Just watched the account tick over 3 mil this morning. Up 147% YTD (about $1.7M net this year). Btw, this $3M was the exact target I set for myself when I started. Now that I hit it, I’m officially retiring and done staring at charts all day.

I know people will see the Robinhood UI and the PnL and assume I just yolo'd 0DTEs on tech or caught a meme stock pump. Honestly, the reality is boring as hell. It’s just math.

When I started, I wanted 100% baggers. It’s a massive trap. Opportunity cost eats you alive while you wait. You know what’s way easier than catching a 100% move? Catching a 10% move. If you compound eight 10% wins, that’s 114%. My entire PnL this year is just stacking small, unsexy swing trades.

My only real rule: if the setup isn't a 3:1 r/R minimum, I sit on my hands. If I'm aiming for a 15% move, the stop is a hard 5%. If you run those numbers, you can literally be wrong 60% of the time and still be green. Those little red dips on my chart? That's just me taking the 5% L and moving on to the next one.

I average maybe 9 or 10 swings a month. Chart on TV, execute on RH. Strictly SMC/ICT concepts. I stay out of the chop, wait for retail liquidity to get swept, wait for a market structure shift, and then bid the retest on an FVG or order block. Patient entries mean tighter stops. Tighter stops mean that 3:1 is effortless.

It really just comes down to risk management and letting probability play out over a large sample size.

Hope you guys make it out of the trenches. Good luck out there.

Here's some of the reasons why I've made a bunch of CSPs in the month of April. It's been overall really good, mostly all expiring!

ASTS

• This is the speculative position (that everyone on reddit seems to be loving lol) and only treated as a wheel stock in the portfolio. The thesis is this: if they pull off direct-to-device satellite connectivity at scale, the addressable market is seems to be enormous
• The partnerships with AT&T and Verizon are validating signals. Plus, the FCC granted its application to modify its authorization to launch and operate its SpaceMobile satellite system in low Earth orbit
• Volatility is high which means premiums are elevated. That big drop from AMZN's partnership this past week is exactly why I executed the trade rather than just hold outright. Looks like it's going to expire no problem with the positive news

META

• The core ads business is as strong as it's ever been
• Three billion daily active users across the family of apps is a number that doesn't have a real competitor
• The free cash flow from the core business makes the valuation look reasonable. The glasses, AI assistants, and WhatsApp monetization are all optionality on top of an already great business
• Huge premiums (especially if you can roll), strong fundamentals, and always will be glad holding ore of it at whatever price. I see it going to $1000

TQQQ

• This is a leveraged ETF, not a business, and the approach has to reflect that. You're not investing in QQQ... you're using it as a premium generation vehicle
• The decay mechanics mean you never want to hold this long-term without actively managing it. But selling cash-secured puts at conservative strikes in a range or trending-up market can generate serious income. My first time doing it, as I was recommended it by the platform
• Strike selection is everything here. You want enough OTM buffer to absorb a bad week in the Nasdaq without getting assigned on a decaying instrument

NFLX

• The bear case on Netflix has been wrong every single time. They've navigated password sharing, added an ad tier, and are now one of the most profitable streaming businesses in existence
• Live events seem to allow users to stay instead of binge & cancel
• The content flywheel is literally insane, a driven content decisions at scale is a structural advantage traditional studios genuinely cannot replicate. I don't mind it exercising.
• The short-term drop of Reed Hastings leaving just seems like noise to me, that's why I went with some OTM trades, i'll be holding LT regardless.

MSFT

• Azure, Office, LinkedIn, and GitHub... all are beasts. I like high quality businesses is all
• Not believing in the SaaS-pocalypse, they're still going to be dominant in the future
• Lower premiums relative to the others but the risk profile is as clean as it gets. You're collecting premium on a business that will almost certainly be worth more in five years

I wanna hear what y'all are wheeling and doing in today's markets!

