A busy week of put-selling, early closes, and four new assignments across the Wheel engine.

This digest covers the simulated paper-trading account run by CCO+Precursive Intelligence. No real capital is at risk -- every figure below reflects activity inside the simulation only.

This Week's Activity

The engine opened 17 new trades between September 21 and September 25, collecting $28,817.42 in premium. Of those, 14 were cash-secured puts across a mix of names including PANW, DDOG, META, UPS, DELL, AMD, NVDA, ANET, SMCI, MSTR, and BA, and 3 were covered calls written against BA, COF, and UPS positions.

Four puts were assigned this week, bringing shares into the portfolio: COF at $205.00, BA (300 shares) at $200.00, UPS at $95.00, and CLX (300 shares) at $85.00.

There were no options that expired worthless this week. Instead, the engine closed 10 put positions early across DELL, AMD, MPC, ANET, SMCI, NVDA, MSTR, META (two separate closes), and DDOG, locking in combined net gains of $13,903.13 and releasing collateral back to available cash in the process.

In total, the account logged 31 transactions this week.

Portfolio Snapshot

As of the current cumulative state (not this week's activity alone):

• Total portfolio value: $1,053,882.68 (starting value: $1,000,000.00)

• Cash: $939,905.68

• Available cash: $131,405.68

• Open stock holdings: 4 positions

• Open covered calls: 3

• Open cash-secured puts: 16

• Total premium collected since inception: $67,661.38

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.

One real trade from the CCO paper wheel, and the wheel-strategy concept it illustrates.

What actually happened: Assigned 100 shares at $95.00. Acquired into portfolio.

Assignment isn't the trade going wrong

Getting assigned on a cash-secured put means the stock finished below the strike and shares get put to you at that price. Within the wheel, that's not a failure state -- it's stage two. The premium already collected lowers the effective cost basis, and the position immediately becomes eligible for covered calls instead of cash-secured puts.

This is a real trade from CCO's paper wheel, not a hypothetical -- the numbers above are exactly what the account did, not a textbook example built to illustrate the concept cleanly.

See the live paper-trading tracker →

Ten early closes, six new puts, and a fully cash-secured book.

This post covers CCO's simulated paper-trading account. No real capital is being deployed here -- every trade, dollar, and position below is part of an ongoing paper simulation of a covered-call/cash-secured-put "Wheel" strategy.

This Week's Activity

The account opened 6 new cash-secured put positions this week, collecting $4,251.68 in premium:

• MPC -- 3 puts, $365 strike, exp 10/20, $1,622.22 collected

• ANET -- 3 puts, $165 strike, exp 10/20, $1,193.43 collected

• BA -- 3 puts, $200 strike, exp 10/20, $545.40 collected

• SMCI -- 3 puts, $30 strike, exp 10/20, $429.45 collected

• CHRW -- 2 puts, $145 strike, exp 10/20, $340.94 collected

• COP -- 2 puts, $125 strike, exp 10/06, $120.24 collected

On the other side of the ledger, 10 previously open puts were closed early this week, generating a combined net P&L of $8,221.90. Tickers involved: MPC, ANET, BA, CHRW, SMCI, COP, PANW, DDOG, META, and UPS. Standout closes included PANW (+$2,294.13) and DDOG (+$1,982.49). Each early close also released its associated collateral back to available cash.

There were no assignments and no expirations this week -- every position that closed did so via an early buy-to-close.

Portfolio Snapshot

As of the current cumulative state (not a weekly figure):

• Total portfolio value: $1,032,395.26

• Total cash: $1,032,395.26

• Available cash: $283,395.26

• Open holdings: 0

• Open calls: 0

• Open puts: 16

• Total premium collected to date: $38,843.96

• Starting portfolio value: $1,000,000.00

The account currently holds no shares, running entirely on 16 open cash-secured put positions.

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.

A paper-trading log of this week's Wheel strategy activity.

This update covers the simulated paper-trading account run by CCO+Precursive Intelligence. No real capital is involved — every figure below reflects a paper-trading engine executing the covered-call/cash-secured-put "Wheel" strategy on simulated positions.

