VCRIX - A Volatility Index for Crypto-Currencies

29 Pages Posted: 13 Nov 2019

See all articles by Alisa Kim

Alisa Kim

Humboldt University of Berlin

Simon Trimborn

National University of Singapore (NUS) - Department of Mathematics

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Date Written: November 4, 2019

Abstract

Public interest, explosive returns, and diversification opportunities gave stimulus to the adoption of traditional financial tools to crypto-currencies. While the CRIX index offered the first scientifically-backed proxy to the cryptomarket (analogous to S&P 500), the introduction of Bitcoin futures by Cboe became the milestone in the creation of the derivatives market for cryptocurrencies. Following the intuition of the "fear index" VIX for the American stock market, the VCRIX volatility index was created to capture the investor expectations about the crypto-currency ecosystem. VCRIX is built based on CRIX and offers a forecast for the mean annualized volatility of the next 30 days, re-estimated daily. The model was back-tested for its forecasting power, resulting in low MSE performance and further examined by the simulation of VIX (resulting in a correlation of 78% between the actual VIX and VIX estimated with the VCRIX model). VCRIX provides forecasting functionality and serves as a proxy for the investors’ expectations in the absence of the developed derivatives market. These features provide enhanced decision making capacities for market monitoring, trading strategies, and potentially option pricing.

Keywords: index construction, volatility, crypto-currency, VCRIX

JEL Classification: C51, C52, C53, G10

Suggested Citation

Kim, Alisa and Trimborn, Simon and Härdle, Wolfgang K., VCRIX - A Volatility Index for Crypto-Currencies (November 4, 2019). Available at SSRN: https://ssrn.com/abstract=3480348 or http://dx.doi.org/10.2139/ssrn.3480348

Alisa Kim

Humboldt University of Berlin ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Simon Trimborn (Contact Author)

National University of Singapore (NUS) - Department of Mathematics ( email )

Department of Mathematics
Singapore, 117543
Singapore

Wolfgang K. Härdle

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

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