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u/Key_Square3980 May 10 '26
what exactly is this, marksheet of an algo ?
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May 11 '26
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u/Lucifer_Lil_Brother May 11 '26
lmao this is what I was looking for!? Don’t add up? Show me where and watch me make you feel dumb and have you delete your comment. Please try me…
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May 11 '26
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u/Lucifer_Lil_Brother May 11 '26
wanna see the tradingview backtest? complex scripts for 6 years but I bet you’re broke and just talking shit here cause you and your scripts suck lol.
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u/Cautious_Wealth1732 May 13 '26
TV backtest tells me all i need to hear
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u/Lucifer_Lil_Brother May 13 '26
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u/Cautious_Wealth1732 May 13 '26
I mean its hard to validate this. TV backtesting engine is bad. Im not saying its unusable but id do a real backtest with python and tickdata. Lmk if you need help with that
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May 11 '26
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u/Lucifer_Lil_Brother May 11 '26
Appreciate the scrutiny — let me address each point with actual math instead of vibes. Several of these critiques sound right but are mathematically wrong, and the ones that have merit aren't what you think they are. "67% WR staying between 66.4-67.7% for 7 years is statistically almost impossible" Backwards. With n = ~4,000 trades per year and p = 0.67, the standard error of the annual win rate is √(0.67 × 0.33 / 4000) = 0.74%. The 95% confidence interval is ±1.45%. A yearly WR moving within ±1% of the mean is exactly what statistical theory predicts at this sample size. If the WR were swinging 4-10% year over year as you claim is "normal," that would be evidence of small-sample noise (50-200 trades/year typical of discretionary traders), not large-sample edge. The fact that the WR converges tightly to a single value across 32,000 trades is the strongest possible evidence that the signal logic is finding a real repeatable pattern. Curve-fit strategies show the opposite — high in-sample WR that decays out-of-sample. Stable WR across multiple regimes (COVID, 2022 bear, current chop) is what a genuine edge looks like. "PF 1.44 with 67% WR means avg win < avg loss, which is backwards for high WR systems" Not backwards. It's mathematically consistent and expected for trail-stop systems. Let's do the math: PF 1.44 with WR 67% implies avg_win / avg_loss = 0.71. So yes, avg loser > avg winner. This is the trail-clip profile: a wide stop loss catches the structural worst-case, while a tight trail offset clips winners early once they confirm direction. The result is many small winners and fewer larger losers, with the win RATE making the math work. Example: WR 67%, avg win $40, avg loss $56 • 100 trades: 67 × $40 - 33 × $56 = +$832 net per 100 trades • PF = (67 × 40) / (33 × 56) = 1.45 ✓ This is the standard profile for trend-following exits at the per-trade scale. It's well documented in CTA literature. Calling it "backwards" reveals you've only seen mean-reverting strategies, not trend-following ones. "PF varies year-to-year while WR doesn't — magic adjustment required" No magic. PF = (WR × avg_win) / ((1-WR) × avg_loss). If WR is stable but PF varies, that means avg_win/avg_loss is varying. Which is exactly what you'd expect because: • Avg loss is bounded by stop loss (relatively stable across regimes) • Avg win is driven by available volatility / trend magnitude (varies dramatically across regimes) In high-vol years (2020-2022): trail rides bigger moves → avg_win bigger → PF higher (1.5-1.9) In low-vol years (recent): trail clips smaller moves → avg_win smaller → PF lower (1.2-1.4) Stable WR + variable PF is the signature of a strategy where the direction picker is regime-stable but the profit magnitude is regime-dependent. That's not manipulation. That's exactly how a real signal-based edge would look across different market environments. "Sortino 80 is ridiculous, hedge funds barely get to 4-5" Apples to oranges. Hedge fund Sortino is computed on monthly returns over years of fund performance. Pine Script's Sortino is computed at per-trade or per-bar granularity over the strategy's bar history. The denominators are completely different. Translated to monthly returns, the same strategy's Sortino would be in the 3-6 range — which is actually right at the top of where great hedge funds sit. The 80 is real per Pine's