TradeTuning

A few weeks into testing a strategy on TradingView, I realized I'd been doing the exact same thing over and over: change one input, rerun the Strategy Tester, write down the result, change it again. For a strategy with even four or five tunable parameters, that's not dozens of runs. It's hundreds, and all done by hand. A serious waste of time.

TradingView's Strategy Tester is great at running one backtest. It has no built-in way to sweep a range of parameters and compare the results side by side. So that part was on me, every time.

The other thing that bugged me: even after all that manual work, the report itself doesn't tell you much. Profit, win rate, maybe a Sharpe ratio — and that's usually it. The numbers that actually predict whether a strategy is survivable, not just profitable on paper, aren't there. Reward:Risk ratio, Expectancy, Risk of Ruin, how much gain you'd need just to recover from a given drawdown. Most traders never calculate these at all, because doing it by hand for every single backtest run isn't realistic.

So I built TradeTuning to handle both problems:

— Automated parameter sweeps: define your ranges, let it cycle through every combination and log the results, instead of running each one by hand

— A "Deep Analysis" line on every result — Expectancy, Reward:Risk, Calmar Ratio, Recovery Factor, RoMaD, a Kelly-based suggested position size, and a Risk of Ruin estimate, computed automatically

— Multi-condition filtering (min trades, min win rate, max drawdown, and more) so a 500-run sweep is actually usable instead of just a wall of numbers

— Full result export as a self-contained interactive HTML report, so you can share or reopen a completed optimization later

— Works with TradingView's regular and Deep Backtesting modes, and on TradingView's international subdomains

The "Deep Analysis" metrics started as a handful of the basics and have grown from there as I dig into what actually predicts whether a strategy holds up out of sample, not just in the backtest. More are coming.

If you optimize strategies on TradingView: what do you actually look at when comparing two parameter sets with similar profit but different drawdowns? I'm curious whether people lean on a gut feeling here, or if there's a specific number you check first.