Corpus ID: 202589661

Pricing Cryptocurrency options: the case of CRIX and Bitcoin

@inproceedings{Chen2018PricingCO,
  title={Pricing Cryptocurrency options: the case of CRIX and Bitcoin},
  author={Cathy Y. H. Chen and Wolfgang Karl H{\"a}rdle and Ai Jun Hou and Weining Wang and Cathy Y. H. Chen},
  year={2018}
}
Cryptocurrencies, especially Bitcoin (BTC), which comprise a new revolutionary asset class, have drawn extraordinary worldwide attention. The characteristics of the cryptocurrency/BTC include a high level of speculation, extreme volatility and price discontinuity. In this paper, we propose a pricing mechanism based on a stochastic volatility with correlated jump (SVCJ) model and compare it to a flexible co-jump model by Bandi and Renò (2016) allowing for non-affine structure. The calibration… Expand
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References

SHOWING 1-10 OF 79 REFERENCES
Testing for Bubbles in Cryptocurrencies with Time-Varying Volatility
  • C. Hafner
  • Journal of Financial Econometrics
  • 2018
The recent evolution of cryptocurrencies has been characterized by bubble-like behavior and extreme volatility. While it is difficult to assess an intrinsic value to a specific cryptocurrency, oneExpand
CRIX an Index for cryptocurrencies
The cryptocurrency market is unique on many levels: Very volatile, frequently changing market structure, emerging and vanishing of cryptocurrencies on a daily level. Following its development becameExpand
Sentiment-Induced Bubbles in the Cryptocurrency Market
Cryptocurrencies lack clear measures of fundamental values and are often associated with speculative bubbles. This paper introduces a new way of testing for speculative bubbles based on StockTwitsExpand
Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis
We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk inExpand
Herding behavior and contagion in the cryptocurrency market
Abstract This study aimed to analyze herding behavior and contagion phenomena in the cryptocurrency market. We selected 50 of the most liquid and capitalized currencies in the period from March 2015Expand
IS BITCOIN BUSINESS INCOME OR SPECULATIVE FOOLERY? NEW IDEAS THROUGH AN IMPROVED FREQUENCY DOMAIN ANALYSIS
The present study addresses one of the most problematic phenomena: Bitcoin price. We explore the Granger causality for two relationships (Bitcoin price and trade transactions; Bitcoin price andExpand
A Statistical Analysis of Cryptocurrencies
We analyze statistical properties of the largest cryptocurrencies (determined by market capitalization), of which Bitcoin is the most prominent example. We characterize their exchange rates versusExpand
CRIX or Evaluating Blockchain Based Currencies
The S&P500 or DAX30 are important benchmarks for the financial industry. These and other indices describe different compositions of certain segments of the financial markets. For currency markets,Expand
What drives Bitcoin price
The cryptocurrencies increased in popularity and have become nowadays well known to a wide audience. This article seeks to assess the issue of Bitcoin price formation from a novel perspective. We useExpand
Predicting crypto-currencies using sparse non-Gaussian state space models
TLDR
A time-varying parameter VAR with t-distributed measurement errors and stochastic volatility is developed that enables us to shrink coefficients associated with irrelevant predictors and/or perform model specification in a flexible manner to control for overparameterization. Expand
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