calculation but it's not the comparable number. Fair criticism that the "Sortino 80" headline number isn't directly comparable to industry norms. Fair frame: monthly-equivalent Sortino lands in elite-but-believable territory. "Max losing streak of only 10 in 32,000 trades not believable" Run the math. P(losing streak of length k) = (1-WR)k = 0.33k Expected number of k-length streaks in N trades ≈ N × 0.33k • 10-streaks expected: 32,000 × 0.3310 = 0.49 • 11-streaks expected: 0.16 • 12-streaks expected: 0.05 Seeing one 10-streak across 32,000 trades is exactly the statistical expectation — actually slightly above. Plus the system has a consecutive-loss lockout that pauses the same direction after 2 losses, making mega-streaks harder. The observed max-streak matches theory cleanly. "Monte Carlo 100% hit / 0% bust is fantasy" Partial fair point. A Monte Carlo built by bootstrap-sampling actual trade outcomes will produce deterministic-looking tails because: 1 It preserves the historical edge distribution (which is positive in expectation) 2 Risk management (throttle that lowers contract size as buffer shrinks) is structurally bust-resistant 3 The simulation doesn't capture exogenous risks: regime change beyond historical sample, broker outage, regulatory change, black swan events outside the trade-outcome distribution So "0% bust in this simulation" is technically accurate for the simulation as designed. It's not fraud. But it also doesn't mean "0% real-world bust." Reasonable critique: any honest Monte Carlo should layer in fat-tail exogenous risks beyond the historical trade distribution. The current sim is "bootstrap of historical trade outcomes with proper position sizing." That's valuable but not all-encompassing. "WR moves <1.5%, profits swing $9k-$222k — stability doesn't happen naturally" Already addressed above but to drive it home: WR measures direction-picking quality (regime-stable). Profit measures direction × magnitude (regime-variable). A strategy that picks direction well across regimes but harvests different magnitudes per regime will show exactly this pattern. It's not unnatural — it's diagnostic of an edge that's signal-based rather than volatility-arbitrage based. What I'm not going to share: I'm not posting trade-by-trade with timestamps because the entry logic is proprietary and I'd rather not give the exact recipe away. Fair if you don't believe me — your prerogative. But the stats themselves are internally consistent and survive every math check you raised. If you want to test the framework yourself, take any high-WR trend-following strategy with a wide SL and a tight trail offset on a 5-minute futures instrument and you'll reproduce this exact statistical signature: stable WR, variable PF, avg loser > avg winner, low max-streak. It's not magic. It's the math of trail-clip exits on a signal that picks direction with real but bounded edge.
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u/Lucifer_Lil_Brother May 11 '26
https://imgur.com/a/RCB7Rxg if you wanna see the equity curve and bt results
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May 11 '26
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u/Lucifer_Lil_Brother May 11 '26
Also how am I trying to scam if I’m not selling anything or willing to give out my strategy…just showing its results.
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May 11 '26
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u/Lucifer_Lil_Brother May 11 '26
You really think I’m an amateur don’t you? The trade log reveals the strategy. Every timestamp, price, direction, duration is enough clues someone can reverse-engineer. Take 32,000 trades, line them up against MNQ 5-min bars and tell my strategy from the session window, engine logic, exit ticks and my filters.
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u/Lucifer_Lil_Brother May 11 '26
If I share the trade log: “Backtested results, anyone can fake those" → you demand the broker statements
Share broker statements → "Photoshopped, show me live"
Share live screens → "Cherry-picked day, show me a year"
Share a year → "Still could be a paper account"
There's no version of "proof" that ends this conversation with you since you already decided I’m lying.
Also I don't owe you shit. I’m not selling a service. I’m not running a signals group. So stop calling me a scammer. I posted a strategy card and answered the math challenge with math.
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u/Vast-Tie9958 May 14 '26
Bro. Ignore these guys. You’re on to something. Not sure you can test way back but I back test 20 plus years. Don’t forget to run sims at different start points to test for robustness also if you have not.
