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The objective of this thesis is to analyze the predictive power of the cryptocurrency limit order book for return predictions. The analysis is performed for the BTC/USD and ETH/USD directional 10-second returns, using limit order book data from three of the largest cryptocurrency spot exchanges. The analysis employs the Random forest algorithm as a classification problem. The results demonstrate t