April is looking pretty good so far, I have the following positions that I’m looking to close out with approx $49K in premiums.

TL;DR: I've been running the wheel for about 20 years and doing ML for about 20 years. Finally built the project I'd been putting off — a model that scores individual CSPs and covered calls for "will this hit 50% profit before expiry?" across 28 tickers, from SPY/QQQ/AAPL through the volatile stuff most of us actually wheel now (COIN, MSTR, HOOD, OKLO, PLTR, MARA, RIOT, SOFI). Trained on 461K trades, 2020-2026. The punchline: on SPY/QQQ the standard wheel rules (30-delta, close at 50%, roll at 21 DTE) are hard to beat. On the volatile names, the rules you inherited from SPY-land actively hurt you, and the model learned why. Sharing because strike selection is where most wheel operators (myself included) under-think, and this experiment made me change how I size and select.

Repo (MIT, nothing for sale): https://github.com/caradhras36/options-ml-scoring

Not a product. Not a service. No Discord, no newsletter, no course. Posting because the wheel community is where I've learned the most over the years and this is me putting something back.

Why this matters for wheel operators specifically

The wheel works. "Sell 30-delta CSP, close at 50%, if assigned sell 30-delta covered call, close at 50%, repeat" is a disciplined playbook that beats most of what retail does.

But the moment you extend the wheel past SPY/QQQ into volatile single names — which is where most of the premium is, and also where most of us have gotten blown up — the heuristics stop behaving the same way. A 30-delta on SPY and a 30-delta on COIN are not the same trade, and every experienced wheel operator knows this intuitively. The question I wanted to answer with this project: can a model formalize that intuition, and does doing so actually help?

Short answer: yes, but less than the headline backtest numbers suggest, and mostly by forcing discipline that an honest wheel operator would already apply.

Setup

For every CSP or covered call meeting:

• 21-60 DTE
• |Delta| 0.10-0.40 (normal wheel band)
• Mid > $0.05

…score whether it will hit 50% of max profit before expiry. Five models on the same ~30 features:

1. hit_50pct — binary (primary)
2. max_profit — how much you realistically clear
3. days_to_50 — how fast it cooks
4. expected_value — dollar EV
5. outcome_category — full win / partial win / breakeven / loss

Data from Polygon EOD chains, 28 tickers, Jan 2020 - Mar 2026. Greeks computed via Black-Scholes and cross-checked against OptionsDX to 0.4% delta error.

The question I care about most for wheel operators: given a ticker and a chain, which strike should I actually sell this week?

What the model learned (wheel-specific takeaways)

Three findings that changed how I wheel:

1. Ticker-specific delta bands

If you apply "sell 30-delta CSP" uniformly across 28 tickers, the hit-rate distribution looks like this:

Ticker	50%-profit hit rate at ~30-delta CSP
SPY	89%
QQQ	87%
AAPL	84%
NVDA	80%
PLTR	74%
COIN	71%
OKLO	68%
MSTR	67%

The SPY rule is a SPY rule. On OKLO/MSTR/COIN, 30-delta is meaningfully more likely to go against you than the community heuristic implies. The model learned to shade lower delta (15-25) on the volatile names and hold normal 25-35 on the mega-caps. My manual rule now: on any name with ATM IV > 50%, shift the target delta band down by ~10 points. This by itself — no ML required — probably captures a meaningful chunk of what the model found.

2. rv_iv_ratio is the feature I wish I'd tracked for 20 years

The single most useful engineered feature in the model is rv_20d / iv_atm — 20-day realized volatility divided by ATM implied. When it's low, you're selling rich premium relative to what the underlying is actually doing. When it's high, you're selling cheap premium into a stock that's been moving.

Every wheel operator does a version of this in their head ("IV looks juicy") but I'd never actually normalized it ticker-by-ticker. The model treats rv/iv on SPY and rv/iv on COIN as the same signal, which is exactly what you want — it's a relative richness signal.