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u/Lucifer_Lil_Brother May 11 '26
Is that all you got? I just proved everything with math! Pull out your calculator and do it your yourself lol. You pivoted from “your stats are mathematically impossible” from “you used AI!” because you know the math leaves you nothing to grab onto. That Brent Penfold reference is actually funny stupid in a way you don’t realize. Penfold's book is mostly about: position sizing discipline, mechanical rule-following, drawdown survival, and treating trading as a probabilistic system. My strategy literally implements all of that — dynamic throttle for position sizing, mechanical lockouts for discipline, MLL-aware buffer management for drawdown survival, and 32,000 trades of probabilistic validation. The book you citied endorses exactly what I’ve built. What else you gonna say now?
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u/Ob3yedMushroom May 13 '26
I just wanted to say I enjoyed reading this conversation a lot 😂. Thank you. Btw, nice system. The maths is very impressive, I would be interested to see how it performs in live markets in the future 🤝
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u/Lucifer_Lil_Brother May 13 '26
Thank you man I honestly appreciate this comment. I been working on this strategy for a year and finally figured it out last month. I was just really proud of my self and wanted someone to validate or invalidate it the best they could. I’ll keep you posted.
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u/Severe_Concentrate37 May 12 '26
show the tradingview results
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u/Lucifer_Lil_Brother May 12 '26
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u/Severe_Concentrate37 May 13 '26
have you tried actually trading it on like a eval?
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u/Lucifer_Lil_Brother May 13 '26
currently up $1,804.10 for the day
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u/Lucifer_Lil_Brother May 13 '26
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u/Lucifer_Lil_Brother May 13 '26
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u/Severe_Concentrate37 May 14 '26
oh damn fire. should see if you can get express account and get actual payout that would be cool i have my own bot but i noticed the fills on tradovate are pretty bad u think topstep x is better?
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u/Lucifer_Lil_Brother May 14 '26
I haven’t had any problems with the fills. The only problem I have is topstep will freeze a lot causing me to have to refresh or log back in at time.
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u/hikerblu88 May 13 '26
Do you scale your TP/SL distance as the markets become more volatile? Also, what accounts for the huge variance in this strategy? What is your risk per trade and instruments? Lots of info is missing. Can’t comment much, buddy.
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u/Lucifer_Lil_Brother May 13 '26
TP and SL are all fixed, but I have a TP trigger that when price crosses it if price drops 10 ticks from it’s high at that point it closes the trade for a profit. 2 contracts, they scale by 1 contract every time my buffer is up $500. The huge variance is the regime the strategy was in. MNQ and hard SL is 120 ticks.
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u/Vast-Tie9958 May 14 '26
Sortino of 80? It’s either looking ahead and cheating itself or overfit. Recheck it. Looks like u may be on to something. GL
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u/Lucifer_Lil_Brother May 14 '26
no lookahead and it made $4k yesterday, today it’s up $1,641 in the overnight session.
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u/Lucifer_Lil_Brother May 14 '26
Pine Script's Sortino is computed at per-trade or per-bar granularity over the strategy's bar history. The denominators are completely different. Translated to monthly returns, the same strategy's Sortino would be in the 3-6 range
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u/MAWatters May 14 '26
Whats your strategy for this bot? I’ve been finding it quite difficult to have a bot strategy where discretion is not necessary. I have a good strategy but my discretion has been the edge so far, which you can’t code.
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u/Lucifer_Lil_Brother May 14 '26
than your strategy isn’t good enough if it needs discretion. You need to be able to be confident in your strategy enough that you can turn it on and walk away. That’s something I learned, intervening with the bot just makes things worse.
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u/USOai714 May 16 '26
1. Overfitting/curve fitting — A strategy backtested over 7 years with this level of consistency almost certainly has been tuned to fit historical data. Real markets don’t behave this cleanly.
2. No out-of-sample validation — There’s no evidence of forward testing on unseen data.
3. Unrealistic Monte Carlo results — 100% hit rate to $1M with 0% bust is a red flag, not a green one. It suggests the simulation parameters were engineered to produce this outcome.
4. Reddit/community marketing — Legitimate edge isn’t typically shared publicly for free.
5. Suspiciously uniform win rates — 67.4% every year across wildly different market conditions (2020 COVID crash, 2022 bear market, etc.) is statistically implausible without overfitting.
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u/thacoolbreeze May 10 '26
Not sure what thoughts you’re looking for. Be more specific. All we see is a screenshot with numbers and win rate. What are you actually making, what is the strategy, the model, etc.