AAPL finished at $313.25, well below the first 330 call strike. All three legs expired worthless, allowing the full $312 credit to be captured.

What Was Opened

When the trade was opened, AAPL already looked stretched after a sharp rebound into the upper end of its recent range.

The stock kept pushing higher for another couple of weeks, but the technical picture was becoming increasingly difficult to ignore. Momentum was extended, price was pressing into resistance, and the setup was pointing to a loss of upside momentum rather than another clean leg higher.

The move finally reset around the late-July earnings window.

AAPL rolled over sharply, momentum weakened, and the stock moved back below the area that had looked overheated at entry. From there, the position had exactly the environment it needed: no sustained upside follow-through and plenty of distance from the 330 call strike.

The timing took patience, but the original technical read ultimately played out cleanly.

Trade Recap

Entry Date: July 9, 2026
Expiration: August 7, 2026
Contracts: 3

Long Call: 330C
Short Calls: 335C
Upper Long Call: 360C

Credit Received: $312
Broker Commissions: -$6.41
Net P/L After Broker Fees: +$306

👉 View on OptionStrat
👉 View in Trade Log

Final Takeaway

One more thing is worth watching here: AAPL’s weekly chart.

Last week produced what is effectively a bearish engulfing reversal after the stock had stretched into the $340 area. The rejection was sharp, the prior upside momentum broke, and price closed the week back near $310.

That changes the short-term picture.

Until AAPL can reclaim that failed breakout area, I would treat the weekly setup as bearish for the next several weeks and expect rallies to face more resistance than they did during the July advance.

The options trade is finished. The chart may not be😎

Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

I would find an interesting stock in TC2000, study the daily, weekly and monthly charts, check whether the move was extended, and mark the levels that mattered. Then I would open other resources to review expiration dates, expected move, implied volatility, earnings, and the option chain. If a possible structure began to make sense, I would move to OptionStrat and start testing strikes.

This workflow gave me plenty of information, but it left one important decision entirely manual.

I could explain why the underlying was interesting. I could also build almost any options structure once I had chosen it. The difficult part was deciding which structure deserved attention in the first place.

A strong chart does not answer that question. Neither does an option chain. Even a good payoff calculator expects me to arrive with a strategy already in mind.

Over time, I realized that this gap was taking up more of my research than the actual construction of the trade. I was repeatedly combining the same pieces of information and trying to decide whether the current setup called for a credit spread, a debit spread, a butterfly, a condor, a ratio structure, or something else.

That is the problem I built Options Playbook to solve.

Strategy Selection Comes Before Trade Construction

Many options tools are designed around a strategy-first workflow.

You select a call spread, a butterfly, an iron condor, or another structure. Then you choose the underlying, expiration, and strikes before adjusting the position.

That is useful once the strategy has already been selected.

My own research usually begins from the opposite direction. I first find an underlying that deserves attention. I then need to understand what the chart, expiration, volatility, expected move, earnings calendar, and option chain collectively suggest.

Only after that do I want to choose the structure.

This distinction may sound small, but it changes the entire workflow.

Suppose AAPL is in an established daily uptrend, but the recent advance has already pushed momentum into moderately extended territory. Earnings are approaching, and the options market is pricing an expected move around the event.

Several strategies may appear reasonable in this situation, but each one expresses a different assumption. A Bear Call Spread and a Call Broken Wing Butterfly can both express caution after an extended move, but they behave differently if momentum continues. A Long Put Spread may benefit from a direct reversal, while a premium-selling structure may only need the stock to stop advancing. A long volatility position may appear attractive before earnings, but it still has to overcome the movement already priced into the options.

The selected expiration changes this comparison further. A position that ends before earnings represents a different trade from one that carries the announcement. Calling the setup simply “bullish,” “bearish,” or “neutral” does not provide enough information to choose the structure.

The stock idea is only the beginning. Choosing an options strategy requires a more precise description of what I expect to happen and how I want the position to respond if I am early, partially right, or completely wrong.

Five Questions Before Choosing the Structure

The decision becomes more manageable when the setup is reduced to five practical questions.

🤔 What is the underlying doing?

The daily chart describes the current move, while the weekly chart shows whether it agrees with the broader trend. A short-term rally inside a weak weekly structure is a different setup from a rally supported by both timeframes.

🤔 How extended is the move?

Direction alone is not enough. RSI, momentum, and the recent price path help distinguish a move that may still have room from one that is already stretched and more vulnerable to a pause or reversal.

🤔 What happens before expiration?

The amount of time remaining and whether earnings fall before or after the selected expiration can completely change the trade. A structure that makes sense before an event may be a poor fit when it has to carry the event risk.

🤔 What is the options market pricing?

Expected move, implied volatility relative to realized movement, put-call skew, and liquidity show how expensive the available exposure is and whether the option chain supports the intended structure.

🤔 What does the payoff need to accomplish?

The position may need continued direction, a limited move, time decay, volatility expansion, mean reversion, or protection against a tail event. “Bullish” and “bearish” are not precise enough to answer this question.

These five questions are connected, but one input can change several of the answers at once: the expiration date.

