The fractional volatility model: An agent-based interpretation

TL;DR

This paper introduces a fractional noise volatility model that aligns well with market data and explores agent strategies that could generate such features in financial markets.

Contribution

It presents a fractional volatility model based on empirical data and investigates agent behaviors that could produce this model's characteristics.

Findings

The fractional volatility model accurately fits market data.

Agent strategies can potentially explain the model's features.

The model offers a simple yet consistent representation of market volatility.

Abstract

Based on criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are discussed and, using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.