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Bitcoin Option Pricing with Delayed Market Attention

Article arXiv papers · Author: Alvaro Guinea Julia et al.
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Summary

The document presents a Bitcoin pricing model in which market attention affects return volatility after a delay. Attention is represented by a mean-reverting Cox-Ingersoll-Ross process, and the resulting model is affine and tractable. The authors derive closed-form conditional characteristic functions for conventional and delayed information filtrations, which support semi-closed pricing formulas for European calls and puts.

The work also provides a maximum-likelihood estimation procedure and a method for moving from the statistical model to a risk-neutral measure. It reports that the model compares favorably with classical and attention-based alternatives when tested on real data. The excerpt does not specify the dataset, comparison metrics, calibration details, or pricing errors, so the strength and generality of that comparison cannot be assessed from this description alone.

Key ideas

  • Market attention is modeled as a mean-reverting process that influences Bitcoin return volatility with a delay.
  • The affine model yields conditional characteristic functions under conventional and delayed filtrations.
  • These functions lead to semi-closed pricing formulas for European calls and puts.
  • The document describes maximum-likelihood estimation and a change to a risk-neutral measure.
  • Real-data comparisons are reported as favorable, though the excerpt gives no dataset or error measures.

Tags

CryptoOptionsDerivatives pricingVolatilityStatistics
Full text
# Bitcoin option pricing: A market attention approach


# Bitcoin option pricing: A market attention approach









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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.