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.
2025-03-15T09:06:34.912933 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.080467 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.260113 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.394024 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.511962 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.650139 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.826850 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:35.997375 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:36.149806 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:36.291911 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:36.456244 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:36.610698 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:36.738468 image/svg+xml Matplotlib v3.9.2, https://matplotlib.org/

2025-03-15T09:06:36.815299 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%39.67%
CAGR﹪2.11%38.07%

Sharpe0.274.58
Prob. Sharpe Ratio59.17%99.99%
Smart Sharpe0.264.35
Sortino0.367.75
Smart Sortino0.357.36
Sortino/√20.265.48
Smart Sortino/√20.245.21
Omega2.112.11

Max Drawdown-8.73%-4.44%
Longest DD Days22953
Volatility (ann.)10.84%11.62%
R^20.560.56
Information Ratio0.390.39
Calmar0.210.34
Skew-0.47-0.28
Kurtosis0.430.6

Expected Daily0.01%0.21%
Expected Monthly0.19%4.35%
Expected Yearly2.19%39.67%
Kelly Criterion-10.68%35.92%
Risk of Ruin0.0%0.0%
Daily Value-at-Risk-1.11%-0.99%
Expected Shortfall (cVaR)-1.11%-0.99%

Max Consecutive Wins810
Max Consecutive Losses46
Gain/Pain Ratio0.051.11
Gain/Pain (1M)0.1927.82

Payoff Ratio0.691.12
Profit Factor1.052.11
Common Sense Ratio0.822.6
CPC Index0.41.56
Tail Ratio0.781.23
Outlier Win Ratio3.542.83
Outlier Loss Ratio2.862.87

MTD-3.25%0.59%
3M-3.24%11.25%
6M1.91%32.21%
YTD2.19%39.67%
1Y2.19%39.67%
3Y (ann.)2.11%38.07%
5Y (ann.)2.11%38.07%
10Y (ann.)2.11%38.07%
All-time (ann.)2.11%38.07%

Best Day1.63%2.08%
Worst Day-2.28%-2.24%
Best Month7.4%8.23%
Worst Month-3.24%-1.47%
Best Year2.19%39.67%
Worst Year2.19%39.67%

Avg. Drawdown-1.91%-1.1%
Avg. Drawdown Days477
Recovery Factor0.258.93
Ulcer Index0.040.01
Serenity Index0.059.42

Avg. Up Month3.44%7.77%
Avg. Down Month-2.93%-1.43%
Win Days54.64%66.12%
Win Month44.44%88.89%
Win Quarter66.67%100.0%
Win Year100.0%100.0%

Beta-0.8
Alpha-0.51
Correlation-74.69%
Treynor Ratio-59.79%

EOY Returns vs Benchmark
YearBenchmarkStrategyMultiplierWon
20232.1939.6718.15+

Worst 10 Drawdowns
StartedRecoveredDrawdownDays
2023-02-062023-03-30-4.4453
2023-07-062023-07-12-2.397
2023-08-152023-08-30-2.2116
2023-06-222023-06-27-2.186
2023-09-052023-09-14-1.9110
2023-08-022023-08-11-1.4010
2023-09-182023-09-22-1.265
2023-06-062023-06-13-1.268
2023-05-222023-05-31-0.9910
2023-05-162023-05-18-0.773