Practical wheel rule: if rv_iv_ratio > 1.2 (realized exceeding implied), skip the open. Wait for IV to catch up or for realized to cool. Not a model requirement — a rule you can apply from any options data source.

3. The 50%-profit label is actually the right wheel target

I was nervous the "hit 50% profit before expiry" label would be weird for wheelers who hold through assignment. Turns out it maps well. For CSPs that end up assigned, the 50%-profit label is rarely hit (the position gets assigned at a loss or at close-to-max — that's what assignment is). The model learned to score low-probability-of-50% trades as "avoid" even when premium looked attractive, which is basically the wheel operator's "do I want to own this at this strike" gut check, formalized.

The model is not a replacement for "pick tickers you're willing to own." It's a filter on top of that.

Results — and the part where I beg you to discount the dollar number

Holdout backtest: Jan 2025 - Mar 2026 (15 months the model never saw):

Metric	Model (threshold 0.85)	"Sell everything in the band" baseline
Trades	193,608	285,379
Hit rate	99.7%	78.2%
Avg P&L / trade	$404	$95
Precision lift	+11pp	—

Five reasons the +$400/trade is fiction-adjacent:

1. Mid-price fills. Every backtest trade fills at the bid-ask midpoint. In a real wheel account selling on names like MSTR or COIN, you're giving up 10-15% of the credit to spread. That alone knocks $30-60 off the average per-trade figure.
2. No capital / margin / concentration constraints. 193K trades over 15 months is ~500/day. No wheel account has that capital. The realistic question is "among the N trades I can actually put on today, does the model's top-N beat the heuristic's top-N?" — and I haven't answered that yet.
3. annualized_return is the model's top feature. SHAP analysis shows the single most important input is premium-per-day-per-capital. That's technically known at trade entry so it's not strict leakage, but it means a meaningful chunk of the model's "edge" is just "avoid thin-premium trades" — which is a rule you can write on a napkin. I'm retraining without it to see what survives.
4. 15 profitable months = a favorable regime. The backtest window was mostly benign for premium sellers. I have no data on what this does in a 2008-style crisis or a 2001-style low-vol grind where premiums compress.
5. No assignment/wheel path modeled. The label is hit-50% or not. It doesn't follow the CSP-into-assignment-into-covered-call cycle that actually defines the wheel. A version that does is on the roadmap but isn't built yet.

What actually changed in my own wheel

Because the only thing that matters for wheel operators is "did this make your own book better," and here's the honest account:

• I stopped selling CSPs at the same delta on COIN/MSTR/OKLO that I sell on SPY. This was the biggest behavioral change, and it doesn't actually require the model — the finding is "volatile names need lower delta," and once you know that, you can apply it manually.
• I added rv_iv_ratio as a manual gut check before opening any position. No model required — just a 20-day realized vol calc.
• I do not use the model as a go/no-go signal. I use it as a confirmation check. Model agrees with my intuition + delta + rv/iv → I size up. Model disagrees with my intuition → I shrink size or skip. Never the only input.
• I'm more skeptical of high-premium CSPs on volatile names, not less. The SHAP analysis caught several cases where the model was rewarding high-premium trades that were actually bad (high notional ≠ good trade), and that made me audit my own real-money history. I found two OKLO trades from 2025 that fit the "bad trade that looked good because premium was fat" pattern. Costly lesson, but it's the kind of lesson a model-output review can surface.

The deeper insight — and the one I'd push you to steal regardless of whether you ever touch the model — is that most of the time, the wheel rules are right, and the wheel rules are wrong in a specific, identifiable direction on volatile tickers. The rules were designed on SPY. If you're wheeling anything with ATM IV above 50%, derate your delta band.

If you want to use this on your own watchlist

Repo has a Jupyter notebook (notebooks/example_inference.ipynb) that walks through scoring a single trade end-to-end — I used an NVDA $130 PUT as the example. You feed it a ticker + chain snapshot, it returns all 5 predictions plus a SHAP breakdown showing which features pushed the score up and down for that specific trade.

