I see a constant debate between weeklies and monthlies. So I ran the backtest delta matched on 84 US large caps from 2021–2026, selling 1-week vs 1-month calls at the same target delta, 0.10 through 0.40.

1. Below 0.25 delta, weeklies win. At 0.10 delta, weeklies beat monthlies risk adjusted (Sortino) on 73% of sample, +1.9 CAGR/yr median. At 0.20, still 66% of sample.
2. At 0.25 it's even.
3. Above 0.30, monthlies win. By 0.40 delta, weeklies win risk adjusted in only 36% of sample.

Why even at 0.25? A 0.10 delta weekly harvests about 2x the annualized premium of monthlies while being assigned just as rarely.

But at 0.40 weekly strike sits much closer to spot, every assignment gives back more of the trend, four times as often.

Methodology: premiums from bid/ask mids where available, otherwise full implied vol surfaces (BAW).

Everyone argues about whether cheap far-out options are dumb. Well...

If losers go to zero and you hold winners to target, the hit rate you need just to break even is set by the payoff:

That's to go flat. Not to make money.

Now the part that actually matters. Losers go to zero is a choice, obviously.... Cut them at −50% instead:

Cutting at half roughly halves the hit rate you need. That's a bigger edge than any amount of better picking, and it's free. The problem is a 3-cent contract doesn't feel worth managing, so it gets held to expiry, and your real break-even is the left column instead of the right one.

Then the spread. On a 0.45/0.55 quote you're down 20% at fill. On 0.01/0.02 you're down 50% before you've done anything — your stop got hit the moment you bought. That's why this stuff paper-trades great and trades terribly.

So: 10x needs 10% holding to zero, ~5% if you cut, back to ~7% after a normal spread, and sub-10-cent contracts are basically unplayable.

Lotto tickets aren't automatically losers. But nearly all the edge is in the exit, not the entry.

Anyone actually track their hit rate on sub-$1 contracts separately? I'd bet it's a lot worse than your overall win rate is hiding.

Ranked this morning's pre-market movers at 9:45 by relative volume and options volume instead of by % gain, dumped the list into TradingView, and let it run.

Here's where all 15 sat pre-market.

Same 15 names at 11:47 ET, sorted by performance:

The asymmetry is the whole story:

All five up-gaps still green. Of the ten down-gaps, four held and six either faded to flat or flipped green.

FRVO is the one to look at. Came in with the highest relative volume on the board at 5.41x, gapped +7%, now +24.7%. That's the whole argument for ranking on participation instead of gap size — it was 8th by percentage and first by volume.

INTC is the mirror image. Gapped −2.92% on 0.37x relative volume — below its own normal — and it's now −0.21%. A gap with nobody behind it.

Here's where my own thesis only half works.

Relative volume sorted the up-gaps cleanly — the two highest (FRVO 5.41x, CRK 2.83x) are the two best performers. It did nothing for the down-gaps. The six that faded had RVOLs of 1.15x, 0.46x, 0.37x, 0.35x, 0.41x, 0.45x. The four that held: 1.61x, 0.41x, 0.52x, 0.34x. No pattern at all. Low participation predicted a down-gap fading about as often as it didn't.

Caveats: one session, 15 names, and 11:47 isn't the close — some of these will look different at 4pm. And gap direction is confounded by whatever the broad tape did today; a market that rallies off the open flatters every down-gap fade.

Anyone tracked up-gap vs. down-gap hold rates over a real sample? One day tells me nothing, but the split was stark enough that I want to know if it holds.

I’ve been developing and backtesting a systematic Opening Range Breakout strategy on SPY and have gotten it to a point where I’d really appreciate some fresh eyes from people with experience in ORBs, systematic trading, or 0DTE options.

The strategy uses a defined opening range, breakout confirmation, time restrictions, range filtering and systematic exits. It trades both directions and is limited to one trade per session.