This Week's Activity

The engine opened 26 new cash-secured put positions between September 7 and September 11, collecting $34,592.28 in premium. Tickers involved included DELL, AMD, PANW, DDOG, MPC, MSTR, ANET, ORCL, CHRW, META, BA, USO, SMCI, NVDA, SLB, COF, COP, UPS, CLX, and TGT, with expirations ranging from late September through mid-October.

Six puts were closed early during the week, across CHRW, META (three separate positions), AMD, ORCL, and USO. These early closes generated a combined net P&L of +$5,965.40 and released the associated collateral back to available cash.

There were no assignments and no options expired this week.

In total, the account logged 32 transactions this week.

Portfolio Snapshot

As of the current cumulative state, the portfolio holds a total value of $1,031,724.40, up from a starting value of $1,000,000.00. Total cash on the books stands at $1,031,724.40, with $2,724.40 of that currently available (the remainder is tied up as collateral against open positions). There are no open stock holdings and no open covered calls. The account currently carries 20 open cash-secured puts. Cumulative premium collected to date totals $34,592.28.

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.

Pairs trading has a well-documented problem. It worked reliably in the 1980s and 90s, when a handful of desks were the only ones running it. Academic research since then (Do and Faff, 2010 and 2012) has tracked the strategy's profitability declining steadily as it went from a proprietary edge to something everyone knew how to do. The reason most often cited: pairs were selected on correlation, not on any test of whether one name's moves actually predicted the other's. A lot of "relationships" that looked tradeable were just noise that happened to line up.

That's close to the same discipline CCO's entry-timing signal is built around: don't act on a number in isolation, check whether it's actually informative first. So we asked a direct question. Does the same idea, applied to pairs trading instead of options premium, do anything useful?

What we tested

Two versions of the same trade, run against ten years of real price data (2015 to 2024), a $1 million starting capital, and a 16-stock universe spanning tech, financials, energy, healthcare, consumer, and industrials. Every week, each version looks for a relationship between two stocks and, if it finds one, bets that a follower stock will move the same direction a leader stock just moved.

The two versions differ only in how a "relationship" gets identified.

The naive version uses simple correlation. If two stocks have moved together over the trailing 90 days, that's a relationship, and whichever one moved more this week is treated as the leader. No test of whether that correlation means anything predictive. This is the crowded, "everyone already knows this" version of the trade.

The gated version uses Granger causality instead. This is a specific statistical test: does stock A's past returns carry information about stock B's future returns, beyond what B's own history already tells you. It's a harder bar to clear than correlation, and we applied Holm-Bonferroni correction on top of it, which controls for the fact that testing hundreds of pairs at once will turn up some false positives by chance alone.

Same starting capital, same universe, same time period, same position sizing. The only variable is which test decides a relationship is real.

What happened

The naive version lost 58.72% of the portfolio over ten years. Sharpe ratio of -0.31. Max drawdown of -60.54%. It traded constantly: 4,551 trades, nearly two a day.

The Granger-gated version lost almost nothing: a total return of +0.35% over the full decade. Sharpe ratio of 0.01. Max drawdown of -7.92%. It traded far less: 133 trades over ten years, roughly one every three weeks.

What this actually means

The gate did its job. It avoided a strategy that would have cut the portfolio in less than half. That's a real result, and it's consistent with everything the academic literature says about this trade: the naive version of pairs trading really has stopped working, and trading it anyway is a losing proposition.

But the gated version isn't a profitable strategy either. A ten-year total return of 0.35% and a Sharpe ratio of 0.01 is statistically indistinguishable from holding cash. The discipline correctly recognized that most weeks, there's no real signal here, and it mostly stayed out. That's honest behavior from the model. It is not the same as finding a new edge.

We think this is worth being direct about, because it would have been easy to publish the comparison between -58.72% and +0.35% and call it a win. It is a win, in the narrow sense that avoiding a large loss is valuable. It is not evidence that Granger-causality gating turns pairs trading back into something you'd want to trade for its own sake.

