Bitcoin and cryptocurrency have been hot topics these years due to the rapid growth of the market value. Due to the lack of regulation, the market of cryptocurrency is very volatile and risky for investors. This project aims to construct a systematic way to predict the volatility of the Bitcoin market through the microstructure of the market. The data source is a highfrequency orderbook, which is a snapshot of all the orders listed on the exchange, and they’re collected from Tardis, a major cryptocurrency data collector. Various machine learning models and features will be investigated and their performance will be evaluated by different metrics as well.
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