I’ve been developing it in TradeStation/EasyLanguage and optimizing the major components individually rather than throwing every variable into an optimizer at once.
I’m trying to judge the strategy on more than net profit — profit factor, expectancy, drawdown, trade count, long/short performance and parameter stability all matter.

The current underlying backtest covers SPY from 2020–2026: 576 trades, 54.2% profitable and a 1.56 profit factor. I attached the equity curve and performance report. The small dollar P&L is due to the test sizing — I’m evaluating the underlying edge and consistency rather than the nominal return.
My eventual goal is to execute this strategy through SPY 0DTE options, which is where things obviously become more complicated. An edge on SPY doesn’t automatically translate to an edge on the option because of strike selection, greeks, IV, spreads, decay, execution, etc.

I know historical intraday options data will eventually be necessary. I’ve looked into purchasing Cboe data ($2,200), but before making that investment I want to take the underlying research as far as reasonably possible and make sure I’m approaching the next stage correctly.

That’s really why I’m posting. I’d love to hear what experienced traders/system developers think when looking at these results. What would you investigate next? What concerns you? What am I potentially overlooking?

I’m not looking for anyone’s proprietary strategy or asking someone to build mine. Just looking for criticism, ideas, resources and another set of experienced eyes before taking the research further.
Happy to discuss more specifics where they’re relevant in the comments. Appreciate anyone that’s read this far and is willing to take a look!

If so, how far out do you usually go on the options
for expiration? How far out of the money do you like to buy puts?

How do you handle big moves up without getting your shares called away? Do you roll the calls?
And on big drops, how do you cash out the puts — sell them, roll them down, or use the gains to buy more stock?

I am mostly interested in indexes.

Curious how this has worked in real life.

Like many people, my ira is a snp500 index fund that I won’t touch for another 20years.
As I’ve learned about options, it seems like it would make sense to regularly sell a put spread from spot to 90% of spot in the account. This would allow me to harvest additional equity risk premium without exposing myself to the catastrophic risk of an uncapped put.
Is this a well understood strategy in the options world? Does anyone else do this?
I found OVL does this with some success, but has high fees. I’d probably automate this myself after some more DD.

390 Professional Order Rule

Just got an email about this new rule. I'm confused and struggling to find info online or on RH about it. It says you cannot exceed an average of 390 Option orders per trading day during a calender month.

Does this mean if I do 1 order of 10 contracts does that count as 1 or 10 towards 390.

Can someone explain this to me better than Google can. Thanks

Edit: I played around on robinhood and was able to talk to the AI assistant and figure out how it works.

Example- If I place an order to buy 20 options and then sell all 20 options in a single order. That will count as 2 orders for the day. If I were to sell those same 20 options as 4 orders of 5 then in total it would be 5 orders for the day.

Almost seems impossible to hit 390 orders a day, thanks for the answers

Hello,

I am trying to use double calendar spread on Webull however could not find it in the list of available strategies. Does anyone know how to trade double calendar on Webull? Also does Webull offer custom spread builder so one can choose legs manually to build double calendar?

I absolutely love the app and thinking about moving other accounts to Webull but this can be deal breaker. I have IKBR and TOS and they offers this option however I am not big fan of their mobile application. Anyone knows if Robinhood or Moomoo has custom spread builder?

Thanks in advance!

I'm a big fan of strangles, but when it comes to harvesting theta, I find it difficult not to have a directional bias.

For me, the ideal time to sell a CALL is after the underlying has already had a strong run, while for PUTs I prefer the opposite, selling them after a significant decline. I focus on reliable, relatively low-volatility stocks.

Lately, I've been testing a theta portfolio in my paper account using this approach:

• CALLs: stocks that have already run up significantly or are near a resistance zone
• PUTs: stocks that have sold off significantly or are near a support zone
• Delta: between 5 and 15
• DTE: 30–45
• Closing positions at around 20–50% profit
• Stopping out only when the underlying gets close to the strike

So my portfolio always has a mix of CALLs and PUTs, but on different stocks.

