Simulated Trading Report

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


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.
2025-03-14T19:07:08.750050 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:08.947952 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:09.159166 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:09.317065 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:09.459327 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:09.618518 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:09.827021 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:10.016836 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:10.186350 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:10.344306 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:10.530427 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:10.750535 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:10.918389 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-14T19:07:11.018082 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%34.76%
CAGR﹪2.11%33.38%

Sharpe0.274.77
Prob. Sharpe Ratio59.17%99.99%
Smart Sharpe0.264.62
Sortino0.367.71
Smart Sortino0.357.46
Sortino/√20.265.45
Smart Sortino/√20.255.27
Omega2.162.16

Max Drawdown-8.73%-3.61%
Longest DD Days22931
Volatility (ann.)10.84%9.76%
R^20.580.58
Information Ratio0.380.38
Calmar0.210.9
Skew-0.47-0.69
Kurtosis0.431.07

Expected Daily0.01%0.18%
Expected Monthly0.19%3.83%
Expected Yearly2.19%34.76%
Kelly Criterion-10.25%36.92%
Risk of Ruin0.0%0.0%
Daily Value-at-Risk-1.11%-0.83%
Expected Shortfall (cVaR)-1.11%-0.83%

Max Consecutive Wins811
Max Consecutive Losses46
Gain/Pain Ratio0.051.16
Gain/Pain (1M)0.19745.21

Payoff Ratio0.71.12
Profit Factor1.052.16
Common Sense Ratio0.822.48
CPC Index0.41.61
Tail Ratio0.781.15
Outlier Win Ratio2.92.72
Outlier Loss Ratio2.753.23

MTD-3.25%1.94%
3M-3.24%7.74%
6M1.91%25.58%
YTD2.19%34.76%
1Y2.19%34.76%
3Y (ann.)2.11%33.38%
5Y (ann.)2.11%33.38%
10Y (ann.)2.11%33.38%
All-time (ann.)2.11%33.38%

Best Day1.63%1.39%
Worst Day-2.28%-2.23%
Best Month7.4%7.89%
Worst Month-3.24%-0.09%
Best Year2.19%34.76%
Worst Year2.19%34.76%

Avg. Drawdown-1.91%-0.89%
Avg. Drawdown Days476
Recovery Factor0.259.62
Ulcer Index0.040.01
Serenity Index0.059.65

Avg. Up Month3.44%6.36%
Avg. Down Month-1.38%-0.05%
Win Days54.64%66.67%
Win Month44.44%88.89%
Win Quarter66.67%100.0%
Win Year100.0%100.0%

Beta-0.69
Alpha-0.45
Correlation-76.06%
Treynor Ratio-59.85%

EOY Returns vs Benchmark
YearBenchmarkStrategyMultiplierWon
20232.1934.7615.90+

Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2023-03-102023-03-30-3.6121
2023-08-152023-09-14-2.8131
2023-02-062023-03-03-2.7126
2023-06-222023-06-28-2.327
2023-07-062023-07-12-1.997
2023-08-022023-08-10-1.299
2023-06-062023-06-13-0.968
2023-05-242023-05-26-0.803
2023-03-082023-03-08-0.671
2023-09-182023-09-22-0.575