Fractal Optimization of Market Neutral Portfolio

TL;DR

This paper introduces a fractal-based optimization method for market-neutral portfolios that enhances stability and risk-adjusted returns by analyzing spread returns with Hurst stability and a fractal walk model.

Contribution

It presents a novel fractal approach to portfolio optimization, incorporating Hurst stability analysis and a fractal walk model to improve risk management and performance.

Findings

Portfolio system is statistically more stable than passive benchmarks.

Higher risk-adjusted cumulative returns achieved.

Out-of-sample performance validated over five periods.

Abstract

A fractal approach to the long-short portfolio optimization is proposed. The algorithmic system based on the composition of market-neutral spreads into a single entity was considered. The core of the optimization scheme is a fractal walk model of returns, optimizing a risk aversion according to the investment horizon. The covariance matrix of spread returns has been used for the optimization and modified according to the Hurst stability analysis. Out-of-sample performance data has been represented for the space of exchange traded funds in five period time period of observation. The considered portfolio system has turned out to be statistically more stable than a passive investment into benchmark with higher risk adjusted cumulative return over the observed period.