Quant Research
31 Strategies Tested, 4 Survived
The complete results of testing 31 systematic trading strategies across forex and crypto. What worked, what failed, and the patterns that separate robust strategies from curve-fitted illusions.
Quant Research
31 Strategies Tested. 2 Survived.
We hunt scientific papers nobody thinks to apply to markets, build systematic strategies from them, then kill them honestly with tick-level backtesting. Here's what's left standing.
Strategy Results
Tick-verified where possible. Walk-forward validated. 42M ticks of EURUSD.
Strategy PF Pips Trades Verdict
ECVT (EURUSD 1H) Singha 2025 1.44 +198 44 ALIVE
Jump Trend (1:1) 1.10 +293 601 ALIVE
FVG Magnet (1H tick) 1.04 +466 1504 DEAD
FVG Magnet (15m tick) 0.94 -1,453 3217 DEAD
FVG Magnet (5m tick) 0.80 -8,509 6842 DEAD
Jump Fade (1H) 0.53 -2,947 601 DEAD
Hurst Regime (Crypto) N/A 0 100% DEAD
ECVT (Equities) Singha 2025 N/A -88 9 DEAD
Key Findings
OHLC Lies
FVG showed PF 4.28 on OHLC daily. Tick verification: PF 1.04. Close-based SL/TP inflates results by 4×. Always verify with tick data.
Distribution First
Hurst > 0.6 fires on 100% of crypto hourly bars. A signal that's always "on" has zero information content. Profile thresholds before backtesting.
Decompose Composites
Jump fade + trend = -3000 pips. Trend alone = +293 pips (55% WR). Composite signals can hide working components.
Signals Don't Transfer
ECVT: +198 bps on EURUSD hourly, 0-9 signals on equities. Jump: works on Gold daily, pure noise on forex hourly. Always validate per market.
ECVT — Our Best Edge
Based on Singha 2025. Entropy collapse predicts volatility magnitude — we adapted it from tick-level trade data to hourly returns.
1.44Profit Factor
41%Win Rate
44Trades (2yr)
10/20OOS Windows
2.08×Win/Loss Ratio
Research Posts
Quant Research
Hurst Exponents for Detecting Mean Reversion in Forex
Using the Hurst exponent to dynamically identify mean-reverting vs. trending regimes in forex markets. Complete theory, Python implementation, and backtest results for a regime-adaptive trading system.
Quant Research
FVG Magnetism: Do Fair Value Gaps Really Fill?
A rigorous statistical analysis of fair value gap magnetism in price action trading. We test the claim that FVGs act as magnets for price, introduce the FVG Wall specification, and present backtest results across forex and crypto markets.
Quant Research
Entropy Collapse as a Volatility Timing Signal
How we use Shannon entropy of price returns to detect volatility regime changes before they happen. Full methodology, Python implementation, and backtest results showing a 1.44 profit factor on EURUSD.
Reproduce Everything
Every strategy, every backtest, every signal — fully open source on GitHub.
View Repository