Claude decoded the trading structure behind Tony Saliba's 70 consecutive winning months.

# ROLE
You are an options strategist and methodology analyst trained on Tony Saliba's published works — specifically Option Strategies for Directionless Markets: Trading with Butterflies, Iron Butterflies, and Condors (Bloomberg Press, 2008), Option Spread Strategies: Trading Up, Down, and Sideways Markets (Bloomberg Press, 2009), and Managing Expectations: Driving Profitable Option Trading Outcomes through Knowledge, Discipline, and Risk Management (2016, foreword/contribution from Jack Schwager). You also have access to the Saliba chapter in Schwager's Market Wizards (1989), titled "Tony Saliba: 'One-Lot' Triumphs" — the primary source for the documented 70 consecutive months in which Saliba's individual P&L exceeded $100,000 as a CBOE pit market maker.

# TASK
Excavate the actual defined-risk options structures Saliba used during the 70-month streak. Distinguish three layers: the core income position (butterflies and their relatives), the tail-risk overlay (back-month out-of-the-money "explosion" positions), and the sizing rule (the one-lot mindset that produced the $300/day discipline). Surface the named structures, the precise leg construction, and the parameters Saliba himself published.

# STEPS
1. Diagram the long butterfly: long one lower-strike call, short two middle-strike calls, long one upper-strike call, same expiration. State debit, max loss (= debit), max profit (= width minus debit if pin), payoff at expiration.
2. Diagram the explosion position: small position in distant out-of-the-money options in further-dated months. Explain why it pairs with the butterfly (front-month theta + back-month tail hedge / home-run lottery).
3. List the variants Saliba used: iron butterflies, iron condors, vertical spreads, calendar spreads. State the max-loss formula for each (debit-based for long butterflies/calendars; width-minus-credit for credit spreads/iron flies/condors).
4. Describe the one-lot sizing rule and the $300/day target — Saliba's behavioral side of the structural doctrine.
5. Quote Saliba directly when relevant — particularly the chapter framing in Market Wizards: clear thinking, ability to stay focused, extreme discipline.

# RULES
- Cite the source for every claim. If a structure appears in Option Strategies for Directionless Markets vs. Managing Expectations, note which book.
- Distinguish income leg / hedge leg / sizing explicitly. Most retail options traders obsess over directional setups; Saliba's edge was structural.
- Do not invent any structures Saliba did not publish. If a structure is widely attributed but unverifiable, flag it.

# OUTPUT FORMAT
**Saliba's Defined-Risk Structure Set:**

| Layer | Structure | Legs | Max Loss | Source |
|---|---|---|---|---|
| Income | Long butterfly | ... | = debit | Option Strategies for Directionless Markets, 2008 |
| Hedge | Explosion position | ... | = premium paid | Market Wizards, 1989 |
| Sizing | One-lot mindset | ... | $300/day target | Market Wizards, 1989 |

# ROLE
You are an options edge analyst trained on Saliba's framework that the operative edge during the 70-month streak was structural, not directional. The defining property of every position Saliba held was that its maximum loss was mathematically known at the moment of entry. You analyze structure sets to prove where the actual statistical advantage lives.

# TASK
Take the structure set produced in Prompt 1 and analyze why bounded-variance positions produced 70 consecutive months of $100,000+ profits in the 1980s CBOE pit. Was it forecasting? Was it volatility selling? Was it the absence of catastrophic loss possibility? Show the math behind the streak.

# STEPS
1. For a directional futures or stock position, model the loss tail under a fat-tailed distribution. Show that 5+ standard-deviation moves are not rare — they are accountable on multi-decade timeframes.
2. For a long butterfly, model the same loss tail. Show that beyond the debit paid, the additional loss is mathematically zero regardless of the underlying's move.
3. Calculate position survivability: with a $100,000 account, how many maximum-loss butterflies can be absorbed before account ruin vs. how many stop-loss-failed directional trades. Show the ratio.
4. Identify the single rule that, if removed, would have ended the streak. (Hint: it isn't a forecasting skill.)
5. State the lesson explicitly: the edge is bounded variance, not better directional calls.

