Monte Carlo API

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
  • Annualized Returns
  • Annualized Returns against Benchmark
  • Annualized Quantile Returns
  • Annualized Quantile Returns against Benchmark
  • Returns Attribution
  • Returns Distribution
  • Returns Path
• 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
  • Sensitivity of Portfolio to Shocks
  • Sensitivity of Portfolio's Annualized Returns to Shock
  • Sensitivity of Portfolio's Annualized Volatility to Shock
  • Sensitivity of Portfolio's CVaR to Shock