Superposition of COGARCH processes

TL;DR

This paper introduces three superpositions of COGARCH volatility models driven by Lévy processes, analyzing their properties, jump behaviors, and tail distributions, with implications for more flexible financial modeling.

Contribution

It proposes novel supCOGARCH models that extend COGARCH by allowing more flexible autocovariance structures and complex jump relationships.

Findings

SupCOGARCH models exhibit Pareto-like tails.

They allow more flexible autocovariance structures.

Not all volatility jumps lead to price jumps, and vice versa.

Abstract

We suggest three superpositions of COGARCH (supCOGARCH) volatility processes driven by L\'evy processes or L\'evy bases. We investigate second-order properties, jump behaviour, and prove that they exhibit Pareto-like tails. Corresponding price processes are defined and studied. We find that the supCOGARCH models allow for more flexible autocovariance structures than the COGARCH. Moreover, other than most financial volatility models, the supCOGARCH processes do not exhibit a deterministic relationship between price and volatility jumps. Furthermore, in one supCOGARCH model not all volatility jumps entail a price jump, while in another supCOGARCH model not all price jumps necessarily lead to volatility jumps.