Expiration Changes More Than Time

An expiration date is often treated as something selected after the strategy. In practice, it influences which strategies deserve consideration in the first place.

Take the same AAPL setup shown above and select a near-term expiration.

Options Playbook builds the analysis from the contracts available for that exact date. The daily chart receives more decision weight, the time remaining becomes part of the strategy filter, and the system checks whether earnings fall before or after expiration. Expected move, implied volatility, skew, liquidity, and available strikes are all calculated from that specific option surface.

Now select a later expiration.

The underlying and its current chart have not changed, but the options trade has. The expected move covers a longer period, the volatility surface is different, earnings may now sit inside the trade, and the weekly chart becomes more important. Some strategies become more natural for the new horizon, while others are deprioritized or removed from consideration.

Options Playbook does not take the first result and stretch it across the calendar. Each ticker + expiration combination produces a separate analysis.

That is why the two AAPL screens can show different rankings without contradicting each other. They are answering different questions.

What Options Playbook Calculates

Selecting an expiration starts a new preparation process rather than a simple DTE adjustment. The analysis is organized around five groups of evidence.

Market structure

The product reads up to 120 completed daily bars and up to 100 weekly bars. It evaluates trend, momentum, RSI extension, the recent price path, and any prepared technical signals. Shorter expirations place more weight on daily structure, while longer horizons gradually shift the main thesis toward the weekly chart.

Time and event fit

The selected expiration is assigned to a time horizon, and every strategy has its own policy for that horizon. Earnings timing is evaluated separately, so an event occurring before expiration becomes part of the analysis rather than a generic warning attached to every result.

Volatility pricing

Options Playbook calculates the expected move for the selected expiration, at-the-money implied volatility, recent realized volatility, and the relationship between them. It also measures the difference between put and call volatility around the 25-delta area to understand how directional risk is being priced.

Option-chain quality

The system checks quote coverage, bid/ask spreads, open interest, daily volume, available strikes, and whether implied volatility and Greeks can be calculated across enough of the chain. A theoretically attractive strategy should not rank well if the required contracts are impractical or the market data is incomplete.

Payoff precision

The final question is not simply whether a strategy is bullish, bearish, or neutral. The system compares the actual payoff logic: bounded direction, premium income, target zone, range, convex movement, mean reversion, protection, or another form of exposure. It also compares each selected strategy with its nearest alternative to determine which one expresses the prepared setup more precisely.

👉 Once these five evidence groups are prepared, a high-capability AI model performs the final comparison. It is not given an open-ended request to suggest “the best strategy.” It receives the calculated facts for one ticker and expiration, a fixed strategy catalog, and a strict scoring contract. The model must evaluate all 38 strategies, support every part of the Fit score with available evidence, and return exactly five results.

I deliberately chose a top-tier model for this stage rather than a cheaper lightweight model. That makes each analysis more expensive to run, but this is the part of the product where small differences in timing, volatility, and payoff structure need to be understood correctly.

The output is validated before it reaches the screen. If the model selects an unavailable strategy, cites unsupported evidence, or breaks the required response contract, the result is rejected rather than shown as a confident answer. This keeps the AI useful for interpretation without allowing it to wander beyond the market data and strategy rules built into Options Playbook.

From 38 Strategies to the Top Five

The final result contains five strategies ranked by their fit with the selected market setup and expiration.

Each Fit score is built from the five evidence groups described above, allowing the final ranking to reflect more than a simple directional opinion.

The score is not a probability of profit and should not be read as one. It is a comparative measure that shows why one structure fits the prepared conditions better than another.

Each strategy includes two short explanations. The first describes the market bet expressed by the payoff. The second explains why that payoff is more suitable than a nearby alternative.

The Fit panel opens the evidence behind the score, including the market, timing, volatility, and chain facts used for that particular result. This makes it possible to see whether a strategy ranked well because of the trend, the expected move, relative volatility pricing, event timing, liquidity, or the shape of its payoff.

The strategy name then opens the corresponding structure in OptionStrat, where the position can be inspected and adjusted further.

Where Options Playbook Fits in the Workflow

Options Playbook does not replace TC2000, TradingView, or another charting platform. Those tools remain better suited to scanning the market and doing detailed technical work.

It also does not replace OptionStrat. Once a strategy has been selected, OptionStrat remains a useful environment for adjusting strikes and studying the payoff.

Options Playbook fills the space between them.

The charting platform helps identify the underlying. Options Playbook compares the structures that fit the underlying’s current market context and selected expiration. OptionStrat then provides the next layer of position modeling.

That missing handoff was the reason the product was built.

When I first wrote about the idea in June, its working name was Options Decision OS. The planned strategy universe was smaller, and much of the product still existed as a scoring concept rather than a complete workflow. The public product is now called Options Playbook, and its first complete version is live at options.10delta.io.

Try Options Playbook

You can select an underlying, review its daily and weekly context, choose any available expiration, and see how the strategy ranking changes.

Market context is available before analysis. A free account includes three complete strategy analyses, with one new complimentary analysis available per market day. Membership provides ongoing access across the available tickers and expirations.

