tech.nmfin.algoquant.demo.model.portfoliooptimization

Class PortfolioOptimizationAlgorithmDemo

java.lang.Object

tech.nmfin.algoquant.demo.model.portfoliooptimization.PortfolioOptimizationAlgorithmDemo

public class PortfolioOptimizationAlgorithmDemo
extends Object

Shows how to compute the asset weights using a portfolio optimization algorithm.

Using this example. Calls getOptimalWeights on a returns matrix, then applies TopNOptimizationAlgorithm and associates the vector with products using PortfolioWeights. Rows are observations and columns are products. The zero initial vector and null optional arguments shown here belong to this optimizer configuration; check the concrete algorithm contract before reusing them.

Model and publication. Related theory and the scope of this example are distinguished below.

Implementation in this tutorial. Builds a composable Lai2010OptimizationAlgorithm with a long-only/shrunk-mean optimizer, Ledoit–Wolf moments and a resampler, then uses getOptimalWeights and a TopN transformation. The selected components and post-processing define an adaptation, not a paper replication.

Author:

Haksun Li

See Also:

T. L. Lai, H. Xing and Z. Chen (2011), Mean–variance portfolio optimization when means and covariances are unknown, Annals of Applied Statistics 5(2A), 798–823

Constructor Summary

Constructors

Constructor and Description
PortfolioOptimizationAlgorithmDemo()

Method Summary

Modifier and Type	Method and Description
static void	main(String[] args)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PortfolioOptimizationAlgorithmDemo

public PortfolioOptimizationAlgorithmDemo()

Method Detail

main

public static void main(String[] args)
                 throws IOException,
                        Exception

Throws:

IOException

Exception