Bitcoin option pricing: A market attention approach

TL;DR

This paper introduces a novel Bitcoin option pricing model incorporating market attention, modeled via mean-reverting processes, which influences volatility and improves pricing accuracy over classical models.

Contribution

It presents an affine, tractable model with closed-form characteristic functions that accounts for market attention effects in Bitcoin prices, including a risk-neutral measure change.

Findings

Model outperforms classical approaches on real data

Provides semi-closed form European option prices

Incorporates delayed market attention effects

Abstract

A model is proposed for Bitcoin prices that takes into account market attention. Market attention, modeled by a mean-reverting Cox-Ingersoll-Ross processes, affects the volatility of Bitcoin returns, with some delay. The model is affine and tractable, with closed formulae for the conditional characteristic functions with respect to both the conventional and a delayed filtration. This leads to semi-closed formulae for European call and put prices. A maximum likelihood estimation procedure is provided, as well as a method for changing to a risk-neutral measure. The model compares very well against classical and attention-based models when tested on real data.