Twenty-two trading days ago, I began an experiment.

The goal: Generate consistent daily cash flow by selling short-duration SPY credit spreads while using gamma exposure to help determine where I wanted to position my risk.

The initial target was straightforward:

$500–$1,000 per trading day.

After 22 trading days, here are the actual results:

Net Realized Profit: $12,959.53
Average Daily Profit: $589.07
Winning Days: 21
Losing Days: 1
Observed Winning-Day Rate: 95.45%
Gross Winning P&L: $15,359.53
Gross Losses: ~$2,400
Profit Factor: ~6.40

These are realized results—not hypothetical trades or backtests.

That said, 22 trading days is a very small sample, and I don't expect a 95% win rate to persist indefinitely. The purpose of this project is to build a much larger dataset and find out what actually holds up over time.

I share my live trades, automated smart money alerts, and a community discord in the button below!

The strategy itself is fairly simple.

I'm selling same-day SPY credit spreads—primarily bull puts and bear calls.

But instead of selecting strikes purely based on delta or premium, I'm paying close attention to the market's evolving gamma exposure (GEX).

I'm looking for areas where significant options positioning may influence price behavior and then trying to position my short strike safely beyond those areas.

In simplified form:

Market structure → Gamma → Strike selection → Sell premium → Let time work.

I'm not trying to predict exactly where SPY will close.

I'm trying to identify areas where I believe SPY is unlikely to finish and sell premium there.

Large opening gaps have been particularly interesting.

When SPY makes an unusually large move without a corresponding fundamental catalyst, implied volatility can become elevated.

If gamma structure also suggests resistance or support beyond the move, I've sometimes been able to sell premium outside that structure and benefit from:

Mean reversion + IV contraction + theta decay.

Several of the fastest winners in the experiment have occurred this way.

But this approach isn't foolproof.

Day 12 gave us our first—and so far only—losing day.

I sold bear calls expecting overhead gamma to help contain the market.

It didn't.

SPY continued relentlessly higher and eventually finished the session up more than 1.75%.

Loss: approximately $2,400.

This was arguably the most important trade of the experiment.

It demonstrated the primary danger of the strategy:

That's something I'm now studying very closely.

The goal isn't to eliminate losing trades. That's impossible.

The goal is to recognize environments where the probability of a runaway directional move is elevated and either reduce exposure, exit earlier, or avoid the setup entirely.

This may be my favorite statistic from the experiment.

I didn't increase position size to recover the money.

I didn't change strategies.

I simply continued taking qualifying setups.

The following 10 trading days were all profitable, generating:

+$6,506.56

That brought cumulative net realized profit to:

After 22 trading days, my biggest takeaway is that gamma isn't necessarily a crystal ball for predicting SPY.

I think its value may be much simpler:

Gamma can help identify where I DON'T want to sell options.

Combine that information with price action, implied volatility, opening gaps, theta decay and disciplined risk management, and it can become a useful tool for structuring credit spreads.

We're still early.

Twenty-two days doesn't prove an edge, and a high win rate can hide substantial tail risk in a short-premium strategy.

That's precisely why I'm documenting everything.

I want to continue this experiment through at least 100 documented trading days.

As the dataset grows, I'll be studying:

If the strategy continues performing as the sample grows, we'll have something considerably more interesting than a profitable month.

We'll have a documented trading framework that has been tested across different market environments.

22 days down. 78 to go.

Educational purposes only. Options involve substantial risk and are not appropriate for every investor. These results reflect my own trading experience and are not a guarantee of future performance.