This article introduces the complete workflow, but each part deserves a closer look. Future posts will cover expiration selection, expected move, implied versus realized volatility, options skew, liquidity, earnings, and the reasons two expirations on the same underlying can lead to very different strategies.

The objective is not to remove judgment from options trading. It is to make the first strategy decision more structured and easier to examine.

Always yours,
— Mansur

Disclaimer

All content is for informational purposes only and does not constitute financial advice. Any trades or strategies should be tested in a simulated environment before use. Trading involves risk, and all decisions are the sole responsibility of the reader.

The position was not built on a market collapse.

It was built on a slowdown.

After a strong advance from the April lows, IWM had reached the upper end of its recent range with price extended above the main moving averages and short-term momentum already stretched.

The broader trend remained intact, but the move was no longer early.

That distinction mattered.

The trade did not require IWM to reverse sharply. It only needed the ETF to stop advancing efficiently, spend time consolidating, or pull back from its recent highs.

Over the following weeks, that is exactly what developed.

Price struggled to produce sustained upside follow-through above the $300 area. The daily chart shifted from persistent expansion into a slower, more rotational structure.

Momentum weakened without turning into a disorderly selloff.

RSI cooled as the upside extension faded, while the daily MACD histogram moved below zero and confirmed a loss of short-term momentum.

The turning point was not a dramatic decline.

It was the absence of another sustained move higher.

As IWM remained below the call structure, time decay continued working in favor of the position. The 314 and 315 strikes were never placed under meaningful pressure during the final stage of the trade.

By expiration on July 24, IWM remained comfortably below the entire risk zone.

All three call legs expired out of the money.

Full premium captured.

Trade Recap

Structure: Call Broken Wing Butterfly
Entry Date: June 24, 2026
Expiration: July 24, 2026
Contracts: 4

Long Call: 314C
Short Calls: 315C
Upper Long Call: 330C

Credit Received: $518
Net P/L After Broker Fees: +$513

👉 View on OptionStrat
👉 View in Trade Log

Post-mortem

The structure stayed fully out of the money through expiration, allowing time decay to complete the trade.

→ The risk zone remained untouched
→ All call legs expired worthless
→ The full premium was captured

The result: $513 net profit after broker commissions and a 100% return.

Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

The daily chart shows a clean rebound, improving momentum, and price holding above the key short-term moving averages. But after that fast move higher, the setup is no longer early. AAPL is now closer to resistance than support, with RSI back near the upper part of its recent range.

That creates a practical setup for a Call Broken Wing Butterfly options trade.

The idea is not that Apple needs to collapse. The thesis is simpler: after a strong rebound into the low $300s, AAPL may begin to slow down, consolidate, or trade with less upside momentum over the next few weeks.

How the Trade Was Selected

AAPL came through Options Strategist, my Telegram terminal, as part of the Call Broken Wing Butterfly scan.

The ranking screen highlighted AAPL with an RSI reading near 60, which made it a useful candidate for a defined-risk options income setup. It was not the most extended name on the list, but it had the right combination of strength, rebound momentum, and location after a fast move off the lows.

That is the type of setup I want to see for a Call Broken Wing Butterfly.

The chart then confirmed the same basic idea. AAPL has regained momentum, pushed back above the moving averages, and is trading near the top of the recent price structure. The move is strong, but it is also mature enough to justify selling premium above the market rather than chasing the stock higher.

Options Strategist then converted that market condition into a structure: a 330/335/360 Call Broken Wing Butterfly expiring on August 7, 2026.

The selected configuration placed the short call spread well above the current stock price, kept the risk fully defined, and opened the trade for a net credit.

That combination matched the setup I was looking for.

Read more

The trade developed largely as expected. After a strong advance into fresh highs, upside momentum began to cool, allowing time decay to work in favor of the position. Rather than exposing the trade to unnecessary expiration risk, I chose to realize the gain while the original thesis remained intact.

What Was Opened

The position was opened on June 15 after the stock appeared near the top of my Options Strategist rankings. The original idea was straightforward: the trend remained healthy, but the move had become increasingly extended after several weeks of persistent buying.

The expectation was never a major reversal. A period of slower upside progress or sideways price action was enough for the trade to benefit from premium decay while keeping risk fully defined.

Trade Recap

Structure: Call BWB
Opened: June 15, 2026
Expiration: July 17, 2026
Closed: June 26, 2026

Contracts: 3

Exit Prices:
680C Long Call: $2.53
690C Short Call: $2.14
720C Long Call: $1.35

Exit Broker Fees: –$6.38

Net P/L: +$448 (79%)

👉 View on OptionStrat
👉 View in Trade Log

Final Takeaway

Not every profitable trade requires a dramatic market move. Sometimes the best outcome comes from a market that simply slows down enough for probabilities and time decay to do their work.

This trade followed the original plan from entry to exit, resulting in a $448 net profit after commissions while capital was freed for the next opportunity.

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Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

Most of my work is built around defined-risk option structures. I write about the full decision-making process behind the trades: what made a setup interesting, how I looked at the risk, why the structure made sense, and what actually happened after the position was opened.

