Mutual information based stock networks and portfolio selection for intraday traders using high frequency data: An Indian market case study.

ABSTRACT: In this paper, we explore the problem of establishing a network among the stocks of a market at high frequency level and give an application to program trading. Our work uses high frequency data from the National Stock Exchange, India, for the year 2014. To begin, we analyse the spectrum of the correlation matrix to establish the presence of linear relations amongst the stock returns. A comparison of correlations with pairwise mutual information shows the further existence of non-linear relations which are not captured by correlation. We also see that the non-linear relations are more pronounced at the high frequency level in comparison to the daily returns used in earlier work. We provide two applications of this approach. First, we construct minimal spanning trees for the stock network b

SUBMITTER: Sharma C 

PROVIDER: S-EPMC6715228 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature