SmartFolio Academic Edition 3.0.52 Description:

SmartFolio is a highly advanced, easy to use analytical tool to assist and enhance the management of investment portfolios according to the investor's risk profile.

It allows the investor to select which assets are best suited to their portfolios, and provides all the information and analysis tools that are required to do so.

The software's advanced functionality and capabilities also make it ideal for corporate clients.

SmartFolio Academic Edition 3.0.52 Features:

General
· Fully supports the multi-period investment paradigm;
· Fully supports portfolios featuring assets with highly 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.
Portfolio Construction
· 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 performed directly on historical prices;
· Risk-free asset option;
· Factor-selection option for a factor-based asset pricing model.
Estimation of parameters
· Stambaugh combined-sample estimates, used if asset histories differ in length;
· Jorion average-returns estimate, which shrinks sample average returns towards a common value;
· Ledoit-Wolf covariance-matrix estimate, which shrinks the sample covariance matrix towards the constant correlations covariance matrix;
· Pastor-Stambaugh-Wang joint estimate of average returns and covariances, which shrinks sample estimates to their respective counterparts, implied by the selected factor model;
· MacKinlay-Pastor joint estimate of average returns and covariances, based on the assumption that prices are explained by an unobservable factor.
Portfolio optimization
· Three optimization criteria:
· Maximization of an expected utility with constant relative risk aversion
· Minimization of target shortfall probability
· Benchmark tracking;
· Worst-case scenario optimization: the resultant portfolios demonstrate optimal behavior under the worst-case scenario;
· Optimization engine based on IPOPT (Internal Point OPTimizer) - one of the most powerful nonlinear optimizers available today.
Target shortfall probabilities analysis
· Calculation of shortfall probabilities according to selected ranges for the investment horizon and target rate.
· Value-at-Risk analysis
· 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.
Historical simulations
· Simulations of portfolio strategies with continuous rebalancing;
· Simulations of portfolio strategies with continuous rebalancing and portfolio insurance - these strategies are optimal 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.
Data management
· Choose either Access-database or Excel-sheet format to store your data;
· Import historical data from a text file or download it from Yahoo!Finance.
Miscelaneous
· "Three-fund" portfolio calculation - utility-based portfolio, optimal in the presence of an estimation 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, STARR ratio.

SmartFolio Academic Edition 3.0.52 Requirements:

· Processor:Pentium III or above
· RAM: >= 500 Mb
· Hard Disk: >= 20 Mb
· Screen resolution: at least 1024x768

Related searches:

smartfolio - academic

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