Discovering causal relations and equations from data
Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …
questions about why natural phenomena occur and to make testable models that explain the …
A review of two decades of correlations, hierarchies, networks and clustering in financial markets
We review the state of the art of clustering financial time series and the study of their
correlations alongside other interaction networks. The aim of the review is to gather in one …
correlations alongside other interaction networks. The aim of the review is to gather in one …
Network filtering for big data: Triangulated maximally filtered graph
We propose a network-filtering method, the Triangulated Maximally Filtered Graph (TMFG),
that provides an approximate solution to the Weighted Maximal Planar Graph problem. The …
that provides an approximate solution to the Weighted Maximal Planar Graph problem. The …
Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment
The paper examines how various COVID-19 news sentiments differentially impact the
behaviour of cryptocurrency returns. We used a nonlinear technique of transfer entropy to …
behaviour of cryptocurrency returns. We used a nonlinear technique of transfer entropy to …
Energy markets–Who are the influencers?
The energy markets have recently undergone important transformations (eg deregulation,
technological progress, renewable energy deployment and changing energy consumer …
technological progress, renewable energy deployment and changing energy consumer …
A survey of the application of graph-based approaches in stock market analysis and prediction
Graph-based approaches are revolutionizing the analysis of different real-life systems, and
the stock market is no exception. Individual stocks and stock market indices are connected …
the stock market is no exception. Individual stocks and stock market indices are connected …
Development of stock correlation networks using mutual information and financial big data
X Guo, H Zhang, T Tian - PloS one, 2018 - journals.plos.org
Stock correlation networks use stock price data to explore the relationship between different
stocks listed in the stock market. Currently this relationship is dominantly measured by the …
stocks listed in the stock market. Currently this relationship is dominantly measured by the …
On financial market correlation structures and diversification benefits across and within equity sectors
We study how to assess the potential benefit of diversifying an equity portfolio by investing
within and across equity sectors. We analyse 20 years of US stock price data, which …
within and across equity sectors. We analyse 20 years of US stock price data, which …
Relation between financial market structure and the real economy: comparison between clustering methods
We quantify the amount of information filtered by different hierarchical clustering methods on
correlations between stock returns comparing the clustering structure with the underlying …
correlations between stock returns comparing the clustering structure with the underlying …
Experimental econophysics: Complexity, self-organization, and emergent properties
JP Huang - Physics Reports, 2015 - Elsevier
Experimental econophysics is concerned with statistical physics of humans in the laboratory,
and it is based on controlled human experiments developed by physicists to study some …
and it is based on controlled human experiments developed by physicists to study some …