Abstract
Public interest, explosive returns, and diversification opportunities gave stimulus to the adoption of traditional financial tools to crypto-currencies. While the CRIX offered the first scientifically-backed proxy to the crypto-market (analogous to S&P 500), measuring the forward-oriented risk in the crypto-currency market posed a challenge of a different kind. Following the intuition of the fear 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 based on the Heterogeneous Auto-Regressive (HAR) model. The HAR model was selected as the most suitable out of a horse race of volatility models, with two proxies for implied volatility, namely the 30 days mean annualized volatility and realized volatility. The model was further examined by the simulation of (resulting in a correlation of 78% between the actual and a VIX version estimated with the VCRIX technology). Trading strategies confirmed the predictive power of VCRIX and supported the selection of the 30 days means annualized volatility proxy. The best performing trading strategy with the use of VCRIX outperformed the benchmark strategy for 99.8% of the tested period and 164% additional returns. VCRIX provides forecasting functionality and serves as a proxy for the investors' expectations in the absence of a developed crypto derivatives market. These features provide enhanced decision making capacities for market monitoring, trading strategies, and potentially option pricing.
Highlights
Since the inception of Bitcoin (BTC) in 2008 the crypto-currency (CC) ecosystem has seen a market capitalization explosion that reached 795 billion USD at its highest point on January 6, 2018 (CoinMarketCap (2018))
Our research aims to create a VCRIX - a volatility index especially designed for markets akin to the CC ecosystem, see Subsection 3.1
BTC futures were not considered for this research due to several reasons: officially listed (Cboe and CME Group) futures do not provide insight into implied volatility of the underlying like option prices do by design, existing data for options is so far only available for BTC from commercial providers like Deribit (2019), not for the broader CC market
Summary
Since the inception of Bitcoin (BTC) in 2008 the crypto-currency (CC) ecosystem has seen a market capitalization explosion that reached 795 billion USD at its highest point on January 6, 2018 (CoinMarketCap (2018)). The rapid growth of BTC price led to persistent talks about "bubble-like" behavior and general skepticism of the market (Hafner (2018), Cheung et al (2015)), exposing the need for a deeper understanding of the underlying processes driving the valuation of CC Research in this field was done by Hayes (2017) and White (2015). Given the absence of a developed derivatives market, we have to infer the characteristics of the implied volatility from the CC market behavior The specifics of the latter (high volatility and low liquidity) triggered the development of new investment methods, see Trimborn et al (2019), further justifying the need for a volatility index, that would capture the unique specifics of CC as an asset class and provide a reliable indicator for the continuously unstable market. VIX is acknowledged by the established CC players as a standard for the implied volatility modeling: in 2019 one of the biggest CC derivative trading platforms Ledger X - a US company regulated by CFTC (United States Commodity Futures Trading Commission) - introduced an implied volatility index for BTC called LXVX (Cointelegraph (2019)), announcing its inheritance to VIX (LXVX (2019))
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