Over time, my workflow became fairly clear:

⚙️ I use TC2000 for technical analysis. It is my main tool for charts, setups, screeners, and reading price action. For someone else, that tool may be TradingView, Thinkorswim, or something completely different. The name of the platform is secondary. What matters is the ability to understand the market context quickly: trend, levels, momentum, compression, extension, and overall structure.

⚙️ Once an idea becomes interesting, I move to OptionStrat. That is where I start working with the actual option structure: strikes, risk profile, reward profile, price scenarios, volatility changes, and time decay.

I wrote more about this workflow in My Stack section.

Although this workflow works well, I kept running into the same gap: the moment between understanding the chart and deciding which options structure actually makes sense, taking into account expiration, volatility, skew, liquidity, expected move, and other market-specific nuances.

With experience, you can look at a chart and understand quite a lot very quickly. You can see when a move is extended, when price is approaching an important zone, when momentum is fading, when the stock is stuck in a range, or when premium might be worth selling.

The harder part comes after that.

Let’s say I like a specific stock. Let’s say I have a general market thesis. Let’s say I am looking at a specific expiration.

The real question becomes:

🤔 Which options strategy should I even look at first? 🤔

That is the problem I want to solve.

Strategy selection is not just a matter of personal preference. The same stock idea can lead to very different option structures depending on the full market context and the way the option chain is priced at that moment.

Sometimes selling premium makes sense. Sometimes a directional structure is cleaner. Sometimes a time spread is more logical. Sometimes the expected move is too expensive or too cheap, and that changes the entire trade logic. Sometimes the best decision is to leave the setup alone.

I tried to improve this process from different angles.

At one point, I launched my own AI tool for reviewing option trade ideas. It runs on a strong OpenAI model, combined with my own prompts and trading context from real setups. Paid subscribers already have access to it and can use it to discuss setups, scenarios, and risks.

It is useful, especially when there is already a concrete idea on the table.

But even that did not solve the main problem :)

I wanted something more structured than a conversation around an idea. I wanted a system that starts with the market itself: ticker, expiration, volatility, option chain, liquidity, skew, expected move, earnings, trend, and extension. Then, based on that context, it should help identify which strategies deserve attention first.

That is how the idea for a new and much-needed tool started 👇👇👇

The working name is Options Decision OS.

The first version has a simple goal:

→ choose a ticker
→ choose an exact expiration
→ and get a ranked list of option strategies that fit the current setup best.

The key unit is:

ticker + expiration

I want to evaluate a specific market situation at a specific point in time. The same stock can produce different answers across different expirations: this Friday, 30–45 days out, and a much later expiration are very different environments, with different time profiles, volatility behavior, liquidity, movement sensitivity, and risk logic.

The first version will be intentionally focused. It will start with a practical universe of tickers that I personally follow and that have enough liquidity for regular options work:

MU, AMD, IWM, QQQ, TLT, SPY, TSLA, NVDA, AAPL, GOOG, SLV, PLTR, MSFT, GLD, AMZN, META, NFLX.

The strategy universe will also be focused. The current working list includes 16 option structures across several practical categories: directional premium selling, debit spreads, iron condors, iron butterflies, broken wing butterflies, calendars, diagonals, straddles, strangles, and back ratio spreads.

The goal is to work with a practical set of option structures and compare them against the current market context in a consistent way.

The main screen I am working toward is called the Strategy Fit Board.

It should show which strategies are stronger, which are weaker, why they received their scores, and what is driving the result. For me, the explanation matters as much as the ranking. I want to know whether the setup is mainly about direction, time, volatility, skew, mean reversion, premium, compression, or expected move.

⚠️ The project is already in active development.

I am building the data core, connecting market data sources, normalizing option chains, working on IV and Greek calculations, checking data freshness, and shaping the deterministic scoring model that will power the Strategy Fit Board.

In the next parts, I want to show how the system is being built from different angles: the product logic, the Strategy Fit Board, the data layer, option-chain analysis, and the path from raw market data to strategy scores.

My goal is to launch the first minimally usable version in early July 💪

I hope some of you will be among the first to try it, not just as a demo, but as a real tool to study, test, and challenge.

Your feedback will matter a lot at this stage.

Always yours,
— Mansur

Disclaimer

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

The trade did what it was designed to do: QQQ stopped pressing higher, upside momentum cooled, and the defined-risk structure gave me a clean window to take profit before expiration risk became the main factor.

What Was Opened

On June 9, I opened a QQQ Call Broken Wing Butterfly using the July 10 expiration.

The structure was:

Buy 3x 761 Call
Sell 6x 762 Call
Buy 3x 785 Call

This was a bearish/neutral trade built after QQQ had already made a stretched upside move. The goal was not to call a major top. The goal was to use a defined-risk options trade to position for a slowdown, consolidation, or pullback while collecting premium.

That is exactly the type of setup this structure is designed for.

Trade Recap

Structure: Call BWB
Opened: June 9, 2026
Expiration: July 2, 2026
Closed: July 10, 2026

Long Call: 761C
Short Call: 762C
Long Call: 785C
Contracts: 3

Exit Prices:
761C Long Call: $1.65
762C Short Call: $1.54
785C Long Call: $0.31

Exit Broker Fees: –$8.41
Net P/L: +$274 (46%)

👉 View on OptionStrat
👉 View in Trade Log

Final Takeaway

This was a clean execution of the original plan.