Where this leaves things

This is one specific design: momentum transfer, betting the follower moves the same direction as the leader. We're also testing a second, more classic version of pairs trading, betting on reversion instead of continuation, using the same gate. That result is a separate piece, because the two designs are different enough that they deserve to be judged on their own.

For CCO specifically, the honest takeaway is this: our signal's real strength so far looks like it's on the risk-avoidance side, not the signal-generation side. That's a more modest claim than "this makes any strategy profitable," and we'd rather publish the modest, accurate version.

CCO+Precursive Intelligence runs a systematic cash-secured-put wheel, with an entry-timing signal that skips writing into compressed volatility. See the live paper book →

Last week we published results from testing whether our entry-timing discipline could revive a specific version of pairs trading: betting a follower stock continues in the same direction a leader stock just moved. The honest answer was no. Our signal avoided a large loss the naive version of that trade produced, but the gated version wasn't profitable either, just closer to flat.

Pairs trading has another, more classic form, and it deserves its own test rather than being lumped in with the first result. Instead of betting on continuation, it bets on reversion: when two related stocks drift apart further than their history suggests they should, buy the one that's lagged and sell the one that's run ahead, betting the gap closes.

What we tested

Same ten-year period (2015 to 2024), same $1 million starting capital, same 16-stock universe as the first test. Every week, each version looks at the spread between two stocks' recent returns. If that spread has stretched further than about two standard deviations from its own recent average, a bet on convergence: long the laggard, short the leader.

The two versions again differ only in how the pair itself gets selected. The naive version uses any two stocks correlated above a threshold, no causality test. The gated version restricts this to Granger-causal leader and follower pairs, the same statistical test used in the first study, requiring one stock's past returns to carry real predictive information about the other's future returns, corrected for testing many pairs at once.

What happened

The naive version lost 7.6% over the ten years. Sharpe ratio of -0.08. Max drawdown of -12.5%. It made 1,722 trades.

The gated version lost 0.71%. Sharpe ratio of essentially zero. Max drawdown of -13.37%, about the same as the naive version. But it made far fewer trades, 113 over the decade, and won 65.5% of them, a genuinely strong win rate.

The part worth sitting with

That combination, a 65.5% win rate against a Sharpe ratio of roughly zero, is a specific and recognizable pattern. It means the strategy wins often, in small amounts, and loses rarely, in amounts large enough to erase most of what the frequent small wins built up. Traders sometimes call this picking up nickels in front of a steamroller. It's a known risk in mean-reversion strategies generally: a spread that looks stretched can keep stretching instead of reverting, and a design with no stop-loss on that scenario will eventually meet one of those trades.

That's a specific, fixable observation about this particular design, not a verdict on Granger-causality gating itself. Our test held every position for a fixed number of days regardless of how the trade was performing while it was open. A version that closed out early when a spread kept diverging instead of reverting might tell a different story. We haven't built that version yet.

Where this leaves things

Two different pairs-trading designs, tested independently, arrive at the same qualitative place. The Granger-causality gate is a real, consistent risk-reduction tool: in both tests, it cut the loss substantially and improved the win rate. In neither test did it produce a strategy worth trading for its own profit. Naive correlation-based pairs trading looks exactly as dead as the research on it says it is, gated or not.

We're publishing both results because the honest answer to "can your signal revive a crowded strategy" is turning out to be more specific than yes or no. It depends on what you're asking the signal to do. Asking it to avoid a bad trade, it does that reliably. Asking it to manufacture a profitable one out of a signal that's genuinely lost its edge is a different question, and so far the data says no.

CCO+Precursive Intelligence runs a systematic cash-secured-put wheel, with an entry-timing signal that skips writing into compressed volatility. See the live paper book →

A quiet week in the paper-trading log.

This post covers the simulated paper-trading account run by CCO+Precursive Intelligence. No real capital is being used -- every figure below reflects a paper portfolio designed to test the Wheel options strategy (covered calls and cash-secured puts) under real market conditions.

This Week's Activity

There was no trading activity this week. No new positions were opened, no premium was collected, and there were no assignments, expirations, or early closes to report. Total transactions for the week: zero.

