Portfolio Simulator — Phase I

What does the BLT Engine
do to your portfolio?

Adjust allocation, AUM, and base portfolio. See real-time Sharpe improvement, VaR reduction, efficient frontier positioning, and crisis period stress-testing — all built from 18 years of backtested data.

Configuration panel
BLT Engine allocation 20%
Base portfolioBLT Engine
Portfolio AUM $50M
⚠ Approaching FX strategy capacity ($32M)
⚠ Exceeds max estimated capacity ($340M)
Base portfolio Sharpe 0.50
Base portfolio volatility 12%
Preset portfolio
Crisis stress-test

BLT Engine (fixed)

CAGR (17y)+7.22%
Volatility10.6%
Sharpe ratio0.34
Beta (full-period)0.075

Disclaimer

Simulation based on backtested data 2008–2025. Not investment advice.

Combined Sharpe
0.78
▲ +0.28 vs base
Portfolio volatility
10.8%
▼ −1.2% vs base
Expected return
+7.8%
▲ +1.8% vs base
BLT allocation ($)
$10M
Within capacity
VaR 95% · Base
−1.24%
Daily loss threshold
VaR 95% · Combined
−1.05%
Daily loss threshold
CVaR 95% · Base
−1.87%
Expected tail loss
CVaR 95% · Combined
−1.58%
Expected tail loss
Simulated equity curve 2008–2025 · $1,000,000 initial
Sharpe ratio comparison
SRcombined = Rp / σp = 0.500
Efficient frontier · Risk vs return
Annual return · Base vs combined
Drawdown profile · Crisis buffer effect
Monte Carlo · 5y CAGR distribution (1,000 deterministic simulations)
Bootstrap resampling of 18 annual returns · 1,000 paths of 5 years
Monte Carlo · Drawdown probabilities
Median 5y CAGR
5th percentile (worst 5%)
95th percentile (best 5%)
P( DD > 20% over 5y )
P( DD > 30% over 5y )
P( positive over 5y )

Deterministic seed = f(allocation, baseSR, baseVol). Same config → same result, always.

Correlation matrix · BLT Engine vs major asset classes
vs Equities
0.075
vs Bonds
0.041
vs CTA
0.112
vs Gold
0.098
vs Credit
0.051
vs 60/40
0.044

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an allocation?

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This simulator is for illustrative purposes only based on backtested data 2008–2025. Not a solicitation. Past performance does not guarantee future results. · Full legal disclaimers →