The setup started with an overbought RSI extension, the structure gave the trade defined risk, and the exit captured a strong profit before expiration risk became unnecessary.

Final result: +$274 net profit after commissions.

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Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

After a strong advance from the April lows, the ETF is now sitting near the upper end of its recent range and close to the all-time high printed earlier this week. The daily chart still shows a clean uptrend, but the move is no longer early. Price has already extended above the main moving averages, RSI remains elevated, and the short-term upside momentum appears stretched.

That makes this setup interesting for a Call Broken Wing Butterfly.

The trade is not built around the idea that IWM has to collapse. The thesis is simpler: after a persistent upside move, especially in a market environment where sentiment remains fragile, IWM may start to slow down, consolidate, or pull back over the next one to two weeks.

How the Trade Was Selected

IWM came through my private Telegram terminal, Options Strategist, as a candidate for a Call Broken Wing Butterfly structure. The system is designed to surface tickers where RSI extension, option structure, and trade location create a practical defined-risk opportunity.

In this case, IWM stood out because the ETF was not weak. It was strong — and that was the point.

The daily chart showed a steady uptrend with price holding near recent highs. The weekly and monthly charts confirmed the same broader theme: small caps have been moving with real strength, and the trend remains intact. But when an instrument is already pressing near all-time highs while the broader market feels unstable, the risk-reward begins to shift.

Options Strategist helped turn that market condition into a tradable structure. The selected configuration placed the short call spread above the current price, kept risk fully defined, and opened for a net credit.

That combination matched the setup I was looking for.

Read more

At the same time, the weekly chart is starting to show signs of a mature move. RSI remains elevated, and the weekly MACD recently hinted at a possible momentum rollover before today’s strong advance pushed the stock higher once again.

That combination is exactly what makes this Call Broken Wing Butterfly interesting.

The trade is built around the idea that AMD does not need to collapse for the position to work. After months of persistent upside expansion, the stock simply needs to start losing momentum over the next 32 days. A period of consolidation, slower upside progress, or a modest pullback would be enough to support the thesis while keeping risk fully defined.

How the Trade Was Selected

AMD appeared near the top of the Options Strategist Call Broken Wing Butterfly rankings, supported by an RSI reading above 65. The stock was not being selected because it looked weak. Quite the opposite. AMD had already recovered from its latest pullback and was trading back near all-time highs, extending a trend that has been in place since April.

Read more

On the daily chart, price lost the short-term moving average, tested the 50-day area, and failed to regain the prior upside channel. The June 5 gap-down session remains the key technical event in this setup.

Momentum also weakened. MACD turned sharply lower, volume expanded during the selloff, and RSI moved back down from elevated levels.

The weekly chart still shows a strong advance from the April lows, but the latest candle suggests momentum has stalled near the highs. That makes QQQ a candidate for a bearish-to-neutral Call Broken Wing Butterfly.

How the Trade Was Selected

QQQ first caught my attention on the chart.

The June 5 gap-down session interrupted the prior advance and shifted the short-term picture from persistent upside momentum to a more neutral setup. The daily chart showed weakening momentum, while the weekly chart suggested the rally from the April lows was beginning to lose strength.

After identifying QQQ as a potential candidate, I used my private Telegram terminal, Options Strategist, to find a structure that matched my trade criteria.

The selected configuration provided a solid net credit and placed the risk zone sufficiently above the current market price. The risk-reward profile fit the setup I was looking for.

The structure met all strategy requirements, and the trade was opened.

Read more

The setup started from an extended upside move. By the time the position was closed on June 5, upside momentum had faded, price pulled back from the highs, and the structure had repriced in our favor.

Trade Recap

Structure: Call BWB
Opened: June 2, 2026
Expiration: July 2, 2026
Closed: June 5, 2026

Long Call: 780C
Short Call: 785C
Long Call: 810C
Contracts: 3

Exit Prices:
780C Long Call: $1.73
785C Short Call: $1.28
810C Long Call: $0.33

Exit Broker Fees: –$5.42
Net P/L: +$369 (69%)

👉 View on OptionStrat
👉 View in Trade Log

What Worked

The key point is that QQQ did not need a dramatic move lower for the trade to work.

The market was already stretched to the upside when the Call Broken Wing Butterfly was opened. After entry, QQQ stopped accelerating higher and started to pull back from the highs. That shift was enough for the position to reprice favorably.

The daily chart also showed the same cooling behavior: price moved off the recent peak, momentum softened, and RSI dropped back from the extended area. For this type of defined-risk options trade, that is the environment where the structure can work well.

This was also a clean management decision. The trade had captured a meaningful portion of the available premium in just a few days. Instead of waiting for expiration or trying to extract every last dollar, the position was closed, the profit was realized, and the remaining risk was removed.

Final Takeaway

This trade did what it was designed to do.

The setup came from an overbought market condition, the structure gave defined risk, and the exit followed the plan once the upside momentum cooled.

A $369 net profit in three days is a strong result — but the main win is process quality: systematic entry, defined risk, active management, and no need to hold the trade into expiration.

