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The IMSL Libraries White Papers
Select one or select all for an in-depth view of the IMSL Libraries:
 Neural Networks: An Introduction
This white paper gives a comprehensive overview of Neural Network technology. It describes the fundamental benefits and uses of this technology. Many algorithm techniques, ranging from regression analysis to ARIMA for time series, among others, are regularly used to generate forecasts. A neural network approach provides a forecasting technique that can operate in circumstances where classical techniques cannot perform or do not generate the desired accuracy in a forecast.
Visual Numerics Technology for Neural Network Analysis
This white paper describes Visual Numerics' implementation of Neural Network technology. It goes into technical detail about the algorithms and Neural Network techniques. The Visual Numerics collection of neural network and data pre- and post-processing algorithms, written in 100% Java, provide a highly configurable neural network algorithm approach, and are written in a programming language that facilitates for smooth system integration.
Advanced Forecasting Functionality with IMSL® Auto_ARIMA
An in-depth look at the Auto_ARIMA function and its constituents with an application to financial data.
"Portfolio Optimization using the IMSL Libraries"
The ultimate goal of portfolio optimization is to build a portfolio with the proper proportion of its components that will balance minimum risk and maximum return. One textbook method to that end involves the computation of the efficient frontier curve, which enumerates a set of portfolios that will generate some given rate of return while minimizing risk to the investor. Once that curve is computed, an optimal portfolio can be selected from the set through a graphical method that involves the risk-free rate of return. This document will travel through the discovery of that ideal portfolio by reviewing the necessary inputs, constraints on the solution, the computation and analysis of the efficient frontier, and how to select the optimal solution from the set of possible solutions.
Portfolio Optimization via Efficient Frontier with the IMSL Numerical Libraries
Describes how to build a portfolio with the proper proportion of its components that will balance minimum risk and maximum return.
Visual Numerics Technology for Neural Network Analysis
This white paper describes Visual Numerics' implementation of Neural Network technology. It goes into technical detail about the algorithms and Neural Network techniques. The Visual Numerics collection of neural network and data pre- and post-processing algorithms, written in 100% Java, provide a highly configurable neural network algorithm approach, and are written in a programming language that facilitates for smooth system integration.
Solving Constrained Differential-Algebraic Systems Using Projections
Reports on software additions to the Differential-Algebraic Equation solver code.
Integrating Feynman-Kac Equations Using Hermite Qunitic Finite Equations
Describes methods for solving a generalized version of the Feynman-Kac partial differential equation that can be used in many financial modeling applications, including Black-Scholes models.
For more detailed information on specific features available for each Library, please contact us for a data sheet.
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