Portfolio Snapshot

As of the current cumulative state, the account holds:

• Total portfolio value: $1,000,000.00

• Cash: $1,000,000.00 (all of it available)

• Open holdings: 0

• Open calls: 0

• Open puts: 0

• Total premium collected to date: $0.00

• Starting value: $1,000,000.00

The portfolio remains fully in cash with no open positions at this time.

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.

Every option has a price, and every option price is built from a handful of inputs: the stock price, the strike, the time left until expiration, and one input that isn't a fact at all but a forecast. That forecast is implied volatility, and understanding what it actually represents is the difference between reading a premium number and understanding where it came from.

IV is the market pricing in uncertainty, not direction

Implied volatility is the options market's collective estimate of how much a stock is likely to move over a given period, expressed as an annualized percentage. It says nothing about which direction the move will go. A stock with 20% implied volatility is being priced as though it could plausibly swing about 20% over the next year, up or down, with the actual range narrower for shorter time frames. A stock with 60% implied volatility is being priced as though its potential range of outcomes is three times wider.

This is worth sitting with because it's easy to conflate volatility with risk in a vague, negative sense. IV isn't a judgment that a stock is bad or dangerous. It's a statement about dispersion of outcomes. A biotech name awaiting a clinical trial readout can have very high IV without anyone believing the news will necessarily be bad. The market is simply acknowledging that the range of plausible outcomes, good or bad, is wide.

Why wider uncertainty means richer premium

For a cash-secured put or covered call seller, this matters directly because option premium is compensation for taking on the other side of that uncertainty. When you sell a put, you're agreeing to buy shares at the strike price if the stock falls that far. The buyer of that put is paying you to accept that obligation. The more uncertain the outcome, the more that obligation is worth, because there's a wider range of scenarios where the stock could fall meaningfully below your strike.

Put two stocks side by side, both trading at $100, both with puts struck 5% out of the money, both expiring in 30 days. If Stock A has 20% implied volatility and Stock B has 50%, Stock B's put will carry a noticeably higher premium for that identical strike distance. Nothing about the strike or the timeframe changed. What changed is the market's estimate of how likely the stock is to actually reach or breach that strike before expiration. Higher IV means a wider distribution of possible prices at expiration, which means more of that distribution falls in territory where the put would be assigned, which means the option is worth more to whoever is buying protection or making a directional bet.

This is the entire mechanical reason "high IV means high premium" is true. It isn't a magic multiplier or a signal that a name is a great trade. It's a direct reflection of the market pricing in a wider range of outcomes, and that wider range is exactly what a seller is being paid to insure against.

The other side of the same coin

This cuts both ways, which is the part that's easy to skip past when premium looks attractive. A stock throwing off a rich premium because its IV is elevated is, by construction, a stock the market believes could move further and faster than a low-IV peer. If that stock drops sharply, a cash-secured put seller is on the hook to buy shares at the strike regardless of how far the stock has fallen below it. The premium collected is compensation for that possibility, not a waiver of it. There is no version of this where the extra income shows up without the extra range of outcomes that produced it.

This is also why comparing IV in isolation, without context, can be misleading. A stock's IV might look high in absolute terms but actually be unremarkable for its sector. Growth-stage tech names and biotech names, as a category, tend to run higher IV than utilities or consumer staples. Looking at a single stock's volatility number without a reference point tells you less than it seems to. What matters is how a stock's IV compares to what's typical for stocks like it right now, not whether the number itself sounds big or small.

Why this matters before you get to mechanics

Everything about wheel strategy premium selection eventually comes back to this relationship. A trader hunting for the richest premium available, without asking why that premium is rich, is often just finding the ticker the market currently sees as most uncertain. That can be a reasonable trade if you understand and accept the risk. It's a much weaker trade if the premium was mistaken for a discount rather than recognized as a fair price for the range of outcomes it's insuring.

None of this is a case against selling premium on higher-IV names. Richer premium for elevated uncertainty is the actual mechanism that makes the wheel strategy function at all. Compensation exists because outcomes are less certain, not despite it. The point is only to make sure the premium number in front of you is understood for what it is: a market estimate of movement, translated into a price, not a verdict on whether a trade is good.

