Publication Date:
2018
abstract:
In this paper we study the high frequency dynamic of financial volumes of traded stocks by using a semi-Markov approach. More precisely we assume that the intraday logarithmic change of volume is described by a weighted-indexed semi-Markov chain model. Based on this assumptions we show that this model is able to reproduce several empirical facts about volume evolution like time series dependence, intra-daily periodicity and volume asymmetry. Results have been obtained from a real data application to high frequency data from the Italian stock market from first of January 2007 until end of December 2010. © 2018, Springer Nature Switzerland AG.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
Keywords:
Financial volume High frequency data Semi-Markov process
List of contributors:
D'Amico, Guglielmo; Gismondi, Fulvio; Petroni, Filippo
Book title:
Stochastic Processes and Applications
Published in: