| Abstract: |
| The paper aims to explore the heterogeneous feature in the determination of Bitcoin volatility using a Markov regime-switching model and test its forecasting ability. The forecasting methodology of the risk measurement of Bitcoin`s returns is based on the Conditional Autoregressive Value at Risk models (CAViaR) approach. Our results show that Bitcoin`s volatility is significantly related to the volatility of the crypto-assets` return and the main determinants of volatility are speculation, investor attention, market interoperability and the interaction between speculation and market interoperability. In addition, we present evidence that investors` attention is the main source of volatility. Speculation and the interaction term are related in a U-shaped form, whereas investor attention and market interoperability show a linear trend on the volatility of Bitcoin |
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