Exits Matter More Than Entries. Here's My Four-Path Exit System.

Everyone obsesses over entries. Which indicator. Which model. Which signal threshold. Entries get you into a trade. Exits determine what you keep. I spent more engineering time on my exit system than my entry model. Here’s why — and how it’s structured. Why Exits Are Harder An entry is a single decision: does this bar look like a long or a short? An exit is an ongoing negotiation between multiple objectives: ...

March 14, 2026 Â· 3 min

Day 3: The System Fixed Itself (After We Fixed the System)

Day 3. Equity went from $701 to $928. Not because the market was kind. Because the data was finally clean. One line of code. Running for two days. Something felt off on day one. I was holding long positions, the market was moving up, but my equity was bleeding faster than it should. I couldn’t find the cause. On day three, I pulled the logs. Found a keyword repeating every 15 minutes: ...

March 13, 2026 Â· 3 min

My Trailing Stop Was Running. It Just Never Fired.

Today I ran a full cross-audit of the V5 quant system. Scope: training, backtest, and live execution — 13 files, 6,500 lines. I was looking for drift. I found something worse. The Trailing Stop Was Updating. It Was Never Checking. My backtest engine has four exit paths: Fixed stop-loss Fixed take-profit Trailing stop Momentum fade SL and TP are delegated to the exchange. The trailing stop has to be managed by the script itself. ...

March 13, 2026 Â· 2 min

Backtest Design Is 60% of the Result. Model Training Is 40%.

Most people obsess over model accuracy. Win rate. Precision. Feature importance. That’s 40% of the problem. The other 60% is how you build the backtest that validates it. What the Backtest Actually Controls A model tells you: this bar looks like a long. The backtest decides everything else: How big is the position? Where does the stop go? How does the stop trail? When do you decide the signal is gone? Do you re-enter after an exit? How do you handle overnight funding? Every one of those decisions compounds over hundreds of trades. ...

March 13, 2026 Â· 3 min

My Quant Model Had 5 Silent Data Bugs. The Backtest Looked Great.

My V4 trading system used 11 data sources: price data, funding rates, open interest, institutional long/short ratio, liquidation data, fear & greed index, CVD, and more. The backtest results looked solid. Win rates above 80%. Drawdown under 15%. Then I audited the code line by line. What I found made me rebuild the entire system from scratch. Bug 1: The Fear & Greed index was always 50 The Alternative.me API returns data in this format: ...

March 13, 2026 Â· 4 min