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 …

This paper uses threshold GARCH (TGARCH) and generalised forecast error variance
decomposition to compute time domain and frequency domain volatility spillover. The …

Smoothing time series allows removing noise. Moving averages are used in finance to
smooth stock price series and forecast trend direction. We propose optimised custom …

Analyzing social systems, particularly financial markets, using a complex network approach
has become one of the most popular fields within econophysics. A similar trend is currently …

The difficulty for startups to secure financing is an important issue in relation to the economic
progress of developing countries. As the main financing channel for startups, informal …

We investigate the impact of climate policy uncertainty shocks on stock market stability in
both developed and emerging G20 economies. Using the network connectedness …

A popular method for network analysis of financial markets is a notable part of econophysics
research. The networks created in such efforts are focused exclusively on linear correlations …

Researchers in finance, managers, and people interested in the stock market observe that
stock prices generally move together. Financial analysts and academic researchers use …

In financial markets, the relation between fluctuations of stock prices and trading behaviors
is complex. It is intriguing to quantify this kind of meta-correlation between market …

This study explores the differential impacts of climate policy uncertainty on stock market
stability in G20 developed and emerging countries. It also identifies key risk transmission …