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Erschienen in: Decisions in Economics and Finance 1/2020

26.07.2019

Market attention and Bitcoin price modeling: theory, estimation and option pricing

Erschienen in: Decisions in Economics and Finance | Ausgabe 1/2020

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Abstract

The goal of this paper is to provide a novel quantitative framework to describe the Bitcoin price behavior, estimate model parameters and study the pricing problem for Bitcoin derivatives. To this end, we propose a continuous time model for Bitcoin price motivated by the findings in recent literature on Bitcoin, showing that price changes are affected by sentiment and attention of investors, see e.g., (Kristoufek in Sci Rep 3:3415, 2013, PLoS ONE 10(4):e0123923, 2015; Bukovina and Marticek in Sentiment and bitcoin volatility. Technical report, Mendel University in Brno, Faculty of Business and Economics 2016). Economic studies, such as Yermack (Handbook of Digital Currency, chapter second. Elsevier, Amsterdam, pp 31–43, 2015), have also classified Bitcoin as a speculative asset rather than a currency due to its high volatility. Building on these outcomes, the price dynamics in our suggestion is indeed affected by an exogenous factor which represents market attention in the Bitcoin system. We prove the model to be arbitrage-free under a mild condition and we fit the model to historical data for the Bitcoin price; after obtaining a approximate formula for the likelihood, parameter values are estimated by means of the profile likelihood method. In addition, we derive a closed pricing formula for European-style derivatives on Bitcoin, the performance of which is assessed on a panel of market prices for Plain Vanilla options quoted on www.​deribit.​com.
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Fußnoten
1
This Web site collects data on sentiment through an algorithm, based on Natural Language Processing techniques, which is capable of identifying string of words conveying positive, neutral or negative sentiment on a topic (Bitcoin in this case).
 
2
It is well documented that Google is the most popular search engine.
 
3
Data available only from 01/07/2015.
 
4
The function \(\varphi \) is usually referred to as the contract function.
 
5
We thank an anonymous referee for this suggestion.
 
6
The Root Mean Squared Error is computed as the square root of the sum, across all options in the sample or subsample, of the squared differences between model and market prices.
 
7
We thank an anonymous referee for pointing this.
 
8
With the exception of Futures, traded on both the CBOE and CME, which are not suited for calibration.
 
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Metadaten
Titel
Market attention and Bitcoin price modeling: theory, estimation and option pricing
Publikationsdatum
26.07.2019
Erschienen in
Decisions in Economics and Finance / Ausgabe 1/2020
Print ISSN: 1593-8883
Elektronische ISSN: 1129-6569
DOI
https://doi.org/10.1007/s10203-019-00262-x

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