Tomorrow, this post turns to how CCO uses a version of this same volatility comparison, not to chase the richest premium available, but to flag when a ticker's implied volatility looks unusually stretched relative to its own peer group before any new position is proposed.

CCO+Precursive Intelligence runs a systematic cash-secured-put wheel, with an entry-timing signal that skips writing into compressed volatility. See the live paper book →

A calendar is not a market signal. Yet a large share of wheel strategy traders default to one anyway: pick a day, usually Monday, and write the next cash-secured put or covered call regardless of what the option chain is actually pricing that morning. It is easy to understand why this habit forms. A fixed schedule is simple, it removes decision fatigue, and it gives the appearance of discipline. But discipline applied to the wrong variable is not the same thing as a good process.

The variable that actually determines how much you get paid for taking on assignment risk is implied volatility, and implied volatility is not constant. It moves with earnings calendars, macro data releases, sector rotation, and shifts in aggregate risk appetite. A ticker that was paying a healthy premium for a 30-delta put three weeks ago can be pricing that same strike at a fraction of the credit today, with no change to the underlying's fundamentals at all. The option's extrinsic value compresses. The premium shrinks. And if your only trigger for writing is "it's Monday," you sell into that compression anyway, because the calendar told you to.

This is the core problem with schedule-driven entries: they treat every Monday as interchangeable, when in fact the compensation for identical risk can differ substantially from one week to the next. Selling a put obligates you to buy shares at the strike if the underlying falls below it by expiration. That obligation, that risk, does not change based on how much premium you collected for accepting it. What changes is only the price you were paid to take it on. Writing into a period of unusually low implied volatility means you are accepting the same downside exposure for less compensation, structurally, before the trade has even had a chance to move against you.

Put another way: the risk side of a cash-secured put is roughly fixed by the strike and the underlying's behavior. The reward side is the one variable you actually have some control over, and it is entirely a function of when you write, not just what you write. A fixed schedule discards that control. It assumes the market offers a constant rate of pay for risk, and it does not.

There is a second, quieter cost to fixed-schedule writing that is easy to overlook: it trains the trader to stop looking. Once "write every Monday" becomes the rule, the option chain becomes something you glance at only to pick a strike, not something you actually evaluate for whether now is a good time to be selling volatility at all. Over enough cycles, this erodes the very edge the wheel strategy is supposed to rely on, which is that selling options is, on average, a reasonable way to monetize the volatility risk premium, provided you are not consistently selling it cheap.

None of this means fixed schedules are without any merit. Consistency matters for capital deployment, for tracking performance, for keeping a portfolio's assignment risk within manageable bounds. The problem is not consistency itself. It is using the wrong thing, the calendar, as the trigger for a decision that should be sensitive to the actual pricing environment. A trader who writes every Monday during a period of persistently low implied volatility across their whole watchlist is not being disciplined. They are being consistent about accepting bad terms.

What is needed instead is some way to tell, ticker by ticker, whether current implied volatility is actually elevated enough, relative to some reasonable baseline, to justify writing today. Not a fixed threshold like "IV above 30%," because reasonable IV levels differ enormously by sector and by name; a biotech and a utility do not share the same baseline for what counts as rich or cheap. What is needed is a relative measure: how does this ticker's current implied volatility compare to what similar tickers are pricing right now. That comparison is the missing piece that a fixed schedule cannot provide. It requires actually looking at where volatility sits before deciding whether an entry makes sense at all, rather than deciding the entry is happening and then just picking a strike.

This is not a small refinement. It is the difference between a process that harvests the volatility risk premium opportunistically, when the market is actually compensating you well for the risk, and one that harvests it indiscriminately, taking whatever is on offer because the day on the calendar said so. The former is closer to what disciplined premium selling is supposed to look like. The latter is discipline in form only.

The practical question this raises is straightforward, even if the answer requires more nuance than a single number: given that premium is not constant, and given that writing into compressed volatility means getting paid less for the same downside, what would it actually look like to have a signal that tells you, before you write, whether current conditions favor selling premium on this specific ticker right now? That question is where entry timing has to start. A calendar cannot answer it. Something that actually reads volatility can.

