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  • WinORS/e-AI

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     “Now that we have the efficient frontier, let’s create a benchmark portfolio for day-to-day management.  Let’s backtest the performance over the past year and then compare Sharpe and Treynor ratios.  We should also create a hedge strategy using either options or futures options given our RBF neural network forecast for  the markets...”

    WinORS Overview

    Wow! Serious applications in the quantitative sciences have never been so meaningful.

    WinORS applications are designed to support a complete analysis of the decision problem.

    In control. The decision-maker always has the required statistical, graphical, and report output that is needed for a detailed analysis of the problem.

    WinORS uses multiple workbooks to break down a solution by concept. This approach permits the analyst to focus on specific decision-making components for a complete problem analysis.

    So, you want to...

    • Compute Value-at-Risk (VaR) for net international cash flows
    • Build a large-scale Markowitz efficient set form actual data in as few as five mouse-clicks
    • Test option spread strategies for any firm with CBOE traded options
    • Option spread strategies using index based options
    • Portfolio backtesting with auto-comparison to an efficient set portfolio
    • Constrained quadratic programming implementation of efficient portfolio problem
    • Financial arbitrage pricing (APT) with 5 mouse clicks
    • Financial statement analysis of historical and pro forma industrial and depository analysis from an online database in 3 mouse clicks
    • Forecast high-frequency financial data using the Kajiji-4 Radial Basis Function Network
    • Forecasting methods by mouse click from the exponential smoothing family to artificial neural networks
    • Perform a regression-based analysis with regression ANOVA support, graphical diagnostics, and interactive help files
    • Descriptive statistics
    • Factor-analyze financial data with a choice of similarity matrix, factor methods, and factor scores
    • Perform constrained optimization: linear, quadratic, branch-bound mixed-integer, cutting plane mixed integer , zero-one, linear and nonlinear goal programming
    • And... yes, there is more...


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