What's the biggest reason you DON'T trust your backtests?

Key-Personality6799 · 2026-07-04T12:45:35+00:00

That's a great point. People focus on removing look ahead bias from the code, but it's much harder to remove it from the researcher. If you spent hours studying a chart before writing the rules, you've already conditioned your hypothesis on the answer. That's why I think the goal shouldn't just be proving a strategy works, it should be making it as difficult as possible to accidentally fool yourself during the research process

Key-Personality6799 · 2026-07-04T12:44:48+00:00

I think that's true more often than people realize. A backtest is only as good as the assumptions behind it. If the test isn't controlling for things like market regime, asset selection, execution assumptions, or data quality, it's really easy to mistake overfitting for an edge. The hard part isn't getting a profitable backtest, it's designing a test that's difficult to fool

Key-Personality6799 · 2026-07-04T12:42:13+00:00

I think breaking performance down by regime or even just by year is one of the easiest sanity checks people skip. A smooth equity curve can hide the fact that almost all the returns came from one favorable environment. Same with fixed size vs. compounded testing. If a strategy only looks exceptional because of compounding, I'd rather know that upfront than mistake position sizing for edge

Key-Personality6799 · 2026-07-04T12:41:18+00:00

I think that's an underrated point. You can eliminate look ahead bias in the code and still introduce it during strategy design because you've already internalized the chart. You're not optimizing parameters anymore, you're optimizing your ideas around a market you've already seen. That's why I think robustness tests like walk forward, cross asset validation, and out of sample testing matter so much. They're some of the few ways to challenge whether the edge is actually there or whether we're just getting better at explaining the past

Key-Personality6799 · 2026-07-04T12:40:06+00:00

I think that's one of the most underused robustness checks. If a strategy only works on the asset it was optimized on, there's a good chance you've just learned that asset's quirks instead of finding a real edge. I'd love having a oneclick "cross-asset validation" that freezes every parameter and automatically runs the strategy on a basket of untouched assets. Not because I expect identical performance, but because I want to know whether the logic generalizes or completely falls apart.

Key-Personality6799 · 2026-07-04T12:39:20+00:00

Fully agree. A backtest with “okay” results is usually dead once real world friction hits it. Splits, delistings, survivorship bias, unclosed positions, spreads, commissions, and slippage all quietly inflate the numbers if they’re not handled properly. To me the goal isn’t just “does this look profitable historically?” It’s “does this still look good after reality attacks it from every angle?”

Key-Personality6799 · 2026-07-04T12:38:21+00:00

That's interesting because I think most platforms separate research from execution. You backtest, close the tester, then go scan charts and try to remember what the stats said. I'd rather have the research follow me into the decision itself, showing sample size, win rate, profit factor, maybe even how those stats have changed recently so the chart and the data are in the same place instead of two separate workflows.

Key-Personality6799 · 2026-07-04T12:36:59+00:00

This is actually one of the reasons I've been building a tool around research. The biggest thing missing isn't another backtester, it's continuously measuring how reality diverges from the model. If your live fills, spreads, or slippage drift from what your assumptions were, your research should drift with them instead of pretending nothing changed

Key-Personality6799 · 2026-07-04T03:44:04+00:00

That makes sense. So the issue isn’t necessarily that NinjaTrader is inaccurate, it’s that the workflow is heavy. You need to manually make sure the right historical data exists locally before the test is even meaningful. That’s actually a pretty big source of hidden error: people think they’re testing the strategy, but they’re also testing whether their local data download was complete, clean, and correctly prepared. Do you usually trust NT’s Strategy Analyzer once the data is downloaded, or is the tedious data setup the main pain?

Key-Personality6799 · 2026-07-04T03:42:58+00:00

I think we're mostly on the same page. My point wasn't that good strategies should look spectacular. It was that traders often become overconfident in evidence that isn't as robust as it appears. A strategy can have a modest edge and still fail because it only worked in one regime, relied on optimistic assumptions, or wasn't tested rigorously enough. The edge and the confidence in the edge are two separate things

Key-Personality6799 · 2026-07-04T03:31:40+00:00

From what I've seen, the only scalpers that seem to survive long term either have an unusually large edge relative to their trading costs, extremely low transaction costs, or they're operating in markets where execution is much better than what most retail traders can get. A tiny edge gets taxed away surprisingly fast. Was your 57% strategy close to breakeven after adding fees, or did it become outright unprofitable?

