2014/07/18 by Paweł Fiedor, Fiedor, Paweł
Decision Sciences · Economics, Econometrics and Finance · Physics and Astronomy · #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Computational Finance (q-fin.CP) #FOS: Economics and business #Innovation Diffusion and Forecasting #Statistical Finance (q-fin.ST)
paper · pdf · doi:10.48550/arxiv.1407.5020
openalex publication_date 2014/07/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In our previous study we have presented an approach to studying lead--lag effect in financial markets using information and network theories. Methodology presented there, as well as previous studies using Pearson's correlation for the same purpose, approached the concept of lead--lag effect in a naive way. In this paper we further investigate the lead--lag effect in financial markets, this time treating them as causal effects. To incorporate causality in a manner consistent with our previous study, that is including non-linear interdependencies, we base this study on a generalisation of Granger causality in the form of transfer entropy, or equivalently a special case of conditional (partial) mutual information. This way we are able to produce networks of stocks, where directed links represent causal relationships for a specific time lag. We apply this procedure to stocks belonging to the NYSE 100 index for various time lags, to investigate the short-term causality on this market, and to comment on the resulting Bonferroni networks.