Simulated Trading Report

Forward model simulation on CLOSE PRICES (4:10pm) with smart exits disabled


Past performance is for illustrative purposes only and does not predict future results.
Simulation runs are...
Simulation runs are without transaction costs, however these are relatively immaterial at scale (0.03% per order) and have a minor impact on expected performance unlike order execution challenges.

Version 1
Utilized a hybrid multi-factor model along with a basic ML-based predictive model and ML-based portfolio selection. Launched on 26/5/2021.
Version 2

Focused on streamlining data processes, enhancing system reliability, and improving transparency. Launched on 10/2/2022.

Note: Version 1 & 2 experienced significant losses in unfavorable market conditions prior to the improved modeling and risk management implemented in version 3 onwards. While not representative of the running system's performance, they are included for transparency.

Version 3
Introduced a highly optimized predictive ML-based model. Launched on 22/06/2022.
Version 4
All positions and position sizing now handled by a portfolio optimiser along with numerous risk management and optimization features. Launched on 8/12/2022.
Version 5
Integrated lessons learned from live operations, enhancing robustness, order execution, and incorporating numerous minor optimizations. Launched on 17/7/2023.
Version 5.1
Order execution enhancements at market closing auction and optimised intraday exit conditions to better match deployed capital. Launched on 18/9/2023.
2025-03-14T19:07:06.106762 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:06.310706 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:06.515391 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:06.668210 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:06.814309 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:06.984663 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:07.199998 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:07.389639 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:07.556448 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:07.710997 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:07.897008 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:08.074279 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:08.224435 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:08.318971 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/
Key Performance Metrics
MetricBenchmarkStrategy
Risk-Free Rate0.0%0.0%
Time in Market98.0%98.0%

Total Return2.19%37.69%
CAGR﹪2.11%36.18%

Sharpe0.274.46
Prob. Sharpe Ratio59.17%99.99%
Smart Sharpe0.264.3
Sortino0.367.56
Smart Sortino0.357.3
Sortino/√20.265.35
Smart Sortino/√20.255.16
Omega2.062.06

Max Drawdown-8.73%-4.93%
Longest DD Days22929
Volatility (ann.)10.84%11.33%
R^20.560.56
Information Ratio0.380.38
Calmar0.28.76
Skew-0.47-0.23
Kurtosis0.430.56

Expected Daily0.01%0.2%
Expected Monthly0.19%4.13%
Expected Yearly2.19%37.69%
Kelly Criterion-6.59%32.76%
Risk of Ruin0.0%0.0%
Daily Value-at-Risk-1.11%-0.97%
Expected Shortfall (cVaR)-1.11%-0.97%

Max Consecutive Wins88
Max Consecutive Losses46
Gain/Pain Ratio0.051.06
Gain/Pain (1M)0.1917.13

Payoff Ratio0.741.2
Profit Factor1.052.06
Common Sense Ratio0.822.8
CPC Index0.421.56
Tail Ratio0.781.36
Outlier Win Ratio3.512.78
Outlier Loss Ratio2.833.09

MTD-3.25%0.38%
3M-3.24%11.81%
6M1.91%30.44%
YTD2.19%37.69%
1Y2.19%37.69%
3Y (ann.)2.11%36.18%
5Y (ann.)2.11%36.18%
10Y (ann.)2.11%36.18%
All-time (ann.)2.11%36.18%

Best Day1.63%2.03%
Worst Day-2.28%-2.12%
Best Month7.4%7.66%
Worst Month-3.24%-2.22%
Best Year2.19%37.69%
Worst Year2.19%37.69%

Avg. Drawdown-1.91%-1.04%
Avg. Drawdown Days476
Recovery Factor0.257.65
Ulcer Index0.040.01
Serenity Index0.057.98

Avg. Up Month3.44%7.19%
Avg. Down Month-2.93%-2.2%
Win Days54.64%63.39%
Win Month44.44%88.89%
Win Quarter66.67%100.0%
Win Year100.0%100.0%

Beta-0.78
Alpha-0.48
Correlation-75.01%
Treynor Ratio-57.4%

EOY Returns vs Benchmark
YearBenchmarkStrategyMultiplierWon
20232.1937.6917.24+

Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2023-02-062023-03-06-4.9329
2023-03-102023-03-30-3.5221
2023-07-062023-07-12-2.667
2023-08-152023-08-30-2.1716
2023-09-052023-09-14-1.6310
2023-06-222023-06-27-1.556
2023-09-182023-09-22-1.545
2023-05-222023-06-01-1.4611
2023-08-022023-08-09-1.248
2023-03-082023-03-08-1.011