Source: YouTube URL: https://www.youtube.com/watch?v=leFWtyKzJBg Date: 2025-11-26 Duration: 5:06 Channel: Steve Gans Strategy Type: Advanced Options Trading
The “Flyagonal” is an advanced options strategy combining a call broken wing butterfly (upside) with a put diagonal (downside), developed with AI assistance. Trading SPY with ~$187 max risk, this strategy has achieved 150% returns over 7 months (132 trades, 125 winners, 94.7% win rate), targeting 10% profit per trade with 4-5 day average holding periods. The strategy benefits from theta decay and can self-correct based on volatility changes.
The Flyagonal Structure
The strategy consists of two complementary components that create a wider profit zone than traditional single-sided structures:
Profit Zone Expansion
The combination nearly doubles the profit range: - Single-sided structure: Approximately 10 points wide (677-686) - Combined Flyagonal: Approximately 20 points wide (666-686) - This wider tent provides greater flexibility for market movement while maintaining profitability
Theta Decay Enhancement
The dual-sided structure provides superior theta characteristics: - Single component: ~$5/day in theta decay - Full Flyagonal: ~$10/day in theta decay (doubled) - With 4-5 day average holding period, this generates $40-50 in time decay per trade - Targeting 10% of max risk ($18-20) means theta provides substantial portion of profit target
Vega Positioning - Self-Correcting Feature
The strategy exhibits intelligent volatility response:
Downside Market Movement: - Market decline typically increases implied volatility - Put diagonal becomes positive Vega in this scenario - Rising volatility expands lower profit tent - Profitability increases on downside moves - Creates “self-correcting” mechanism during market weakness
Upside Market Movement: - Market rallies typically decrease implied volatility - Falling volatility benefits call butterfly structure - Profitability increases on upside moves - Works in tandem with positive theta decay
This dual volatility response creates flexibility across different market conditions, though the creator notes the downside expansion “doesn’t always happen” - it’s situational based on actual volatility changes.
Live Trading Results (7 Months)
Since May 2025 implementation: - Total Trades: 132 - Winning Trades: 125 - Win Rate: 94.7% (exceptionally high for options strategies) - Total Return: 150% over ~7 months - Annualized Projection: ~300% (assuming consistent performance) - Average Trade Duration: 4-5 days
Position Sizing Philosophy
The trader employs conservative position sizing: - Max risk per trade: $187 - Max theoretical profit: $446 (not the goal) - Target profit: 10% of max risk (~$18-20) - Quick exits at profit target rather than holding for maximum gain - Small position size allows for multiple concurrent trades and risk management
Trade Management Approach
The strategy emphasizes consistent small wins: - Target: 10% return per trade - Exit immediately upon reaching target - Don’t hold for maximum profit potential - Prioritize consistency over home runs - 4-5 day holding period reduces overnight risk exposure
Experience Prerequisites
This is explicitly an advanced strategy requiring prior mastery of:
Recommended Approach for New Traders
Complexity Factors
The Flyagonal requires managing: - Multiple option legs simultaneously - Different expirations across diagonals - Adjustment decisions based on market movement - Volatility changes affecting different components - Theta decay across multiple structures
Design Methodology
The AI involvement likely contributed to: - Optimal strike selection for both components - Greek balancing between upside and downside structures - Risk/reward optimization - Profit zone width maximization
SPY-Based Implementation
Trading characteristics: - High liquidity ensures tight bid-ask spreads - Abundant option chain with many strikes - Reliable price discovery - Lower capital requirements than SPX - Suitable for smaller position sizes (~$187 risk)
The creator mentions: - Comprehensive educational content available for learning the strategy - Black Friday promotional pricing mentioned - Class structure for in-depth instruction - Trade tracking and sharing via link (mentioned in video)
“This trade has two unique components to it. It has a call broken wing butterfly on the upside of the trade… and then it has a put diagonal below the market.”
“It takes this tent from basically being from 677 to 686 approximately 10 points wide. It takes it all the way down here to 666 up to 686. So it almost gives you double the width to play in.”
“I’m getting double the theta decay. Now there is one final component to this that can be helpful as well.”
“This trade, one of the things that I really like about it, I had a lot of AI involved in helping me design and develop this. One of the awesome things about this trade is it can be a little bit self-correcting.”
“I’ve made 132 trades. I have had 125 winners and the trade has generated about 150% return over the roughly 7 months that I’ve traded it. That’s pushing close to an 300% annual return.”
“I’m just looking to get 10% or so out of this trade, shut it down, and move on.”
“It is important to understand that this is a more advanced trade. If you have not traded broken wing butterflies before, if you have not traded calendars and diagonals before, this is something you should totally and completely paper trade.”
