Purpose: The COVID-19 crisis has brought to the forefront the importance of rural health enterprises (RHEs), the peculiarity, in these terms, of rural areas, and the impact of rurality on health entrepreneurial activities. This paper aims to undertake a literature review regarding RHEs in the...

Purpose: Motivated by the ongoing debate on the existence and magnitude of herding in financial markets, the purpose of this paper is to examine Eurozone stock markets for herding behavior. In the context of the present study, the authors seek for herding behavior of stock markets as a whole as...

Purpose: The purpose of this paper is to examine the value-at-risk and related measures for the Bitcoin and to compare the findings with Standard and Poor’s SP500 Index, and the gold spot price time series. Design/methodology/approach: A GJR-GARCH model has been implemented, in which the...

Many surveys analyse the volatility of stock market indexes, omitting the role of individual stocks in that phenomenon. In the present study, we focus on that part of the market, using financial and market data from listed firms in the Athens Stock Exchange (ASE) index in several crashes, during...

We elaborate on a new distributional scheme resulting from the generalised Pearson distribution with application to financial modelling. As case studies, we consider the major historical indices daily returns, DJIA, NASDAQ composite, FTSE100, CAC40, DAX and S%P500, as well as, high-frequency...

We examine the high frequency dynamics of euro to Japanese yen foreign currency exchange rates for the period of January 2001 to January 2010, comprising approximately three million data entries. The probability density function is described competently by the Tsallis q-Gaussian statistics,...

We examine the value-at-risk where the volatility and returns are modelled via a typical GARCH(1,1) model and the innovations process is the Pearson type-IV distribution. As case studies, we examine the NASDAQ and FTSE100 indices from 12-Dec-1984 to 21-Dec-2000. The model is fitted to the data...

This work examines an artificial neural system (ANS) capable of dimensionality-reduction and its fitness to a business data analysis problem. While ANSs are often used in the later stages of explorative data analysis to place similar cases in clusters or to identify known patterns, the role of...