Tomorrow's post looks at what implied volatility itself is actually telling you about the premium you are being offered, and why that number means something different for every ticker.

CCO+Precursive Intelligence runs a systematic cash-secured-put wheel, with an entry-timing signal that skips writing into compressed volatility. See the live paper book →

The first leg: selling a cash-secured put

You sell (write) a put option on a stock you'd genuinely be fine owning, at a strike price you'd genuinely be fine paying. You collect a premium immediately, and you set aside cash equal to 100 shares times the strike price — that's the "cash-secured" part. It's collateral, not spending.

Say you sell a $50-strike put for $2.00 in premium. You collect $200 up front (the premium is quoted per share, times 100 shares per contract), and $5,000 sits aside as collateral. From here there are exactly two outcomes at expiration:

• The stock stays above $50. The put expires worthless. You keep the full $200, no shares change hands, and your collateral is freed up to do it again.

• The stock drops below $50. You get assigned — obligated to buy 100 shares at $50, using the collateral that was already set aside.

Assignment isn't a loss — it's the point

A lot of people treat assignment like something went wrong. It didn't. Assignment is the wheel's intended fallback, not a failure state — it's simply the other half of what you agreed to when you sold the put.

And your real cost basis isn't $50. It's $50 minus the $2.00 you already collected — $48 per share — because that premium is already yours regardless of what happens next. If the stock is sitting at $47 the day you're assigned, you're not "down $3." You're down $1, because $2 of the drop is already covered by premium you were paid up front.

The second leg: writing the covered call

Now you own 100 shares at an effective basis of $48. You write a call option against those shares — a covered call, covered because you actually hold the stock behind it — at a strike you'd be genuinely happy selling at. Say a $52 strike for $1.50 in premium. Same two-outcome shape as before:

• The stock stays below $52. The call expires worthless. You keep the shares, keep the $150, and write another call next cycle.

• The stock rises above $52. Your shares get called away — sold at $52, whether the stock is at $53 or $80. You don't get the extra upside, but you keep every dollar of premium collected along the way, plus the gain from your $48 basis up to $52.

In this example: $200 (put premium) + $150 (call premium) + $400 (capital gain, $52 minus $48 basis, times 100 shares) = $750 total, whether or not you ever intended to "trade options" versus just owning the stock outright.

Why it's called a wheel

Sell a put. Either it expires and you do it again, or you get assigned and hold shares. Sell a call against those shares. Either it expires and you do it again, or the shares get called away and you're back to cash. The cycle turns: cash-secured put, assignment, covered call, called away, back to cash. Every leg pays you a premium regardless of which of its two outcomes happens — that's the actual engine behind "the wheel," not a metaphor.

What this series isn't

This isn't a "guaranteed income" pitch, and if anyone tells you the wheel has no downside, they've skipped the part where the stock can fall well below your strike and stay there — you're still holding it, premium collected or not. That's real risk, not a technicality, and it's exactly what the next several posts are about: what actually decides when to write a new position instead of just doing it on a fixed schedule, and what happens when a position moves against you before expiration.

Tomorrow: why writing on a fixed schedule — every Monday, no matter what — is worse than it sounds, and what CCO's engine actually checks before it writes anything at all.

A simulated look inside the Wheel engine's trading week

This update covers the simulated paper-trading account run by CCO+Precursive Intelligence. No real capital is being traded here -- every figure below reflects a paper portfolio used to test and demonstrate the Wheel options strategy.

This Week's Activity

The engine opened 10 new options positions this week, collecting $9,792.88 in total premium:

• MSTR puts: 2 trades, 6 contracts total, $100 strike, expiring 2026-09-28, combined premium $2,414.94

• USO puts: 2 trades, 6 contracts total, $115 strike, expiring 2026-09-28, combined premium $2,102.46

• TGT puts: 2 trades, 4 contracts total, $150 strike, expiring 2026-09-30, combined premium $892.52

• MPC put: 1 trade, 2 contracts, $325 strike, expiring 2026-10-01, premium $1,229.50

• CHRW call: 1 trade, 2 contracts, $180 strike, expiring 2026-10-01, premium $1,228.90

• PANW puts: 2 trades, 2 contracts total, $330 strike, expiring 2026-10-02, combined premium $1,924.56

One assignment occurred this week: the CHRW puts were assigned, adding 200 shares to the portfolio at $165.00/share.