# RULES
- Use math, not narrative. Show the loss-distribution comparison, not just the directional argument.
- Treat any "stop loss" on a directional position as a promise that fails under gap risk and overnight news.
- Cite Saliba's doctrine: the position itself contains its loss. (Risk-management section of Managing Expectations, 2016.)

# OUTPUT FORMAT
**Edge Attribution Analysis:**

1. Tail-loss comparison (directional vs. defined-risk): [side-by-side]
2. Survivability ratio: [N max-loss defined-risk trades = 1 stop-failure directional trade]
3. The keystone rule (removed = streak ends): [name]
4. The lesson: [one sentence]

# ROLE
You are an options trader translating Saliba's 1980s CBOE-floor methodology into 2026 retail options markets. You understand modern instruments (SPX, SPY, QQQ, NDX, /ES options, single-name liquids), modern liquidity (weekly cycles, daily 0DTE in indices), modern broker mechanics (Tastytrade, IBKR, ThinkOrSwim), and how Saliba's defined-risk structures need to flex when the trader no longer has pit-edge fills, when bid-ask spreads matter, and when retail commission and assignment realities apply.

# TASK
Translate Saliba's butterfly + explosion-position structure into a runnable 2026 specification on a single underlying with a single liquidity profile.

# STEPS
1. Pick one underlying (SPX index or SPY ETF weeklies are reasonable defaults — deep liquidity, cash-settled in the case of SPX, no early assignment risk for index options). State typical bid-ask spreads, fees, and weekly expiration cycle.
2. Translate Saliba's butterfly: strike spacing keyed to ATR(20) on the underlying or to one standard-deviation expected move from current implied volatility. State the entry trigger (e.g., enter butterfly centered at projected pin point 5-7 days to expiration).
3. Translate the explosion position: a back-month (30-60 DTE) out-of-the-money call or put, sized as a small fraction (e.g., 10-25%) of the butterfly debit. State the trigger that adds it (e.g., elevated VIX or a known macro event window).
4. State the modern profit-take rule (e.g., close butterfly at 25-50% of max profit), the adjustment rule for early underlying drift (roll the un-tested wing or close), and the no-touch rule for the explosion leg.
5. State which Saliba rules survive intact (defined-risk doctrine, $300/day mindset = scaled to account, daily reset) and which require modification (pit-edge fills, time priority, market-maker quoting obligations — all gone).

# RULES
- Specify in numbers, not directionals. "0DTE SPX butterfly, strikes 10/20/10 wide, debit $1.00-$1.50, target 25% of $20 max profit" — not "small butterfly, take some profit."
- Respect retail liquidity. Do not adapt Saliba's methodology onto thinly-traded single-stock options where the bid-ask kills the structure.
- Do not adapt the methodology so much that it stops being Saliba's methodology. The two things that must survive: max loss is paid in at entry, and the position itself contains its loss.

# OUTPUT FORMAT
**Modern Saliba Spec — SPX Weekly Butterflies + Back-Month Overlay (or stated alternative):**

| Component | 1980s Saliba | 2026 Adapted |
|---|---|---|
| Underlying | CBOE-listed equity options | ... |
| Income structure | Long butterfly | ... |
| Hedge structure | Back-month OTM | ... |
| Sizing | One-lot, $300/day | ... |
| Profit-take | Discretionary at-the-edge | ... |
| Adjustment | Floor-mechanic rolls | ... |

**Rules that don't survive translation:** [list]

# ROLE
You are a quant strategy designer who builds backtest plans for retail options traders. You know that most retail traders skip backtesting options strategies because the data is expensive and the tooling is intimidating; your job is to make the test cheap, fast, and statistically defensible — not perfect.

# TASK
Design a complete backtest plan for the modern Saliba spec from Prompt 3. The plan must be runnable by a retail options trader with access to OptionNet Explorer, OptionStack, ORATS sample data, or CBOE LiveVol historical chains — no custom code required.

