Volatility Harvesting: Extracting Return from Randomness

TL;DR

This paper explores how excess volatility in financial returns, modeled through binomial and Gaussian processes, can be exploited to generate growth, validated with real-world data and risk analysis.

Contribution

It introduces a novel approach called volatility harvesting, demonstrating how excess volatility can be systematically traded for returns in financial markets.

Findings

Excess volatility can be exploited for growth.

Model phenomena are confirmed with real-world data.

Implicit risks in volatility trading are highlighted.

Abstract

Studying Binomial and Gaussian return dynamics in discrete time, we show how excess volatility can be traded to create growth. We test our results on real world data to confirm the observed model phenomena while also highlighting implicit risks.