Portfolio Optimisation via the Heston Model Calibrated to Real Asset Data

TL;DR

This paper investigates how the optimal investment strategy (active or passive) varies with market conditions, modeled through the Heston model calibrated to real stock data, and tests this approach on major indices.

Contribution

It introduces a method to determine optimal investment strategies based on Heston model parameters calibrated to actual market data, highlighting the dependence on market conditions.

Findings

Passive strategies outperform active ones in certain market conditions.

Active strategies are preferable in different market regimes.

The approach is validated on S&P 500, DAX, and WIG20 indices.

Abstract

The debate between active and passive investment strategies has been ongoing for many years and is far from being over. In this paper, we show that the choice of an optimal portfolio management strategy depends on an investment climate, which we measure via the parameters of the Heston model calibrated to the real stock market data. Depending on the values of those parameters, the passive strategy may namely outperform the active ones or vice versa. The method is tested on three stock market indices: S\&P500, DAX and WIG20.