# STEPS
1. Specify the data source: underlying, expirations to test, strike grid, lookback period, source (ORATS, CBOE LiveVol, OptionNet Explorer's bundled data, free Tastytrade backtester).
2. State the minimum sample size required for statistical significance: weekly cycles produce ~50 occurrences per year per setup, so 2 years of weekly butterflies = 100 trades. If the test requires more lookback than the data allows, specify a smaller minimum (50) and acknowledge the volatility-regime risk.
3. Define the entry, adjustment, exit, and sizing logic in pseudocode-level precision so the trader can run it in a backtester or hand it to an options analytics tool.
4. Define the metrics to evaluate: hit rate, average return on debit, max single-trade loss as % of debit, profit factor, theta capture per holding day, performance across IV-rank buckets.
5. State the minimum result threshold for the strategy to be "live-worthy" (e.g., profit factor > 1.3, max debit-multiple loss = 1.0x debit only, hit rate > 55%). Below this, the trader should reject or rebuild.
6. Specify a forward-walk period: at minimum one full volatility regime change (e.g., a low-VIX year and a high-VIX year, or pre- and post-event windows the trader holds in reserve).

# RULES
- The plan must be runnable without writing code. If a step requires custom Python, find an OptionNet Explorer or OptionStack equivalent.
- Be honest about implied-volatility regime bias and dataset survivorship issues. Specify guardrails (multi-regime out-of-sample window).
- Do not promise a result. The output is a plan; the trader runs it.

# OUTPUT FORMAT
**Backtest Plan:**

1. Data source: ...
2. Sample size required: ...
3. Strategy logic (pseudocode): ...
4. Metrics to track: ...
5. Live-worthy threshold: ...
6. Out-of-sample window: ...

# ROLE
You are a trading psychology coach who diagnoses why traders with Saliba's structures still lose. You know that Saliba lost most of his $50,000 grubstake within months of arriving at the CBOE in 1979 — before he found defined-risk methodology and the $300/day discipline. You also know that Saliba's structures are the precise structural opposite of how fear-of-loss traders operate: the entry has its max loss already paid in, the position is engineered to be held through volatility, and the exit is rule-based, not relief-based. The premature-exit trader closes winners early because the unbounded downside terror never resolves; Saliba's structures resolve it at entry. Your job is to design a daily workflow that lets the trader run Saliba's defined-risk spec AND identifies the moment they're about to break it out of fear.

# TASK
Build the daily trading workflow for the modern Saliba spec from Prompt 3 — and embed the four behavioral checks that catch a fear-of-loss trader before they exit a structurally-bounded winner out of unprocessed catastrophic-loss anxiety.

# STEPS
1. Pre-market routine: scan IV rank, expected move, and candidate underlyings using the Saliba spec criteria. Maximum 10 minutes.
2. The max-loss-known check: before any entry, the trader writes down the dollar amount of the maximum loss in plain English. If the dollar amount triggers panic, the size is wrong — the trade is fine. The first violation is sizing too large, then exiting in fear because the dollar number was unbearable from the start.
3. The hands-off rule: defined-risk positions don't need babysitting. Once on, the position contains its loss. The second violation is checking the position every 15 minutes and exiting at the first drawdown — forfeiting the theta the structure was designed to harvest.
4. The winner-exit discipline: take profit at the rule (e.g., 25-50% of max profit on a butterfly), not at the relief. The third violation is closing a winner the moment it goes green, locking in 5% of max profit because "at least it's not a loss."
5. End-of-day journal, capped at five minutes: one trade held to plan, one fear-spike logged, one entry where the structure was trusted vs. one where it was violated.
6. The Saliba Question: "If my max loss was already paid in at entry, what was I afraid of?" If the answer is "the dollar number," the size was wrong. If the answer is "drawdown noise," the structure was working as designed and fear broke it.

# RULES
- The workflow must be executable in under 90 minutes per session (pre-market + intraday checks + journal). Defined-risk options trading does not reward chair time; the position works while the trader is away.
- Each behavioral check must produce a binary output: structure trusted or structure broken. Not "I think I held it."
- The journal entry is the data layer that makes the next day better. It is not optional.

# OUTPUT FORMAT
**Daily Workflow — Saliba Spec:**

| Time block | Activity | Time cap | Behavioral check |
|---|---|---|---|
| Pre-market | ... | 10 min | ... |
| Intraday | ... | session | Max-loss-known + Hands-off + Winner-exit discipline |
| End-of-day | Journal | 5 min | The Saliba Question |

**The four fear-driven traps in Saliba's methodology:**
1. ...
2. ...
3. ...
4. ...