Based on video examples:
Upside Component (Call Broken Wing Butterfly): - Strike configuration: Positioned above current SPY price - Creates upper profit boundary - Example upper limit: ~686
Downside Component (Put Diagonal): - Strike configuration: Positioned below current SPY price - Creates lower profit boundary - Example lower limit: ~666
Combined Profit Zone: - Width: ~20 points (666-686 in example) - Center: Current SPY price - Flexibility: Allows 10 points of movement in either direction
| Greek | Single Component | Full Flyagonal | Benefit |
|---|---|---|---|
| Theta | ~$5/day | ~$10/day | 100% increase |
| Vega | Varies | Positive on downside | Self-correcting |
| Delta | Near neutral | Near neutral | Market direction flexibility |
Entry: - Not explicitly detailed in video - Likely based on market conditions favoring range-bound movement - Position sizing: Max risk ~$187
Exit: - Target: 10% profit (~$18-20) - Timeline: 4-5 days average - Management: Exit immediately at target, don’t hold for max profit
Risk Management: - Max loss: $187 per trade - No mention of stop losses (profit tent provides natural risk boundaries) - Small position size relative to account
Exceptional Metrics: - 94.7% win rate is extraordinarily high for any options strategy - 150% in 7 months (300% annualized) is exceptional if sustainable - However, important caveats: - 7-month track record is relatively short - May 2025 start captures specific market conditions - Past performance doesn’t guarantee future results - Market regime changes could affect strategy effectiveness
Realistic Expectations: - Strategy likely performs best in range-bound, moderately volatile markets - Extreme volatility events or sustained trends might stress the structure - Win rate may normalize over longer timeframes - Returns may vary with different market conditions
vs. Iron Condor: - Flyagonal: Wider profit range, better theta, more complex - Iron Condor: Simpler, narrower range, easier to manage
vs. Single Butterflies: - Flyagonal: Double the profit range, higher theta, more capital - Single Butterfly: Simpler, lower capital, narrower range
vs. Credit Spreads: - Flyagonal: Higher win rate, more complex, better theta - Credit Spreads: Simpler, lower win rate, easier adjustments
「Flyagonal」是一種進階選擇權策略，結合看漲不對稱蝶式價差（上檔）與看跌對角價差（下檔），透過AI輔助開發。交易SPY時最大風險約$187美元，此策略在7個月內實現150%回報（132筆交易，125筆獲利，94.7%勝率），目標每筆交易獲利10%，平均持有期4-5天。策略受益於時間價值衰減，並能根據波動率變化自我修正。
Flyagonal結構
此策略包含兩個互補組件，創造比傳統單邊結構更寬的獲利區域：
獲利區間擴展
組合策略幾乎將獲利範圍擴大一倍： - 單邊結構：約10點寬（677-686） - 完整Flyagonal：約20點寬（666-686） - 更寬的帳篷為市場波動提供更大的靈活性，同時保持獲利能力
