PF
Property Perfect Public Co Ltd
stock NYSE

Hey everyone,
We have been live testing a multi-strategy crypto perpetual futures bot (trading on Delta Exchange with 5x leverage and a 9-regime classifier based on ADX, ATR%, and Hurst exponent).
We recently completed a forensic audit across our first \*\*115 closed live trades\*\* and noticed a severe performance divergence that we want to get feedback on from the community:
\---
\### The Empirical Numbers
\*\*Trades 1 to 21 (Sept 1 - Sept 6) -- The Peak:\*\*
\* \*\*Win Rate:\*\* 57.1% (12W / 9L) | Net PnL was positive with a steady equity curve.
\* \*\*Timeframes:\*\* 1h LTF / 4h HTF and 4h LTF / 1d HTF (avg duration: 10 to 24 hours).
\* \*\*Core Drivers:\*\* VWAP Pullback and VSA Climax Momentum.
\* \*\*Parameters:\*\* Tight stops (1.0x to 1.4x ATR), 1.3x to 1.6x R:R targets.
\*\*Trades 22 to 115 (Sept 7 - Sept 30) -- The Drawdown:\*\*
\* \*\*Win Rate:\*\* Dropped to 39.8% (37W / 56L) with net negative drift.
\* \*\*Root Causes Identified:\*\*
Timeframe reduction down to 5m/15m micro-scalping (high taker fees + noise stop-outs).
Rapid "setup churn" (adding experimental setups like FVG Rebalance, Asia Session Expansion, and VP VAL Reclaim which over-traded adverse chop).
\---
\### The Optimizer Bottleneck We Need Feedback On
We run a \*\*Cross-Sectional Multi-Timeframe Universe-Pooled Rolling Walk-Forward Optimizer (WFO)\*\*. When we run backtests across 60 to 200 days, almost all our top-performing setups are now being stamped \*\*KILLED\*\* by the optimizer filters.
Here are the 4 specific design questions we would love your critique on:
\#### 1. Unconditioned Aggregate PF vs. Whitelisted Regime PF (The "Mutual Drag" Trap)
In Part B (Out-of-Sample evaluation), the optimizer calculates an \*\*unconditioned aggregate Profit Factor across all 9 market regimes combined\*\* and enforces a hurdle (PF >= 1.15 / Noise Floor).
\* \*\*The Problem:\*\* In our recent run for WLDUSDT on 1h/4h VWAP Pullback:
\* In RANGING\_LOW\_VOL: \*\*100% Win Rate (4W/0L), +8.26% PnL\*\*
\* In RANGING\_MED\_VOL: \*\*60% Win Rate (3W/2L), +1.80% PnL\*\*
\* In WEAK\_TREND\_LOW\_VOL: It took 4 losses (-8.38% PnL).
\* Because the unconditioned 9-regime PF came out to \*\*1.14\*\*, the WFO stamped it \`KILLED (Noise Floor < 1.15)\` and discarded the symbol completely.
\* \*\*Question:\*\* In production, our bot \*\*whitelists only profitable regimes\*\* and suppresses the rest. Shouldn't the WFO qualification hurdle be evaluated strictly on the \*\*whitelisted/filtered regime trades\*\* (e.g., Filtered PF >= 1.30, N >= 10) rather than requiring a mean-reverting setup to be profitable inside an unfavorable trending regime?
\#### 2. Timeframe Selection: Locking Back to 1h/4h vs. 15m Scalping
\* On 5m/15m charts, exchange taker fees (0.05%), bid-ask slippage, and random wick stop-outs severely degraded our edge.
\* On 1h/4h, macro EMA(50) alignment filtered out most fakeouts, and average moves exceeded 1.5% to 3.0%, easily beating fee drag.
\* \*\*Question:\*\* In crypto perps, do you recommend completely abandoning intraday 5m/15m setups in favor of purely running 1h/4h and 4h/1d swing regimes?
\#### 3. Cross-Sectional Universe Pooling vs. Volatility-Clustered Centroids
\* Right now, the optimizer pools all symbols in the basket together to find a single universal centroid \`(SL\_mult, TP\_ratio)\`.
\* However, high-beta coins (e.g. WLD, APT) have drastically different ATR expansion profiles than lower-beta coins (ADA, BTC).
\* \*\*Question:\*\* Do you prefer universal cross-sectional pooling (1 shared parameter set for all symbols in the basket), or should centroids be clustered by volatility tiers / individual symbol centroids?
\#### 4. Stop Loss Multipliers: Tight (1.0x to 1.4x ATR) vs. Wide (2.5x to 3.0x ATR)
\* The optimizer added an anti-overfitting rule (\`is\_cliff\` when SL <= 1.0), which penalizes tight stops.
\* As a result, the optimizer drifted SLs up to 2.5x to 3.0x ATR, which extended trade holding times past 24 to 36 hours and caused larger dollar drawdowns per loss.
\* \*\*Question:\*\* For 1h/4h swing setups, what is your recommended sweet spot for Stop Loss ATR multipliers (1.2x to 1.5x vs 2.0x to 2.5x) to balance noise tolerance with capital preservation?
\---
Would love to hear how other systematic quants and algorithmic traders handle regime-gated WFO filters and cross-sectional parameter pooling!