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Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

SPDR S&P 500 ETF Trust (SPY) moved exactly into the type of environment this structure was built for: upside momentum slowed, the overbought condition cooled, and the position allowed us to take profit without waiting for expiration.

Trade Recap

Structure: Call BWB
Expiration: June 26, 2026
Long Call: 776C
Short Call: 777C
Long Call: 800C
Contracts: 2
Credit Received: $388
Broker Fees: –$5.30
Net P/L: +$256 (66%)

👉 View on OptionStrat
👉 View in Trade Log

What Worked

The core thesis was simple: SPY was extended to the upside, RSI was elevated, and the move was no longer early.

The trade did not require a sharp selloff. It only needed the market to stop accelerating higher. That is the advantage of using a Call Broken Wing Butterfly in this type of setup.

SPY stalled, pulled back from the highs, and the overbought pressure cooled. That allowed the structure to reprice favorably while time decay worked in our direction.

The important part is that the exit followed the plan. This was never intended to be held into expiration. Once a meaningful portion of the available premium was captured, the position was closed and risk was removed.

Final Takeaway

This was the first closed trade under the updated framework, and it did exactly what I want this strategy to do.

The setup came from a systematic process, the risk was defined from the start, the market condition matched the structure, and the exit was taken before expiration.

A $256 net profit on the first Call BWB is a clean result — not because the trade was perfect, but because the process was clear.

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Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

After several weeks of relentless upside momentum, the Nasdaq ETF has reached one of its most extended technical conditions of the year, with RSI climbing above 79.

Conditions like these push assets to the top of my Call Broken Wing Butterfly rankings.

Earlier today, QQQ was one of them.

I opened a new position designed to benefit from a slowdown, consolidation, or simply less upside than the market currently expects.

How the Trade Was Selected

The process started inside my private Telegram terminal — Options Strategist.

The scanner ranked multiple candidates based on RSI, volatility conditions, liquidity, and structure quality.

QQQ immediately stood out.

At the time of entry:

Read more

Today I’m closing the trade with a realized gain of:

+$57.50 (+27%)

Entry structure:

• +1 270C 29 May

• -2 280C 29 May

• +1 295C 29 May

• -1 245P 29 May

• +1 240P 12 Jun

Position management result:

• 240P Jun 12: -$0.83

• 245P May 29: +$0.57

• 270C May 29: -$0.25

• 280C May 29: +$0.63

• 295C May 29: -$0.16

Net result:
+$57.50

OptionStrat Link: https://optionstrat.com/8XNbQVuvICAl

The trade worked.

But the bigger conclusion is that I personally do not enjoy managing Flyagonals very much.

The structure is flexible, but it also becomes noticeably more demanding operationally:

• multiple expirations

• more moving Greeks

• more management decisions

• more attention required day-to-day

After trading it live, my current impression is that Flyagonals probably make the most sense on ultra-liquid index products like SPX, SPY, QQQ.

For now, I’m not planning to continue actively trading Flyagonals.

Instead, I’ll be focusing primarily on Call Broken Wing Butterflies, which currently fit my execution style much better:

• cleaner management

• more intuitive positioning

• simpler adjustment logic

• less operational friction

The experiment was useful.
The profit is real.
But the main value was understanding what actually fits my process — and what doesn’t.

Disclaimer  

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

This is the first real-money execution after transitioning away from weekly 10-delta credit spreads toward longer-duration asymmetric structures.

How the Trade Was Selected

I used my private Telegram terminal — Options Strategist — to scan for setups based on:

• elevated RSI;

• strong upside extension;

• acceptable implied volatility;

• liquid option chains.

The scanner returned several candidates:

Read more

The main conclusion was simple: the market idea behind 10 Delta Playbook still makes sense. Markets often reach zones of stretched momentum where continuation becomes less efficient, while option premium remains attractive enough to structure a defined-risk trade around that condition.

What needed to evolve was the structure.

A simple weekly credit spread does not always provide enough space when a strong move continues longer than expected.

That is why the next phase of 10 Delta Playbook will be built around a more mature options structure:

👉 Call Broken Wing Butterfly 👈

This framework is an evolution of the original credit spread logic — built around the same premium-selling philosophy: stretched movement, elevated RSI, rich premium, defined risk, and probability-based positioning.

What changes is the structure itself: more time, more asymmetry, and a more flexible risk geometry better suited for continuation-heavy market conditions.

Why 10-Delta Bear Call Spreads Worked for So Long

For almost a year, my weekly workflow revolved around 10-delta credit spread structures — primarily Bear Call Spreads, with occasional Put Credit Spreads built around the same probability-driven logic.

Over that period, I publicly documented 52 structured trades built around the same probability-driven framework: stretched upside movement, elevated RSI, rich premium, and defined-risk positioning through short-duration credit spreads.

The series remained highly consistent for a long time — until one sharp failure exposed how sensitive a narrow weekly structure can become when momentum expansion continues much further than expected.

Where a Simple Credit Spread Becomes Limiting

The core logic behind credit spreads still makes sense to me: sell premium around stretched conditions, define the risk upfront, and let probability and time work together.

