Greedy Online Classification of Persistent Market States Using Realized Intraday Volatility Features
In many financial applications, it is important to classify time-series data without any latency while maintaining persistence in the identified states. The authors propose a greedy online classifier that contemporaneously determines which hidden state a new observation belongs to without the need to parse historical observations and without compromising persistence. Their classifier is based on tIn many financial applications, it is important to classify time-series data without any latency while maintaining persistence in the identified states. The authors propose a greedy online classifier that contemporaneously determines which hidden state a new observation belongs to without the need to parse historical observations and without compromising persistence. Their classifier is based on t