That's the fastest path for a wheel operator who wants to actually use this — not to retrain, just to score your own watchlist each week. Everything is MIT-licensed. The 28-ticker pre-trained model is in the repo via Git LFS.

https://github.com/caradhras36/options-ml-scoring

What I'd actually want feedback on

1. Is 50% profit the right label for wheel operators? "Close at 50% OR 21 DTE" is more realistic for most of us. I'll probably relabel in v8. Anyone tried both?
2. Does rv_iv_ratio > 1.2 = skip match your experience? I think it's generalizable but I've only tested it on these 28 tickers.
3. For wheel-specific backtesting, should I model the full CSP→assignment→CC cycle as the label, instead of per-trade hit-50%? That's a bigger project but probably the right one.
4. What's your honest per-ticker delta band on volatile names? I moved to 15-25 on COIN/MSTR/OKLO, 25-35 on SPY/QQQ. Curious what other experienced wheel operators do.

I'll be in the thread for the next few hours. Brutal feedback welcome — especially on the mid-price backtest and the annualized_return leakage concern, which are the two things I'm least confident about.

I will post a separate comment with a link to the detail behind each option sold this week.

After week 16, the average premium per week is $888 with an annual projection of $46,184.

All things considered, the portfolio is down $10,275 (-2.27%), on the year. Additionally, the trailing 1-year performance is up $140,715 (+46.61%). This is the overall profit and loss and includes options and all other account activity.

All options sold are backed by cash, shares, or LEAPS. I do not sell on margin, nor do I sell naked options.

All options and profits stay in the account with few exceptions. This is not my full time job, although I wish it was. I still grind on a 9-5.

I contributed $600 for the 15th week in a row.

The portfolio is comprised of 98 unique tickers, unchanged from 98 last week. These 98 tickers have a value of $381k. I also have 180 open option positions, down from 183 last week. The options have a total value of $62k. The total of the shares and options is $443k. The next goal on the "Road to" is Half a Million.

I'm currently utilizing $42,750 in cash secured put collateral, down from $42,850 last week.

2025 through 2028 LEAPS
In addition to the CSPs and covered calls, I purchase LEAPS. These act as collateral to sell covered calls against. You may have heard of poor man's covered calls (PMCC).

See r/ExpiredOptions for a detailed spreadsheet update on all LEAPS positions including P/L for each individual position.

LEAPS note 1: the 2025 LEAPS expired 1/17/25. They were up $36,440 overall with a 233.74% increase. The major drivers were AMZN and CRWD.

LEAPS note 2: After holding for 2 years, I exercised an AMZN $80 strike from 2023 up +$11,395 (+463.21%) and CRWD $95 strike from 2023, up +$21,830 (+663.53%)

LEAPS note 3: Purchased 1/16/26 CRWD LEAPS for $8,230.03 on 1/17/24. I sold this LEAPS on 6/5/25 for $21,659 for a realized profit of $13,428.97 (+163.18%)

Total premium by year:
• 2023 $23,132 in premium
• 2024 $47,640 in premium
• 2025 $68,319 in premium
• 2026 $13,929 YTD

Premium by month (2026):
• January $3,334
• February $3,625
• March $3,706
• April $3,423

Annual results:

• 2023 up $65,403 (+41.31%)
• 2024 up $64,610 (+29.71%)
• 2025 up $111,496 (+34.52%)
• 2026 down $10,275 (-2.27%YTD)

I am over $154k in total options premium, since 2021. I average roughly $34 per option sold. I have sold over 4k options. I have been able to increase the premiums on an annual basis and I will attempt to keep this upward trend going forward.

Strategy:
The underlying strategy is buy and hold. I also use simple 1-legged options to supplement that strategy. Options have somewhat of a learning curve, but I believe that most people can supplement their investments using simple options with careful risk management.

