WebCab Portfolio 4.2

WebCab Portfolio apply Markowitz Theory and Capital Asset Pricing Model to analyze and construct the optimal portfolio.
WebCab Portfolio apply Markowitz Theory and Capital Asset Pricing Model (CAPM) to analyze and construct the optimal portfolio with/without asset weight constraints with respect to Markowitz Theory by giving the risk, return or investors utility function; Also includes Performance Evaluation, extensive auxiliary classes/methods including equation solve and interpolation procedures, analysis of Efficient Frontier, Market Portfolio and CML.

Here are some key features of "WebCab Portfolio":

Markowitz Model - Construct optimally diversified portfolios.

Efficient Frontier - Construct the Efficient Frontier with or without constraints on the asset weights.
Utility Function - Discover and set the investors utility function.
Optimal Portfolio - Select the optimal portfolio or set of portfolios by providing the expected return desired, the maximum risk or the investors utility function.

Capital Asset Pricing Model (CAPM) - Construct optimally diversified portfolios with can hold or borrow cash.

Efficient Frontier - Construct the Efficient Frontier with or without constraints on the asset weights.
Market Portfolio - Find the Market Portfolio which offer the greater expected return per unit of risk.
Capital Market Line (CML) - Construct the CML with contains the optimal portfolio with respect to the CAPM.
Selecting Optimal Portfolio - Select the optimal portfolio by given expected return, risk or the Market Portfolio weighting.
Analysis of Optimal Portfolio - Evaluate the risk, expected return or Market Portfolio weighting of the optimal portfolio whenever one of these three properties is known.

Auxiliary Classes

Interpolation - Cubic spline and general polynomial interpolation procedures to assist in the study and manipulation of curves such as the Efficient Frontier which are evaluated at a finite number of points.
SolveFrontier - Solve the Efficient Frontier with respect to the risk, return, or the investors utility function which may be given as a function of the risk or the expected return.
TwoAssetPortfolio - Evaluate of the optimal weighting of a portfolio with two assets. This functionality can be used to analyze the effect of a single purchase or sale from an arbitrary portfolio
AssetParameters - Evaluation of the covariance matrix, expected return, volatility, portfolio risk/variance, ARCH model for expected price.
MaxRange - Evaluates the maximum range of the values of the expected return for which Efficient Frontier should be considered when the historical data set does is not consistent within the assumptions of Markowitz Theory and CAPM.
Performance Evaluation - Offers a number of procedures for accessing the return and risk adjusted return (Treynors Measure, Sharpes Ratio).

GUI Bundle - we bundle a suite of graphical user interface JavaBean components allowing the developer to plug-in a wide range of GUI functionality (including charts/graphs) into their client applications.
JDBC Mediator - A J2SE Component which mediates between a J2SE component, its J2SE Clients and the Database server. The JDBC Mediator J2SE classes are a convenient way of enhancing all financial and mathematical specific methods with JDBC-based functionality. Check the jdbc subpackage of every J2SE class for JavaDocs documentation.
Web Application Example - A Java WAR file which contains a JSP example that makes use of the functionality provided by our J2SE Component.
Synthetic JDBC - The JDBC functionality provided by the Web Application example included within this package. This Web Application is an example of how to make a JSP client using our J2SE Component while manually implementing the JDBC code. The JSP Application applies J2SE methods to certain rows from the database and lists the output in HTML format.

last updated on:
March 1st, 2006, 21:02 GMT
price:
$199.00
 
developed by:
WebCab Components
homepage:
www.webcabcomponents.com
license type:
Shareware 
category:
ROOT \ Internet \ HTTP (WWW)

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