Author

# WebCab Components

## WebCab Bonds

Home Page

Categories: Miscellaneous

Models the pricing and risk analytics of interest rate cash and derivative products.
WebCab Bonds covers the fundamental theory of bonds, as well as the topics of fixed-interest bonds and interest-based calculations.

Supports:
- Fundamental theory of bonds: Pricing and Yield, Treasury bonds, Constructing the Zero Rate Curve, Forward Rates and FRAs, Duration and Convexity
- Yield of Fixed-Interest Bonds on Interest payment dates
- Interest Calculations

Also contains:
- GUI Bundle: suite of graphical user interface JavaBean components allowing to plug-in GUI functionality (including charts/graphs) into client applications.
- JDBC Mediator: a J2SE component that mediates between a J2SE component, its J2SE clients and the database server.
- Web Application Example: a Java WAR file that contains a JSP example that makes use of the functionality provided by the J2SE Component.
- Synthetic JDBC: an example of how to make a JSP client using the 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.

 Built for Java Library

## WebCab Functions

Home Page

Categories: Math - Logic - AI - Rules - Science

Java API components offering numerical procedures to either construct a function of one or two variables from a set of points (i.e. interpolate), or solve an equation of one variable. The interpolation procedures provided include Newton polynomials, Lagrange's formula, Burlisch-Stoer algorithm, Cubic splines (natural and free), Bicubic interpolation and procedures for find the interpolation functions coefficients. In order to solve an equation we provide the Van Wijngaarden-Dekker-Brent algorithm, interval bisection method, secant and false position, Newton-Raphson method and Ridders' method.

This suite includes the following features:
- Interpolation Module: polynomial interpolation and extrapolation, coefficients of an interpolating polynomial, interpolation and extrapolation in two or more dimensions.
- Equation Solver Module: Interval Method, Secant Method, Brent's Algorithm, Ridders' Method, Method of Regular Falsi, Method of Regula Falsi, Newton-Raphson Method, Fail-Safe Newton-Raphson Method.

 Built for Java Library

## WebCab JGraph

Home Page

Categories: Charting, Graphics,

Graphing and charting component.

Features include:
- Graph component: Several interpolation methods can be used (e.g. cubic spline, linear interpolation); Multiple series; JDBC compliant; Zooming; Scaling; Centering; Saving as JPEG; Anti-aliasing; Dragging.
- Chart component: Several types of bar charts are available (e.g. bar and pie); Multiple series; JDBC compliant; Anti-aliasing; Light effect; Transparency; Shadows; Saving as JPEG; Rotation.
- Pie component
- Pictogram component

 Built for Java Library

## WebCab Optimization

Home Page

Categories: Math - Logic - AI - Rules - Science

Procedures for solving and performing sensitivity analysis on uni and multi-dimensional, local or global optimization problems which may or may not have linear constraints. Specialized Linear programming algorithms based on the Simplex Algorithm and duality are included along with a framework for sensitivity analysis w.r.t. boundaries (duality, or direct approach), or object function coefficients.

Features include:
- local unidimensional optimization: fast "low level" algorithms (where the weight is on speed and not the accuracy of the results); bracketing algorithm (find an interval where at least one extrema of a continuous function exists); locate algorithms (converge to the extrema if the extrema is bracketed and the function under consideration is continuous); accurate "high level" algorithms;
- global unidimensional optimization: finds global minima/maxima;
- unconstrained local multidimensional optimization;
- unconstrained global multidimensional optimization;
- constrained optimization for derivable functions with linear constraints;
- linear programming: here the functions are linear and the constraints are linear;
- sensitivity analysis: stability of the value and location of the extremum.

 Built for Java Library

## WebCab Options and Futures

Home Page

Categories: Miscellaneous

Prices a broad range of option and futures contracts using a range of price/vol/interest rate models. Includes in addition to the general pricing framework a detailed Black-Scholes-Merton Model API (including Greeks and implied volatility) for European, Asian, American, Lookback, Bermuda and Binary Options using Analytic, Monte Carlo and Finite Difference techniques. Also offers an implementation of a binomial and trinomial trees based pricing engine for the evaluation of employee options in accordance within the Enhanced FASB 123 model and a module allowing the evaluation of the Value-at-Risk (VaR) of an investment portfolio in accordance with the Linear model.

 Built for Java Library

## WebCab Portfolio

Home Page

Categories: Miscellaneous

Apply the 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; or with respect to CAPM by given the risk, return or Market Portfolio weighting. Also includes Performance Evaluation, extensive auxiliary classes/methods including equation solve and interpolation procedures, analysis of Efficient Frontier, Market Portfolio and CML.

 Built for Java Library

## WebCab Probability and Statistics

Home Page

Categories: Math - Logic - AI - Rules - Science

Offers functionality for Basic Statistics, Discrete Probability, Standard Probability Distributions, Hypothesis Testing, Correlation and Linear Regression.

Includes:
- Statistics Module: Incorporates evaluation procedures of standard quantitative measures of centrality (mean) and dispersion of (discrete) numerical sets. This module incorporates weighted averages, geometric mean, Inter-Quartile range, mean and standard deviation, sample variance and the coefficient of variation.
- Discrete Probability Module: Encapsulates the foundations of discrete probability and discrete probability distributions. This component includes the addition law, conditional probability, cumulative distribution function, mean and variance of a distribution, expected values, covariance and simplification of expressions involving random variables.
- Correlation and Regression Module: Allows the user to investigate relationships between two variables. These finding can be used to predict one variable from the given values of other variables. It covers linear (Spearman's, t-test, z-transform) and rank (Spearman's, Kendall's) correlation, linear regression and conditional means.
- Standard Probability Distributions Module: Assists in the development of applications that incorporate the Binomial, Poisson, Normal, Lognormal, Pareto, Uniform, Hypergeometric and Exponential probability distributions. The probability density function, cumulative distribution function and inverse, mean, variance, Skewness and Kurtosis are implemented where appropriate and/or their approximations for each distribution. It also offers methods that randomly generate numbers from a given distribution.
- Confidence Intervals and Hypothesis Testing Module: Presents two aspects of inferential statistics known as confidence intervals and hypothesis testing.

 Built for Java Library

## WebCab Technical Analysis

Home Page

Categories: Miscellaneous

Provides a collection of technical indicators that can be used in the construction of technical trading systems. Moreover, by using these methods with the built-in database mediator technology you will be able to iteratively apply these indicators to historical data stored within a DBMS.

Features include:
- Technical indicators
- Single and multi-period indicators