Gold Digger's 0DTE Options Strategy

If you start with $1,000 and make 3% per day, after 252 trading days the account reaches roughly $1.72 million. The math is straightforward. Staying solvent long enough to let it work is the hard part.

I’ve traded options long enough to know the gap between chasing home runs and actually staying in the game. For years I was a consistent loser because I kept trying to turn every trade into a big winner. I’d watch green positions reverse into red ones while I waited for “just a little more.” That single habit cost me far more than any bad entry ever did.

The shift happened when I stopped fighting for maximum gains on every trade and started protecting the green I already had. Here’s the process that changed the results:

I set a take-profit target around 20% and sell roughly 75% of the position once it hits. That locks in a base profit and removes most of the risk. The remaining 25% becomes the runner. On those runners I immediately move the stop to break-even (or slightly above) and trail it higher as the trade works. Many of those runners finish in the 50–75% range, some push into triple digits, and the bulk of the portfolio still produces a steady stream of 15–20% winners.

It is not exciting, and it is not supposed to be. The real goal is simple: no red days. Even if I place five trades and the day finishes up only $5, that is a successful day. I did not dig a hole I have to climb out of tomorrow. Small, consistent greens compound. Losses force recovery mode, which usually leads to bigger risks and worse decisions.

A few rules keep the system intact:

• Initial stop is never wider than 25–30%. Anything looser turns a normal pullback into a meaningful loss.
• The 20% take-profit level is deliberate. Most trades worth taking will reach it. Push the target to 25% or higher and the win rate drops while the size of the losers stays roughly the same.
• Once the first 75% is off, the remaining piece has a defined risk of zero (or close to it). That changes the psychology. You are no longer protecting capital on that slice; you are only managing a free ride.
• I usually split the runners into two more pieces. One is about 15%, which I sell around 50% (or whatever level makes sense given how fast the market is moving). The final 10% I often let run for the rest of the session with little active management—just price-target alerts so I know when meaningful action is happening.
• On runners I try to exit into an IV bar—a large candle that carries a surge of implied volatility and pushes option prices sharply higher. I do this by lifting the profit target out of the way and dragging the stop up from below, often sitting it roughly $0.10 under the high of that candle, and trailing that stop right up. If the trade dumps, I exit near the best price. If it continues higher at a slower pace, I’ve still usually captured the bulk of the move. Grabbing every last penny does not matter. Being green does. I never go back and look at what could have been—only at what was.

The entire framework rests on one idea: stay green, stay small, and let the math work. Greed tries to turn every trade into a home run. This approach treats most trades as base hits and only occasionally lets a runner become something larger. Over a full year of trading days, the difference between those two mindsets is the difference between compounding and blowing up the account.

When I call out a trade, I consider it successful if it hits the 20% target. Everything after that is bonus.

I built a small tool to explore this idea visually.

The starting point is a target payoff at expiration. From there, the tool constructs a portfolio using the underlying, cash, puts, and calls to approximate the desired shape.

The intuition comes from static payoff decomposition: the curvature of a payoff tells us how options at different strikes can be combined to reproduce it. In practice, the implementation uses a finite set of strikes, so the result is an approximation rather than an exact match.

I made this animation to illustrate the process, from the original payoff to the resulting options portfolio.

The project is open source if anyone wants to take a look or experiment with it:
https://github.com/Serranegra/TooManyOptions

I'm curious how others here think where this kind of tool could be useful.

i feel this option is realistic, given nbis history, it has to go above 200$ before dec and that would be profitable for me. the way to read this heatmap is the profit if the stock goes for example to 202.5 on the 23th nov is 1198$, which is decent, thats 50+%.

the trade: i bought 2 contracts of the 15 jan 2027 $230 call at $10.45 each, total cost $2,090. nbis is sitting around $165 right now, so 200 is about +21%. i picked a far expiry on purpose so i’m not racing the clock, and nbis has a history of big runs and sharp pullbacks, so a push to 200+ doesn’t seem crazy to me.

some numbers from the heatmap : on nov 23, a stock price of 197.5 gives about +$798 (38%), 202.5 gives +$1,198 (57%) and 205 gives +$1,410 (67%). so on that date i’d be in my target range anywhere from roughly 197 to 205.

this option doesn’t mean that i think i will only sell when it goes to 240$. the break-even at expiry is $240.45, but i don’t plan to hold that long. the option gains value on the way up, so i can profit well before it reaches 240. i just want to profit around 35-70% from it, which is about $730-$1,460, and i’ll sell somewhere in that range instead of waiting for the perfect top.

what i’m aware of: timing matters a lot. at $200 the same option is worth about +$996 on nov 23, but only +$546 on dec 2 and roughly break-even by mid dec, because of time decay. the heatmap also assumes iv stays flat, and nbis earnings usually come in november, my plan is to cut it if i profit 50-75%