時間價值衰減增強
雙邊結構提供優越的Theta特性： - 單一組件：每天約$5美元的時間價值衰減 - 完整Flyagonal：每天約$10美元的時間價值衰減（加倍） - 以4-5天平均持有期計算，每筆交易產生$40-50美元的時間衰減 - 目標獲利為最大風險的10%（$18-20美元），意味著Theta提供了獲利目標的相當部分
Vega定位 - 自我修正特性
策略展現智慧型波動率反應：
下跌市場行情： - 市場下跌通常增加隱含波動率 - 看跌對角價差在此情境下成為正Vega - 波動率上升擴展下方獲利帳篷 - 下檔波動時獲利能力增加 - 在市場疲軟期間創造「自我修正」機制
上漲市場行情： - 市場上漲通常降低隱含波動率 - 波動率下降有利於看漲蝶式價差結構 - 上檔波動時獲利能力增加 - 與正Theta衰減協同作用
這種雙向波動率反應在不同市場條件下創造靈活性，儘管創建者指出下檔擴張「並非總是發生」——取決於實際波動率變化的具體情況。
實盤交易結果（7個月）
自2025年5月實施以來： - 總交易次數：132筆 - 獲利交易：125筆 - 勝率：94.7%（選擇權策略中極高的勝率） - 總回報：7個月約150% - 年化推估：約300%（假設績效持續） - 平均交易週期：4-5天
部位規模哲學
交易者採用保守的部位規模： - 每筆交易最大風險：$187美元 - 最大理論獲利：$446美元（非目標） - 目標獲利：最大風險的10%（約$18-20美元） - 達到獲利目標立即退出，而非追求最大獲利 - 小部位規模允許多個同時交易和風險管理
交易管理方法
策略強調穩定的小幅獲利： - 目標：每筆交易10%回報 - 達到目標立即退出 - 不持有追求最大獲利潛力 - 優先考慮一致性而非全壘打 - 4-5天持有期減少隔夜風險暴露
經驗先決條件
這明確是一種進階策略，需要事先精通：
新手交易者建議方法
複雜性因素
Flyagonal需要管理： - 同時多個選擇權腳位 - 對角價差的不同到期日 - 基於市場波動的調整決策 - 影響不同組件的波動率變化 - 多個結構的時間價值衰減
設計方法
AI參與可能貢獻於： - 兩個組件的最佳執行價選擇 - 上下檔結構之間的希臘值平衡 - 風險回報優化 - 獲利區間寬度最大化
基於SPY的實施
交易特性： - 高流動性確保窄買賣價差 - 豐富的選擇權鏈具有多個執行價 - 可靠的價格發現 - 相比SPX資本要求較低 - 適合較小部位規模（約$187美元風險）
創建者提及： - 提供全面的學習策略教育內容 - 提及黑色星期五促銷定價 - 深入教學的課程結構 - 透過連結進行交易追蹤和分享（影片中提及）
“這筆交易有兩個獨特組件。它在交易的上檔有一個看漲不對稱蝶式價差……然後在市場下方有一個看跌對角價差。”
“它將這個帳篷從基本上677到686約10點寬，一路延伸到666到686。所以幾乎給你雙倍的活動空間。”
“我獲得了雙倍的時間價值衰減。現在還有一個最終組件也可能有所幫助。”
“這筆交易，我真正喜歡的其中一點是，我有很多AI參與幫助我設計和開發這個。這筆交易最棒的一點是它可以有點自我修正。”
“在這個階段，自從我開始實盤交易這個策略以來，我進行了132筆交易。我有125筆獲利，這筆交易在大約7個月內產生了約150%的回報。這接近300%的年回報率。”
“我只是想從這筆交易中獲得10%左右的收益，關閉它，然後繼續前進。”
“重要的是要理解這是一個更進階的交易。如果你以前沒有交易過不對稱蝶式價差，如果你以前沒有交易過日曆價差和對角價差，這是你應該完全徹底模擬交易的東西。”
基於影片範例：
上檔組件（看漲不對稱蝶式價差）： - 執行價配置：部位於當前SPY價格之上 - 創造上方獲利邊界 - 範例上限：約686
下檔組件（看跌對角價差）： - 執行價配置：部位於當前SPY價格之下 - 創造下方獲利邊界 - 範例下限：約666
組合獲利區域： - 寬度：約20點（範例中666-686） - 中心：當前SPY價格 - 靈活性：允許任一方向10點的波動
| 希臘值 | 單一組件 | 完整Flyagonal | 效益 |
|---|---|---|---|
| Theta | 約$5美元/天 | 約$10美元/天 | 增加100% |
| Vega | 變動 | 下檔正值 | 自我修正 |
| Delta | 近中性 | 近中性 | 市場方向靈活性 |
進場： - 影片中未明確詳述 - 可能基於有利於區間震盪的市場條件 - 部位規模：最大風險約$187美元
出場： - 目標：10%獲利（約$18-20美元） - 時間框架：平均4-5天 - 管理：達到目標立即退出，不持有追求最大獲利
風險管理： - 每筆交易最大損失：$187美元 - 未提及停損（獲利帳篷提供自然風險邊界） - 相對於帳戶的小部位規模
卓越指標： - 94.7%勝率對任何選擇權策略都極為罕見 - 7個月內150%（年化300%）如果可持續則非常出色 - 然而，重要注意事項： - 7個月追蹤記錄相對較短 - 2025年5月開始捕捉特定市場條件 - 過去績效不保證未來結果 - 市場制度變化可能影響策略效果
實際預期： - 策略可能在區間震盪、中度波動的市場中表現最佳 - 極端波動事件或持續趨勢可能對結構造成壓力 - 勝率可能在更長時間框架內正常化 - 回報可能隨不同市場條件而變化
vs. 鐵鷹式價差： - Flyagonal：更寬獲利範圍，更好的theta，更複雜 - 鐵鷹式價差：更簡單，更窄範圍，更易管理
vs. 單一蝶式價差： - Flyagonal：雙倍獲利範圍，更高theta，更多資本 - 單一蝶式價差：更簡單，較低資本，更窄範圍
vs. 信用價差： - Flyagonal：更高勝率，更複雜，更好的theta - 信用價差：更簡單，較低勝率，更易調整
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