In a way, you could think of it as a short strangle across different underlyings, but with a directional bias based on mean reversion. I'm essentially betting that stocks that have moved significantly in one direction will eventually retrace, or at least that their movement will slow down.

This has been working very well in my paper account so far. Of course, I know the risks involved with naked options, including the possibility of multiple positions being stopped out at the same time. The idea is not to use leverage, but rather to manage the portfolio so that the overall exposure remains controlled.

I'm curious if anyone here is doing something similar.

Is there a specific name for this approach? If you've seen a Reddit discussion, article, or even a good YouTube video covering something along these lines, I'd really appreciate the link.

I'm mainly trying to understand the different ways this can play out and learn from people who have actually traded this type of approach.

Using a TLT call credit spread for income because I can’t refinance at these long rates.
I don’t need yields to rise. I need them not to fall ~100bp. TLT is $81.87. Duration is ~15, so 100bp lower on the long end is roughly TLT into the mid-90s. That’s about the move that would make a refi real for me. Until then I’m stuck with the mortgage, so I’m getting paid to wait.
Trade (from the Nov chain today)
• TLT $81.87
• Sell 20-Nov-26 85 call / buy 20-Nov-26 90 call
• 80 DTE
• Credit $0.50 ($50 per)
• Width $5
• Max profit $50
• Max loss $450
• BE $85.50
85 is ~+3.8% (~25bp). 90 is ~+10% (~65bp). Full 100bp / ~$94 is still outside the long strike. If rates never come down enough to refi, I keep the credit. If they drop hard enough that a refi is actually on the table, this can already be at max loss before TLT gets to $94.
I looked at 90/94 on the same expiry. Credit is only ~$0.08–0.09. Not worth it for “can’t refi so I want premium.” Nov IV on TLT is ~11–12%, so you don’t get paid for being that far OTM.
Defined risk only. Not short TLT, not naked calls.
Management
• Take it off around $0.25 (half the credit)
• Don’t hold the last week if it’s close
• Size off the $450 max loss
Questions:
1. Is pairing “can’t refi unless long rates drop a lot” with this 85/90 a reasonable way to get paid while I wait, or am I just selling cheap TLT vol and dressing it up as a mortgage story?
2. For the same idea, would you sell closer (83/88, more credit) or farther (88/94, less credit, closer to the 100bp line)?
3. Anything dumb about Nov vs pushing it to Dec?
Not advice. House first, options second. Want the structure kicked before I size it.

Continuation of yesterday's post — real numbers, no fluff, this is how the day actually played out.

Overnight, the warning from yesterday played out: one of the two walls had to give, and this time it was the put side. Pre-market saw real selling pressure testing the ES 7659 level.

By the open, the 0DTE put wall was only Fragile at 7625, with the call wall Moderate at 7705. Price dipped straight into the open but bounced off the range support inside the very first 15-minute candle and turned higher.

An hour in, the position was sitting on roughly $820 of profit — well clear of the 7659 level. With 12 contracts still open, I made the classic mistake: held for another $80 instead of taking the win. Greed, plain and simple, and I know better. The market dipped, the paper profit evaporated, and a resting order to lock in $640 didn't fill. Had to sit through the 7625 support actually getting tested and breached on a third dip before finally closing the main position, buying it back from 0.85 down to 0.15.

Added one more small position later for $80, bringing the total for the day to $779.

Lesson worth repeating: once you're at 70-80% of max profit on a spread, take it and walk away — especially on a volatile, high-volume day like this one. Riding a position from near-full credit into a real drawdown, then white-knuckling it back to almost-full credit, isn't a repeatable strategy. It's luck.

