The Blockchain technology and a comparison between classical statistical models and machine learning methods for time series analysis

This thesis wants to put together the area of computer science and statistics. For the IT side, the mechanisms of the blockchain technology and classical concept of computer science necessary for understanding it will be outlined. On the other hand, the quantitative part will present the state of the art of machine learning algorithms. The work will end with an empirical chapter where machine learning methods will be compared to classical statistical models. The comparison metric will be the forecasting error of the conditional mean and the conditional variance of timeseries belonging to the cryptocurrency world.