We provide a trend prediction classification framework named the random sampling method (RSM) for cryptocurrency time series that are non-stationary. This framework is based on deep learning (DL). We compare the performance of our approach to two classical baseline methods in the case of the...

Trader behavior in FX market -- The effects of information reliability on financial market -- Property price distributions of Taiwan and the UK -- Phase transition in estimation of parameters of low default portfolio -- A Cryptocurrency Fraud Spill in Japan -- Idiosyncratic volatility of the...