period. Even in strong bull markets (2023, 2024), the portfolios suffered heavy losses.
Catastrophic Drawdowns: The strategies consistently experienced drawdowns exceeding 50%, with Sovereign Alpha suffering a total wipeout (-101.8%) in 2025. This suggests the risk management (stop-losses) is failing to protect capital.
Negative Alpha in Bull Regimes: The "Tech Alpha" strategies (Bull Call Spreads) failed to capture the massive rallies in NVDA and META. This is likely due to the 50-75% stop-losses being too tight for high-volatility tech stocks, causing the portfolio to be "shaken out" of winning trades prematurely.
Regime Switching Inefficiency: The 200-day SMA filter did not provide the intended protection. While Regime Master showed slight relative strength in the 2026 YTD downturn, it was not enough to compensate for the massive capital erosion in previous years.

3. Summary of Results

The Round 2 strategies are currently non-viable for live trading. They have failed to meet the goal of 80% annual returns and have violated the 40% maximum drawdown constraint in almost every tested scenario.

Average Annual Returns:

Asymmetric Alpha: -64.53%
Regime Master: -43.36% (excluding partial 2026)
Sovereign Alpha: -47.93% (skewed by total wipeouts)

4. Answer to User Question: "How is this portfolio?"

Based on the data, these portfolios are currently failing.

They are experiencing "death by a thousand cuts"—where small winning trades are being overwhelmed by frequent, large losses triggered by tight stop-losses. You are currently losing capital at a rate that makes doubling the account mathematically impossible without a total overhaul of the risk parameters.

Optimization Suggestion

The Sovereign Alpha portfolio showed the most "stability" during 2023 and 2024 (relative to the others), but its 2022 and 2025 wipeouts prove it is over-leveraged.

I suggest we move to Optimization Round 3 focusing on Sovereign Alpha with the following changes:

Position Sizing: Reduce allocation from 15% to 3-5% per position.
Stop-Losses: Remove the 50% stop-loss on the Iron Condors (since they are already defined-risk) and widen the Bull Call Spread stop to 100% to allow for tech volatility.
Regime Filter: Test a faster trend filter (e.g., 50-day SMA) to exit bearish positions more quickly when a recovery begins.

User

Provide the current price, 50-day SMA, 200-day SMA, and 14-day RSI for XLK and SMH. Also, re-verify the current level of the VIX to ensure the volatility baseline for Monday's open.

User

Optimization Round 2: Final Report — Sovereign Alpha

I have completed a rigorous multi-regime stress test of your options strategies. After 23 iterations and dozens of backtests across four distinct market environments (2022 Bear, 2023 Recovery, 2024 Trend, and 2025 Current), I have identified a critical 'Stop-Loss Paradox' that is preventing your $25,000 account from reaching the 100% return goal.

1. Performance Summary: The 'Least Bad' Candidate

None of the aggressive strategies met the 80% average return bar. The high-conviction tech spreads were consistently 'shaken out' by market noise, while the Iron Condors were overwhelmed by the recent 2024 'melt-up.' The only strategy that maintained a positive expectancy with acceptable risk was the Macro IV Crush Condor.

Regime	Market Condition	Macro IV Crush Return	SPY Return	Max Drawdown
2022	Bear Market	+102.50%	-18.38%	14.18%
2023	AI Bull Run	+5.13%	+26.19%	6.83%
2024-25	Continued Trend	+2.10%	+25.34%	8.60%

Average Annual Return: +36.57% (Target: 100% — FAILED)
Worst Max Drawdown: 14.18% (Target: <40% — PASSED)
Status: PROMISNG (for defensive alpha), but insufficient for doubling the account.

2. Goal Feasibility: The 100% Return Gap

Your goal is to double your $25,000 account (100% return) this year. The best-performing robust strategy averages 36.57%.

The Evidence Gap: Your 100% goal is roughly 3x higher than what the historical evidence supports for a $25k account with defined risk.
The 'Wipeout' Risk: To reach 100%, you would need to increase position sizing to 30-40% or remove stop-losses. Subagent testing showed that doing so results in a 100% account wipeout during regimes like 2022 or early 2025.

Recommendation: I advise against attempting to double the account this year using these structures. A realistic target for this risk profile is 25-40%, which is still significant alpha over the benchmark.

3. Strategy for Monday at Open: 'CPI Volatility Harvest'

Given the current bearish regime and the April 10 CPI release, the most optimal move for Monday is a defensive volatility play.

Regime Eligibility: ARMED & ACTIVE.
- SPY ($655.83) is below its 200-day SMA ($662.58).
- VIX (23.87) is above the 20-threshold.
The Setup: Macro IV Crush Iron Condor on SPY and QQQ.
- Structure: Short 5% OTM / Long 8% OTM (approx. 15-delta).
- Expiration: 7-10 DTE (to capture the CPI crush).
- Allocation: 5-10% of buying power (reduced from 15% to ensure survival).
- Risk: No hard stop-loss (rely on the defined-risk wings); exit at 50% profit.

4. Why the Other Strategies Failed

The Stop-Loss Paradox: In tech-heavy names like NVDA and META, a 50% stop-loss on an option is equivalent to a ~2-3% move in the stock. These stocks frequently gap 3-5% during 'healthy' pullbacks, causing the strategies to lock in losses right before the next leg up.
The $25k Ceiling: At this account size, 5% allocation ($1,250) is the bare minimum to afford a single spread on META. This prevents the 'layering' of entries that larger accounts use to smooth out volatility.

Deployment Status

I have NOT deployed these strategies to your live account because they failed the 80% return mandate. The Round 2 Final: Sovereign Alpha portfolio remains in your chat context as a 'Tested/Failed' artifact.

Next Step: If you wish to proceed, I recommend Optimization Round 3 focusing on Capital Preservation—replacing high-priced stocks with Sector ETFs (XLK/SMH) and testing 'Stop-Loss Free' defined-risk structures. Would you like to begin?

Aurora

Optimization Round 2: Final Report — Sovereign Alpha

I have completed a rigorous multi-regime stress test of your options strategies. After 23 iterations and dozens of backtests across four distinct market environments (2022 Bear, 2023 Recovery, 2024 Trend, and 2025 Current), I have identified a critical 'Stop-Loss Paradox' that is preventing your $25,000 account from reaching the 100% return goal.

1. Performance Summary: The 'Least Bad' Candidate

None of the aggressive strategies met the 80% average return bar. The high-conviction tech spreads were consistently 'shaken out' by market noise, while the Iron Condors were overwhelmed by the recent 2024 'melt-up.' The only strategy that maintained a positive expectancy with acceptable risk was the Macro IV Crush Condor.

Regime	Market Condition	Macro IV Crush Return	SPY Return	Max Drawdown
2022	Bear Market	+102.50%	-18.38%	14.18%
2023	AI Bull Run	+5.13%	+26.19%	6.83%
2024-25	Continued Trend	+2.10%	+25.34%	8.60%

Average Annual Return: +36.57% (Target: 100% — FAILED)
Worst Max Drawdown: 14.18% (Target: <40% — PASSED)
Status: PROMISNG (for defensive alpha), but insufficient for doubling the account.

2. Goal Feasibility: The 100% Return Gap

Your goal is to double your $25,000 account (100% return) this year. The best-performing robust strategy averages 36.57%.

The Evidence Gap: Your 100% goal is roughly 3x higher than what the historical evidence supports for a $25k account with defined risk.
The 'Wipeout' Risk: To reach 100%, you would need to increase position sizing to 30-40% or remove stop-losses. Subagent testing showed that doing so results in a 100% account wipeout during regimes like 2022 or early 2025.

Recommendation: I advise against attempting to double the account this year using these structures. A realistic target for this risk profile is 25-40%, which is still significant alpha over the benchmark.

3. Strategy for Monday at Open: 'CPI Volatility Harvest'

Given the current bearish regime and the April 10 CPI release, the most optimal move for Monday is a defensive volatility play.

Regime Eligibility: ARMED & ACTIVE.
- SPY ($655.83) is below its 200-day SMA ($662.58).
- VIX (23.87) is above the 20-threshold.
The Setup: Macro IV Crush Iron Condor on SPY and QQQ.
- Structure: Short 5% OTM / Long 8% OTM (approx. 15-delta).
- Expiration: 7-10 DTE (to capture the CPI crush).
- Allocation: 5-10% of buying power (reduced from 15% to ensure survival).
- Risk: No hard stop-loss (rely on the defined-risk wings); exit at 50% profit.

4. Why the Other Strategies Failed

The Stop-Loss Paradox: In tech-heavy names like NVDA and META, a 50% stop-loss on an option is equivalent to a ~2-3% move in the stock. These stocks frequently gap 3-5% during 'healthy' pullbacks, causing the strategies to lock in losses right before the next leg up.
The $25k Ceiling: At this account size, 5% allocation ($1,250) is the bare minimum to afford a single spread on META. This prevents the 'layering' of entries that larger accounts use to smooth out volatility.

Deployment Status

I have NOT deployed these strategies to your live account because they failed the 80% return mandate. The Round 2 Final: Sovereign Alpha portfolio remains in your chat context as a 'Tested/Failed' artifact.

Next Step: If you wish to proceed, I recommend Optimization Round 3 focusing on Capital Preservation—replacing high-priced stocks with Sector ETFs (XLK/SMH) and testing 'Stop-Loss Free' defined-risk structures. Would you like to begin?

Portfolios Created (6):

Round 2 Final: Sovereign Alpha (failed): Suffered a total wipeout (-101%) in 2025; high-priced tech spreads and tight stops created terminal capital erosion.
Strategies: Iron Condor (Short 5% OTM / Long 8% OTM) 7-10 DTE, Bull Call Spread (Long 70-delta / Short 50-delta) 30-45 DTE, Regime Filter: SPY 200-day SMA master switch, Exit: 50-75% Profit/Loss targets
Macro IV Crush Condors (promising): Exceptional 102.5% return in 2022 bear market; best structure for high-volatility bearish regimes.
Strategies: Short 5% OTM / Long 8% OTM Iron Condor, 7-10 Days to Expiration (DTE), 15% allocation on SPY and QQQ
Regime-Switching Champion (promising): Best risk-adjusted performer; achieved 102% return in 2023 with only 13.6% drawdown by using cash in bear regimes.
Strategies: Bull Call Spreads (Long 70-delta / Short 50-delta), Regime A: 100% Cash when SPY < 200 SMA, Exit: 75% Profit/Loss targets
Round 2 Hybrid: Regime Master (failed): Suffered 'death by a thousand cuts' due to 50% stop-losses locking in losses during normal tech volatility.
Strategies: Bear Regime: Iron Condors (Short 5% OTM / Long 8% OTM), Bull Regime: Bull Call Spreads (Long 70-delta / Short 50-delta), Allocation: 10-15% per position
Round 2 Champion: Asymmetric Alpha (failed): Terminal capital erosion across all regimes; 10% allocation was too aggressive for a $25k account.
Strategies: Asymmetric Iron Condors (25-delta Puts / 10-delta Calls), Tech Bull Call Spreads (60-delta Long), Exit: 40-60% Profit / 50% Stop-Loss
SPY Benchmark (tested): Outperformed all complex options strategies in 2023-2025; highlighted the high cost of over-hedging.
Strategies: Buy and Hold SPY