I sell options on a weekly basis. I prefer cash secured puts and covered calls. Sometimes I'm ahead of the indexes and sometimes I'm behind. My goal is consistency in option premium revenue. I am building an income stream that will continue long into retirement.

Spreadsheets:
Unfortunately, I no longer provide spreadsheets. I received too many follow ups about formatting, pivot tables, compatibility etc. I think tracking is very important, but I post to discuss investing and options, not to provide tech support for Excel. I do appreciate the interest in my tracking methods.

Software:
I captured the screen shots from a proprietary software platform I built to track, analyze, and manage my options strategies.

Commissions:
I use Robinhood as a broker and they do not charge commissions. There is a an industry standard regulation fee of about $0.03 per contract. Last year I sold just over 1,400 contracts which is just over $40.00 in fees paid in 2024. In 2025, the contract fee is $0.04, which would push the fees up to around $60 based on current projections. The fee has been lowered to .02 per option contract.

The premiums have increased significantly as my experience has expanded over the last three years.

Make sure to post your wins. I look forward to reading about them!

Price is $86.76, and will hopefully be above $87 for Monday open.

Hey guys,

Just finished my first full month of wheeling, which has just been CSPs up to this point. I learned some lessons early on but feel like I've got a good hang on what's going on.

I built out my model and have gotten some really good use out of it thus far. I am a fairly conservative guy, and my results certainly speak to that.

My framework is as follows:

1. DTE Window - Target 20-40 days to expiration.

2. Delta Target - 0.20 to 0.30.

3. Minimum Return Thresholds: Minimum Trade ROC: 2.0% / Minimum Annualized ROC: 25%

4. Underlying Quality: Must be a well-established company; No penny stocks; Elevated IV is acceptable only if the underlying is still worthy of ownership.

5. BTC at 50% profit opened immediately for each new CSP, set GTC.

What I've learned thus far...

1. Trade ROC doesn't matter quite as much if your capital velocity is high; though that involves a degree of luck that you cannot rely on.

2. Don't get antsy and buy out early just because you get nervous... I did that with DOCU and missed out big time. Either way, if you don't feel comfortable being assigned at your cost basis then you shouldn't have executed the trade.

3. The urge to "tinker" is so difficult. I am very ADHD and work in finance, so I get very into models and squeezing out efficiency where I can. This kind of method doesn't work well if you over-engineer everything; just keep it simple and let theta decay and a strong opening position do the rest.

Conclusion:

I can't wait to see how this goes for the foreseeable future and to continue growing my account. I built out a whole policy framework for my trading to keep myself in line and not get out over my skis with "interesting" or highly volatile stocks - I am happy to share that document with anyone else that also wants a conservative strategy like mine. Also, haven't had to CC - as I haven't been assigned yet - so I may have some lessons learned in next month's update with HIMS and SOFI, given my current position with those.

MSTX — sold 3 covered calls at the $35 strike same-day expiry, collected $180 clean. MSTX closed around $33

MARA — this one didn’t cooperate. Opened the week with a $11C position, rolled it twice trying to find the right strike as MARA ripped from the $8s all the way to $11.11 by Thursday. The stock moved too fast in the wrong direction for a CC. Closed everything out for a -$92 net loss — a scratch. Sometimes the right move is cutting it clean and moving on rather than chasing.

Net: $88 credit — 0.78% ROI

Week 17 , TSLL, RCAT, APLD, ONDS, and SOFI expiring Apr 24.

* So i looked back at MSTX, that cost seemed high to me from last week, the 37$ is the original, but I have walked it down to 32$.

The program keeps your original cost, it does not adjust for the premium

Not sure if I will changed it or keep it like it is.

Maybe add it somehow.

Made some mistakes rushing with MARA, spent 21 hours on a plane Monday coming back from Vacation, should not have opened it.