The limitation appears in the structure itself:

A narrow weekly spread becomes increasingly sensitive when momentum continues expanding longer than expected. As expiration approaches, the trade compresses into a much more timing-dependent position, leaving very little flexibility if the original idea is correct but early.

That is ultimately what pushed me toward a structure that keeps the same premium-selling philosophy, but provides more space, more asymmetry, and a more adaptive payoff profile.

Credit Spread vs Broken Wing Butterfly

The idea finally crystallized after studying SMB Capital’s discussion:

What immediately stood out to me was that Broken Wing Butterfly was not some completely different philosophy. Structurally, it felt like a more advanced evolution of the same premium-selling logic I had already been trading through weekly credit spreads.

The important point: Broken Wing Butterfly does not replace the philosophy behind credit spreads. It extends it into a more flexible and structurally balanced framework.

This is the key comparison:

That is why I do not see BWB as a completely different strategy.

I see it as the next structural evolution of the same framework.

Why the Focus Is Now Around 30 DTE

Weekly trades were fast and efficient, but short expirations create heavy timing pressure. If momentum continues for several more sessions, a narrow weekly structure can become rigid very quickly as gamma exposure accelerates into expiration.

That is why the new framework shifts toward structures opened around ~30 DTE.

The purpose of the longer duration is not to hold positions into expiration, but to open trades with a more stable and flexible risk structure from the start.

In practice, most positions will still be managed actively and often closed much earlier — frequently within about a week — depending on how the price action develops.

The framework now prioritizes structurally balanced entries and active position management instead of expiration-dependent execution.

How the New Framework Works

Broken Wing Butterfly structures need liquidity. They need reliable option chains, tight bid/ask spreads, working greeks, and the ability to quickly check the full structure in OptionStrat.

That is why the current asset universe is limited to:

SPY, QQQ, IWM, AMD, AAPL, MSFT, TSLA, NVDA, AMZN, META, SLV, GLD, TLT, NFLX, GOOG, MU, PLTR.

The new selection logic works like this:

1. RSI and volatility rank are evaluated first.

2. Assets with elevated RSI and strong prior upside expansion become primary candidates.

3. Expiration is selected around ~30 DTE.

4. The short center call is selected around 20-delta.

5. The lower call wing is selected around roughly 70% of the short call premium.

6. The upper call wing is selected cheaper, roughly around 15% of the short call premium.

7. The structure must open for at least ~$100 net credit per 1-contract structure.

8. SAFE structures pass a max-loss filter of up to roughly ~$2,000.

9. HIGH_RISK structures may still appear if the minimum credit threshold remains attractive.

A Private Terminal for the New Phase

After a year of preparing trades manually, it became clear that the next version of the framework needed to be more than an idea. It needed to become a working tool.

That is why I built Options Strategist —
a private Telegram terminal for paid subscribers.

It is not a signal bot and it does not replace judgment with a button.

Its purpose is to automate structure preparation inside a clearly defined framework.

It handles the parts that take time manually and can easily break under pressure:

✅ filters liquid assets and option chains;

✅ prepares asymmetric Broken Wing Butterfly structures automatically;

✅ validates credit, risk, and structure quality;

✅ blocks unstable or incomplete market data;

✅ generates direct OptionStrat links with the full structure already built.

Paid subscribers get direct access to this workflow through Telegram authorization using the same email address tied to their subscription.

This is where preparation for new weekly structures will now begin.

What Changes Now in 10 Delta Playbook

The old weekly credit spread framework is now retired as the primary structure inside the project.

From this point forward, the focus shifts toward systematically built Call Broken Wing Butterfly positions executed through the new framework and workflow described above.

A new public trade log will continue to be maintained transparently, with real-money positions, real entries, real exits, and fully documented weekly execution.

Some weeks may produce one setup. Some weeks may produce several. But the process itself will remain systematic.

The goal now is not simply to find premium. — The goal is to continue refining a repeatable and structurally disciplined approach to options trading in public.

Thank you to everyone following the project so far.

More structures ahead.

— Mansur

Disclaimer 

All content is for informational purposes only and does not constitute financial advice.Any trades or strategies should be tested in a simulated environment before use.Trading involves risk, and all decisions are the sole responsibility of the reader.

Up until now, most of my options trading has been focused on weekly credit spreads, mainly Bear Call Spreads. But Flyagonal caught my attention because it creates a much more flexible payoff structure with multiple profit scenarios instead of a simple linear profile.

So I decided to start with a small test trade and study:

• how the structure behaves in real market conditions

• how the P/L evolves day by day

• how the Greeks change over time

• how manageable the position feels

• and whether Flyagonals fit my trading style at all.

For this first trade, I narrowed the market down to highly liquid names with weekly options and tight bid/ask spreads:

• AMZN

• SPY

• IWM

• QQQ

• META

• NVDA

• AAPL

• NFLX

• SLV

• TLT

Then I analyzed each ticker using:

• Daily timeframe

• Weekly timeframe

• Monthly timeframe

The indicators were intentionally simple:

• EMA 21

• EMA 50

• Bollinger Bands

• RSI

• ATR

The goal was not to predict a huge directional move, but to find a stock with:

• strong liquidity

• healthy movement

• controlled momentum

• and enough room for a Flyagonal to work properly.

