Monte Carlo APIΒΆ
Monte Carlo API applies to a series of methods that apply to a 3 dimensional data cube where the dimensions represent the time, trials and assets respectively. For example, if the simulated cube projects 10 years of monthly data for 8 assets for 10000 trials (that is 10000 simulations), the cube will be a numpy array with shape (120, 10000, 8).
- Returns
- Risk
- Portfolio Beta against Asset
- Portfolio Correlation against Asset
- CVaR Attribution
- CVaR Diversification Ratio
- Portfolio CVaR
- Diversification Ratio
- Drawdown Statistics
- Portfolio Empirical Covariance Matrix
- Risk Performance Benchmark
- Risk Performance Benchmark
- Tail Loss Statistics
- Tracking Error
- Volatility Attribution
- Portfolio Volatility
- Sensitivity