Key Findings

The implementation of the transaction cost model to account for market impact produces statistically robust alpha generation despite aggressive market friction assumptions.
The total return differential of 1529% confirms persistence of alpha generation after incorporation of realistic execution costs.
Post-cost Sharpe ratio SR AI Strategy=1.86 versus SR Buy-and-Hold=0.69 demonstrates that transaction cost drag does not eliminate statistical significance of performance differentials.

The AI Strategy performance exhibits monotonic decay with respect to the execution latency parameter, resulting in Sharpe Ratio decay of 18% as the delay increases from 1 to 15 minutes.
Despite the maximum tested latency, the strategy maintains +135.3% CAGR outperformance (CAGR AI Strategy = 40% vs CAGR Buy-and-Hold=17%)
All the risk return metrics maintain statistical resilience to execution delay, representing an improvement over passive implementation.

Optimal risk-adjusted metrics achieved by Hybrid approach with Sharpe ratio enhancement of ΔSR=+0.14 versus AI Strategy implementation and ΔSR=+1.31 versus passive allocation.
Cumulative return amplification of 62.2% achieved through optimized market exposure.
Time-series decomposition reveals superior convexity characteristics with 9/12 quarters generating positive excess returns, including peak quarterly alpha generation exceeding +100% in multiple observation periods.

Leverage distribution f(L) exhibits pronounced positive skewness with P(L≤2.0)=0.862, indicating 86.2% of position entries maintain conservative leverage parameters.
Capital utilization probability mass function concentrated in the first decile bin with P(C≤0.10)=0.603, implementing systematic variance-minimization methodology.
Bivariate distribution analysis confirms strategic conditional dependency with joint probability P(L=1.0,C∈[0,10%])=0.362, while maximum risk exposure configuration (L=5.0,C≈70%) constitutes only 1.7% of trading intervals.
Expected leverage-capital product E[L⋅C]≈0.286 maintains sufficient margin buffer capacity to prevent performance degradation through forced liquidations during adverse market conditions.

Conditional probability analysis confirms significant drawdown protection during sharp market corrections.
Strategy demonstrates statistically insignificant capture of extreme positive momentum regimes, consistent with mean-reversion rather than trend-following signal extraction.
Inverse conditional distribution reveals alpha generation during neutral or negative price environments
Empirical probability structure provides mathematical validation for Hybrid implementation superiority through orthogonal return stream generation relative to passive exposure.

Last updated 2 months ago

The implementation of the transaction cost model to account for market impact produces statistically robust alpha generation despite aggressive market friction assumptions.
The total return differential of 1529% confirms persistence of alpha generation after incorporation of realistic execution costs.
Post-cost Sharpe ratio SR AI Strategy=1.86 versus SR Buy-and-Hold=0.69 demonstrates that transaction cost drag does not eliminate statistical significance of performance differentials.

The AI Strategy performance exhibits monotonic decay with respect to the execution latency parameter, resulting in Sharpe Ratio decay of 18% as the delay increases from 1 to 15 minutes.
Despite the maximum tested latency, the strategy maintains +135.3% CAGR outperformance (CAGR AI Strategy = 40% vs CAGR Buy-and-Hold=17%)
All the risk return metrics maintain statistical resilience to execution delay, representing an improvement over passive implementation.

Optimal risk-adjusted metrics achieved by Hybrid approach with Sharpe ratio enhancement of ΔSR=+0.14 versus AI Strategy implementation and ΔSR=+1.31 versus passive allocation.
Cumulative return amplification of 62.2% achieved through optimized market exposure.
Time-series decomposition reveals superior convexity characteristics with 9/12 quarters generating positive excess returns, including peak quarterly alpha generation exceeding +100% in multiple observation periods.

Leverage distribution f(L) exhibits pronounced positive skewness with P(L≤2.0)=0.862, indicating 86.2% of position entries maintain conservative leverage parameters.
Capital utilization probability mass function concentrated in the first decile bin with P(C≤0.10)=0.603, implementing systematic variance-minimization methodology.
Bivariate distribution analysis confirms strategic conditional dependency with joint probability P(L=1.0,C∈[0,10%])=0.362, while maximum risk exposure configuration (L=5.0,C≈70%) constitutes only 1.7% of trading intervals.
Expected leverage-capital product E[L⋅C]≈0.286 maintains sufficient margin buffer capacity to prevent performance degradation through forced liquidations during adverse market conditions.

Conditional probability analysis confirms significant drawdown protection during sharp market corrections.
Strategy demonstrates statistically insignificant capture of extreme positive momentum regimes, consistent with mean-reversion rather than trend-following signal extraction.
Inverse conditional distribution reveals alpha generation during neutral or negative price environments
Empirical probability structure provides mathematical validation for Hybrid implementation superiority through orthogonal return stream generation relative to passive exposure.

Last updated 2 months ago