Looking at tomorrow: this makes three red days in a row. The real concern is what the close shows for the next session — the put wall has already slipped back to 7550, and there's no reliable support level on the chart between here and there. That's a real warning sign. On the upside, there's a resistance zone around SPX 7670 that I'm skeptical this tape breaks without a genuine catalyst.

Current lean: a put credit spread doesn't look attractive up here — if anything, only below 7550 on a real dip. A call credit spread up around 7710, respecting that 7670 resistance, looks like the more sensible side. All of that can change overnight, but you can't trade a guess. In hindsight, a lower entry below 7590 today would have priced in more credit — impatience cost me there.

Levels SPX Source: gammawalls.com

Zebra Technologies took its name from the black and white stripes of a barcode. It makes barcode scanners, rugged mobile computers, RFID readers, machine vision systems, and printers, the physical hardware layer underneath most modern inventory tracking, retail checkout, and warehouse logistics operations. If a package got scanned somewhere between a warehouse and your front door, there's a real chance Zebra hardware was involved.

Q2 2026 results were genuinely strong. Revenue grew 20.4% year over year to $1.56 billion, beating estimates by nearly 4%. Non-GAAP EPS of $6.35 crushed the $4.38 consensus by 45%. Gross margin expanded to 53% from 47.6% a year earlier, helped partly by IEEPA tariff recoveries and favorable currency effects. Management raised full-year 2026 non-GAAP EPS guidance to $20.75-21.25, up from an earlier range, and issued Q3 guidance above what analysts were expecting too. This followed an already strong Q1, where EPS of $4.75 beat estimates by 16% and sales grew 14.3%.

The demand drivers span retail and e-commerce, transportation and logistics, and healthcare, with management specifically framing the strategy around deploying AI on the frontline through connected devices and automation solutions. Recent product launches like the WS501-R wearable computer target frontline worker productivity directly. Transportation, logistics, and retail e-commerce have been consistent strengths, while manufacturing and parts of Europe, especially automotive-exposed markets, have lagged.

The stock is up 48.5% year to date following these results, and one fair value model built around 7.5% annual revenue growth through 2029 implies around 25% further upside from current levels, though that requires sustained execution on the growth trajectory. The honest risk with Zebra is real: tariff exposure and trade policy remain a genuine ongoing variable even with recent recoveries helping margins, the company is still working through integrating recent acquisitions like Elo and Photoneo, and reliance on hardware sales means this business stays more cyclical than a pure software company would be. Anyone track the industrial data capture and automation space?

Did you ever find what happens when you go and look at the option options chain or scanner, and select the strike to sell?

There is a lot going on and traders make discretionary decisions what strike to use.

I want to automate that part for making trading more consistent and hopefully more profitable

First attempt I went with a naive delta range. It was something like 24-38, then turned into a map for ranges, separated on calls and puts.

It’s still didn’t work well sorry so I added more maps to adjust for stock prices, and IV ranges.

That worked for a while, and then market settled in current mode, “flat” implied volatility where a lot of names get a narrow premium distribution across strikes. What happens is premiums get clustered around ATM strike.

Which means delta range has to extend to 45-48 on puts

I decided it’s time to build a model which going to look at greeks, expected move and determine delta range for strikes.

It tools a while to build something that determines ranges reliably across different securities, separately for calls and puts. I wanted closed richer puts and more distant calls.

This was one of the most fun project I did. I have a full test suite to validate results, but I haven’t quite figure out how to make test inputs automated since they have to come out of some other model or calibration data.

I’m also not using any historical data or backtesting, again same problem what’s the test inputs.

Still, it works with remarkable consistency. I run it today on a bunch of names, NBIS TLT COST CHWY just random liquid names and all strikes from delta ranges were well defined. I was looking and yup that’s where I’d look to sell premium.

Has anybody build anything similar? As a model, math formula basically, rather than set of rules.

Anybody interested to compare results, even empirically for discretionary selection? Let me know the names, I can reply with results (when market opened)

Upd this is how it works

Pretty good selection across vastly different securities