An increasing number of applications require to recognize the class an incoming time series as quickly possible without unduly compromising accuracy prediction. In this paper, we put forward a new optimization criterion which takes into account both cost misclassification and delaying decision. Based on criterion, derived family non-myopic algorithms try anticipate expected future gain in infor...

Autoregressive models are reviewed for the analysis of multivariate count time series. A particular topic interest which is discussed in detail that choice a suitable distribution vectors random variables. The focus on three main approaches taken series analysis: (a) integer autoregressive processes, (b) parameter-driven and (c) observation-driven models. aim to highlight some recent methodolog...

This study examines intraday time series momentum in Bitcoin. Unlike stock markets, Bitcoin trades 24 h a day and therefore has not got clear opening closing period. Therefore, we use trading volume as proxy for the market show that first half-hour positively predicts last return. We find sessions with highest or volatility are associated greatest predictability momentum. also momentum-based yi...