tech.nmfin.algoquant.demo.model.portfoliooptimization

Class PortfolioOptimizationBacktestDemo

java.lang.Object

tech.nmfin.algoquant.demo.model.portfoliooptimization.PortfolioOptimizationBacktestDemo

public class PortfolioOptimizationBacktestDemo
extends Object

Backtests a particular optimizer to see its performance over time using historical data.

Using this example. Evaluates a portfolio optimizer over historical windows rather than computing one static allocation. Read the configured estimation, rebalancing and simulation periods together. Training inputs must be available before the corresponding rebalance decision.

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

Implementation in this tutorial. A rolling backtest separates estimated weights from realized returns after rebalancing. Follow the data-window and rebalance callbacks to see when each estimate is available. Transaction and turnover conventions belong to the simulation, not the static mean–variance equations.

See Also:

H. Markowitz (1952), Portfolio Selection, Journal of Finance 7(1), 77–91

Constructor Summary

Constructors

Constructor and Description
PortfolioOptimizationBacktestDemo()

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

PortfolioOptimizationBacktestDemo

public PortfolioOptimizationBacktestDemo()

Method Detail

main

public static void main(String[] args)