Five positions were closed early, all for gains, totaling $3,876.90 in combined net P&L:

• GS put closed early: +$1,214.85

• MPC put closed early: +$943.08

• UPS put closed early: +$295.23

• MSTR puts closed early (2 trades): +$711.87 each, +$1,423.74 combined

No positions expired this week.

Portfolio Snapshot

As of this week's close, the cumulative state of the paper portfolio stands at:

• Total portfolio value: $1,056,711.61

• Cash: $1,026,633.61 (of which $37,633.61 is available/uncommitted)

• Open holdings: 1 stock position

• Open options: 20 puts and 1 call currently open

• Total premium collected since inception: $77,456.31

• Starting portfolio value: $1,000,000.00

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.

A week of active put rotation across the Wheel book, with early closes locking in gains ahead of new positions.

This digest covers CCO's simulated paper-trading account. No real capital is at risk here -- every trade, dollar, and position referenced below exists only within the strategy's simulation engine.

This Week's Activity

The engine opened 13 new cash-secured put positions this week, collecting $22,670.44 in premium. Trades spanned 11 tickers, including DELL, DDOG, MPC, ANET, MSTR, UPS, AMD, GS, COF, CLX, and SLB, with expirations set for September 21 and September 24, 2026.

Seven put positions were closed early this week, across AMD, GS, COF, CLX, SLB, USO, and MSTR, for a combined net gain of $6,523.82. Each early close also released its associated collateral back into available cash.

There were no assignments and no expirations this week -- all closed positions were exited early, ahead of their contractual expiration dates.

Portfolio Snapshot

As of the current cumulative state:

• Total portfolio value: $1,052,628.34

• Total cash: $1,052,628.34

• Available (uncommitted) cash: $75,128.34

• Open stock holdings: 0

• Open put positions: 17

• Open call positions: 0

• Total premium collected since inception: $67,663.43

• Starting portfolio value: $1,000,000.00

The account currently holds no assigned shares -- all capital deployed is tied up as collateral against the 17 open put contracts.

You can follow this strategy in real time or set up your own version using the links below.

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.

A look inside the Wheel: new puts sold, a wave of early closes, and where the paper book stands now.

This update covers CCO's simulated paper-trading account. No real capital is at risk — every trade, dollar, and position referenced below is part of an ongoing paper simulation of a cash-secured put / covered-call "Wheel" strategy.

This Week's Activity

New positions opened: 8 cash-secured puts were sold this week across SLB, SMCI (two separate strikes/dates), NVDA, PANW, DELL, ORCL, and DDOG, collecting a combined $3,293.12 in premium.

Early closes: The bulk of this week's activity was closing existing puts ahead of expiration. 13 put positions were bought back early across SMCI, DELL, DDOG, ORCL, MSTR, META, ANET, MPC, COP, and PANW, generating a combined net P&L of $11,945.10 and releasing the associated collateral back to available cash.

Assignments and expirations: None this week — no shares were put to the account, and no options expired outright.

In total, the account executed 21 transactions this week between new puts sold and existing puts closed early.

Portfolio Snapshot

As of the current cumulative state of the account:

• Total portfolio value: $1,043,989.11

• Cash balance: $1,043,989.11

• Available cash: $364,489.11

• Open stock holdings: 0

• Open covered calls: 0

• Open cash-secured puts: 12

• Total premium collected since inception: $58,481.29

• Starting portfolio value: $1,000,000.00

Watch the live portfolio: https://cco.predictintel.io/paper/ Subscribe to run this yourself: https://cco.predictintel.io/signup

Past simulated performance does not guarantee future results. Options trading involves substantial risk of loss and is not appropriate for all investors. Consult a licensed financial advisor before making any investment decisions.