SmartFolio 3.2.4 Corporate License

Find the most appropriate asset allocation according to your investment goals, market history andforecasts;

Analyze risks of your investment portfolio from various perspectives (volatility, value-at-risk,shortfall probabilities);

Arrive at adequate portfolio rebalancing strategy to minimize rebalancing transaction costs.

Fully supports the multi-period investment paradigm.

Fully supports portfolios featuring assets with non-Gaussian distribution of returns, or non-linear inter-dependencies, including options and hedge funds. This is achieved through direct simulation of portfolio dynamics with no model assumptions.

Simultaneous creation of two environments for portfolio analysis:  

• Analytical environment: logarithmic price increments are assumed to be independent normally distributed random variables.
• Historical environment: optimization and other procedures are based directly on historical prices.

Risk-free asset option.

Factor-selection option for a factor-based asset pricing model.

Equally-weighted sample estimates of expected returns and covariances

Exponentially weighted sample estimates of expected returns and covariances (new in v.3.1)

Stambaugh combined-sample estimates, used if asset histories differ in length. 

Jorion expected returns estimate, which shrinks sample average returns to a common value.

Ledoit-Wolf covariance matrix estimate, which shrinks the sample covariance matrix to the constant correlations covariance matrix. 

Pastor-Stambaugh-Wang joint estimate of expected returns and covariances, which shrinks sample estimates to their respective counterparts, implied by the selected factor model. 

MacKinlay-Pastor joint estimate of expected returns and covariances, based on the assumption that prices are explained by an unobservable factor.

The Black-Litterman model that incorporates subjective invetsor views in parameter estimation and asset allocation process.

Dummy estimates of expected returns and covariances further used in construction of risk-based portfolio strategies (risk parity and maximum diversification) (new in v.3.2)

Calculation of target shortfall probabilities according to selected ranges for the investment horizon and target rate.

Simultaneous calculation of two risk measures: Value-at-Risk (VaR) and Conditional Value-at-Risk(CVaR).

Various techniques for calculation of VaR and CVaR, including:

• Delta-Normal Method (DNM)
• Empirical distribution
• Implied normal distribution
• Implied non-central t-distribution 
• Cornish-Fisher expansion.

Construction of VaR and CVaR surfaces according to selected ranges for the investment horizon and significance level.

Simulations of portfolio strategies with continuous rebalancing.

Simulations of portfolio strategies with continuous rebalancing and portfolio insurance — these strategies are optimal in a situation when a predetermined portion of the initial wealth and/or accumulated profits must be maintained.

Portfolio-strategy simulations with “inaction region” rebalancing — these strategies are optimal in the presence of proportional transaction costs.

Portfolio-strategy simulations with “inaction region” rebalancing and portfolio insurance.

Choose either an Access-database or Excel spreadsheet format to store your data.

• Yahoo!Finance
• Text files
• Excel tables
• Bloomberg Professional

Batch import from all data sources

1-click update from all data sources

“Three-fund” portfolio calculation — utility-based portfolio, optimal in the presence of anestimation error in the model parameters.

Utilization of Block Bootstrapping algorithm in the calculation of VaR, CVaR, and shortfall probabilities.

Determine Inaction region optimal size in the presence of proportional transaction costs, based on a multidimensional extension of the Davis-Norman approach.

Wide range of optimization constraints, which also include:

• Constraints on assets groups
• Highly non-linear margin constraint to account for margin requirements in portfolio components.

Various performance measures including Information ratio, Sortino ratio and STARR ratio.