Amazon.com Inc (AMZN) ended up being the best candidate.

Read more

I don’t want to turn this article into a detailed breakdown of that specific trade. Situations like this are inevitable when you work with short premium and weekly credit spreads. What matters much more is understanding how I gradually arrived at this point, where exactly my process started drifting away from its original structure, and what I plan to change moving forward.

Where the system actually started breaking down

When you trade 10-delta Bear Call Spreads, you accept the nature of the structure from the very beginning. Most of the time, the market never reaches your short strikes, theta works in your favor, and time decay outpaces price movement. That’s exactly why these strategies can look incredibly stable, especially over dozens of trades.

But there’s a subtle psychological problem built into that stability. After a long enough streak of smooth outcomes, your perception of risk begins to change. Especially when several previous trades survived uncomfortable situations and still ended up as winners.

Originally, my system was never based on the simple idea of “this stock is overbought”. The foundation was different. I was looking for actual signs of momentum exhaustion through specific reversal patterns — bearish engulfings, evening stars, failed breakouts, dark cloud cover formations, and similar setups. In other words, overextension by itself was never enough for me to enter a trade. I also wanted evidence that the move was beginning to lose structural strength.

Over time, I started drifting away from that principle. Not because I consciously decided to change the strategy, but because I slowly adapted the process to my own publishing and trading rhythm. I developed a habit where every week was supposed to produce a new trade. And that’s where an important shift happened: instead of waiting for truly high-quality setups, I increasingly started looking for stocks that were simply stretched enough and offered acceptable premium.

That becomes especially dangerous in a strong bull market. Over the past several months, major indexes kept printing new highs, strong tech names continued grinding upward with very little meaningful pullback, and many trades that honestly no longer met my original standards still ended up profitable anyway. Those are exactly the kinds of environments that quietly weaken discipline, because the market starts rewarding behavior that technically shouldn’t be rewarded.

In that sense, MU wasn’t some bizarre outlier. If anything, it was the natural conclusion of a process that had started much earlier. I gradually began confusing simple overextension with actual reversal setups, even though those are two very different things. A stock can stay stretched far longer than feels rational, especially during aggressive momentum expansion phases. Credit spreads can create a long-lasting illusion of control right up until the market suddenly moves into the exact tail-risk scenario the strategy is designed to carry.

A limited universe — and the trap of weekly execution

There’s another important factor that I underestimated for a long time.

My trading universe is not “the entire market”. I monitor a relatively limited group of liquid names with weekly options and meaningful premium — roughly 50 to 60 stocks out of the entire market. And the reality is that truly high-quality reversal setups simply do not appear there every single week.

Of course, you can still force a trade. You can find an extended chart, elevated RSI, high implied volatility, and convince yourself the premium looks attractive enough. But that doesn’t automatically mean there’s real edge in the setup.

At the same time, staying engaged with the market every week also had genuine benefits. Running at least one position weekly kept me closely connected to market structure. I was consistently tracking volatility, momentum, earnings reactions, sector rotation, and overall index behavior. Without that rhythm, I probably would have become much less systematic and much more random in how I observed the market.

But now I realize there’s a major difference between participating in the market to maintain discipline and participating in the market simply because the calendar says it’s time for another trade. At some point, I started mixing those two things together.

What happens after a major loss

After a trade like this, you enter a psychological state that almost every trader probably recognizes. The immediate impulse is to make the money back quickly. Open another position. Increase size. Prove to yourself that the previous outcome was just bad luck.

And that’s exactly where many traders completely destroy their systems, turning one controlled loss into a chain of emotional decisions.

That’s why I’m consciously stepping away from live trading for now. Not because I suddenly stopped believing in options trading, and not because I think the market is “wrong”, but because I want to reset the execution side of the process and rebuild discipline properly. Right now, my goal is not to recover losses quickly. My goal is to get back to a state where decisions are made calmly and structurally again, rather than emotionally under the pressure of wanting to repair the previous result.

And separately — about subscribers

After the MU trade, I received a lot of messages, and honestly, that was probably the hardest part of the entire experience.

Despite all the standard disclaimers about risk and the fact that nothing I post is financial advice, it’s obvious that some people were following my trades and took losses as well. Formally speaking, trading is always the responsibility of the individual participant. But when you publicly document positions, explain entry logic, publish management plans, and share trade reviews, it’s impossible to completely detach yourself from that reality emotionally.

What surprised me, though, was something else. 🤝 Most of the messages were not complaints. They were expressions of interest in continuing to follow the process moving forward. And honestly, that became one of the main reasons I decided not to shut everything down after this experience, but instead approach the next phase of the project much more seriously.

What comes next

Read more

Up until Thursday, the trade was behaving relatively нормально. Momentum was still strong, but price action started slowing down a bit after the initial gap, with a doji forming near the highs.

That changed quickly on Friday.

Read more

The trend is still intact — but extension is becoming more aggressive.

This is not about calling a top.
This is about positioning into stretched conditions where continuation requires sustained momentum.

Read more