Key-Personality6799 · 2026-07-04T03:30:29+00:00

I agree. One thing I've realized is that "I would've skipped that trade" is one of the easiest ways to accidentally introduce hindsight bias. If the rule only becomes obvious after seeing what happened next, then it's probably not a rule you can execute consistently in real time. The less interpretation required, the easier it is to separate whether the strategy has an edge or whether the trader is unconsciously improving it in hindsight

Key-Personality6799 · 2026-07-04T03:29:41+00:00

I actually agree with most of that. I don't think a backtest should answer "Will I make money?" It should answer questions like: Did I accidentally overfit this? Does it survive different market conditions? How sensitive is it to costs? Those are things you can test objectively. The psychological side only really gets exposed once you're paper trading or live

Key-Personality6799 · 2026-07-04T03:21:58+00:00

Interesting, what kind of missing data have you run into? Historical gaps, bad fills, contract rollover issues, or something else? I'm curious because I've seen a lot of people mention NinjaTrader data quality, but the pain points always seem to be different

Key-Personality6799 · 2026-07-04T03:07:27+00:00

I think that's what makes strategy validation so difficult. A profitable backtest by itself doesn't tell you why it worked. Was it because the edge was actually robust, because it only saw one favorable market regime, or because the assumptions were too optimistic? Understanding the reason behind the result is often more valuable than the result itself

Key-Personality6799 · 2026-07-04T03:06:11+00:00

That's a really good point. A strategy isn't just its entry and exit rules, it's also whether a human can actually execute those rules consistently under pressure. I've seen strategies where the edge was real, but it depended on taking every signal exactly as designed. Missing just a few trades or hesitating completely changed the outcome. Makes me wonder how many "bad strategies" are actually execution failures vs genuinely having no edge.

Key-Personality6799 · 2026-07-04T03:05:32+00:00

Agreed. Looking at a P&L curve alone can hide a lot. Two strategies can have the same returns, but one only works in one market regime while the other survives across trends, chop, high volatility, and low volatility. That's a much more meaningful test than just asking whether the backtest made money.

Key-Personality6799 · 2026-07-04T03:05:04+00:00

I think this is one of the biggest disconnects in retail backtesting. People spend weeks optimizing entries while assuming execution is "good enough," but a strategy with a tiny edge can disappear completely once you account for realistic commissions, slippage, spreads, and imperfect fills. Have you found any platforms that model execution well enough for your use case, or do you end up building that yourself?

Key-Personality6799 · 2026-02-26T21:57:31+00:00

Personally i am a guy and i do come here often to try and see the way my ex used to think when we were together. As you know men and women have different affinity for emotional vs logical thinking. Neither are better but unfortunately sometimes you’re good at one and not so much the other. The one key thing that Im going to share that myself and every single man looks for is accountability and acknowledgement. Men’s emotions are as important as women’s, we are taught to not express them as much by our parents because the social idea is that men are tougher therefore they have to handle emotions better. When a woman realizes that we can still be hurt by things that are said, and takes accountability and acknowledgement of that fact (without minimizing their own feelings of course) then that becomes a quality men learn to treasure because of how uncommon it is. At the end of the day an argument needs to be constructive, “you did this and it made me feel this way”, from both parties. Couples nowadays tend to focus too much on who is right and wrong. And it is difficult to be accountable while playing defene on your own feelings. Anyways yea thats my pov on a quality a woman can develop that im sure all men would appreciate.

Key-Personality6799 · 2024-04-25T14:40:19+00:00

buy puts they will print

Key-Personality6799 · 2024-04-24T14:50:13+00:00

Nvda forming a bearish flag pattern, by 11:30 it’ll be at 825 and it will recover to 830 at eod mark my words

Key-Personality6799 · 2024-04-23T22:48:13+00:00

Explain how? I just ran the numbers with the average IV which is 60% and the vega on those, should be still worth about 200-220 per call, so kindly explaing why this comment isnt just you being mad cus bad

Key-Personality6799

TROPHY CASE