Buying more BLS, because I want to.
Everything else is the PF is forking me from left, right and centre!

btw the Krugs are SP, not PF

I use both, but I trust the distribution/ranges more than a single rolling PF. I compare the last 30–50 closed trades with the backtests expectancy range, then split it by regime and execution tags. Rolling expectancy is a useful dashboard; PF can get skewed by one big winner. If the results fall outside the tested band while rule-following and fills look clean, I cut size and re-test. If the tags show execution drift, it’s a process problem, not proof the edge disappeared.

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1-minute XAUUSD data, including spreads, slippage, and swap; compounded sizing. Harsh-fill result: 7.8%/month, PF 1.71, 34% max DD, \~5.5 trades/month, 40% losing months. Monte Carlo (reshuffled trades, 10% randomly skipped): median $54K from $1K, worst 5% $7K with a 61% drawdown.
The window is gold's strong 2022–26 uptrend; in older, choppier years, this approach breaks even. Looking for feedback on robustness testing.

if you back it out from your PF and win rate, your avg winner is about 2.25x your avg loser. that's actually a decent shape for breakouts. breakeven at that ratio is around a 31% win rate, so you're roughly 2 winners out of 49 away from flat. that's noise at this sample size, not a broken strategy. i'd keep logging and look at whether the losers cluster somewhere specific (first 30 min, failed retests, low volume breaks) before changing anything.

my personal rule of thumb, only develop on the first 60% of 5+ years of data. Then next 20% should be validation data and the last 20% data should be used for OOS. Train / develop on the first 60% of data until you get reasonable results i.e PF >=1.3, expectancy and whatever other requirements you have. then run the backtest on the validation data. validation results net profit must be positive to continue, doesn't need to be fantastic because it's a much shorter period of data then training. If validation net profit is positive then run on oos data. same requirement as validation data, it must be net positive. now my personal final requirement is that validation + oos net profit must be >= 70% training period data. if these requirements don't pass strategy goes out the window and we move on. hope this helps

book some profits which also is optional imo cause your average is 110 even 5-10% movement in this will keep pushing your PF (but 47K market cap is huge its a midcap company now so from here stock price growth might be slow)

Would you say PF 1.5 about 52% win rate, and 1.25 win ratio about 160 trades a year is acceptable, over 12 months backtesting

Most are good stocks. If you are new investor, got decent selection here. Now sure what's size of your PF, unless its solid 7 fig, it's bit over diversified.
Relience is very lumpy and given what all company is doing, i am looking to get out. If you have invested recently better get out at breakeven.

Looking good. I just managed to pass my first prop eval using my NQ intraday algo. Passed in 6 days. 63% win rate and 2.8 PF

Guys broker appraiser here if di ninyo na kuha ang benta accept na lang. Support the client sa decision nila.
Also if broker kayo or salesperson na nag hahaggle ng services for the “congratulations” ng company it’s not worth it talaga. Respect the profession. You have the professional fee because you are procurement cause. Don’t discount too much lalo if yung PF mo naka salalay.
Also to the agent na nag share pa kay client about personal things ng other agent na naka close. That’s so unprofessional. Less talk, less mistake.

Bro with max 2 lakh loss complaining while people holding losses with lakhs and crores aren't. If you're doing SIP for a long term, just shut up and continue doing it. Barking in short term will not affect your PF in long term. Drawdowns happen and also recover fast when it does.

Mrs. FM: “I don’t invest in stocks. My money is safely in PF.”
Also Mrs. FM: “Market is down? Great opportunity! Keep investing. Take it positively.”