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The Athens Stock Exchange (ASE) is a dynamic financial market with complex interactions and inherent volatility. Traditional models often fall short in capturing the intricate dependencies and long memory effects observed in real-world financial data. In this study, we explore the application of fractional Brownian motion (fBm) to model stock price dynamics within the ASE, specifically utilizing the Athens General Composite (ATG) index. The ATG is considered a key barometer of the overall health of the Greek stock market. Investors and analysts monitor the index to gauge investor sentiment, economic trends, and potential investment opportunities in Greek companies. We find that the Hurst exponent falls outside the range typically associated with fractal Brownian motion. This, combined with the established non-normality of increments, disfavors both geometric Brownian motion and fractal Brownian motion models for the ATG index. [ABSTRACT FROM AUTHOR]

This study aims to answer the question about the interactions between "investors' fear", two factors proposed by Fama & French, the Carhart momentum factor, andthe risk premium, and how these interactions were affected by two financial crises, the Dot-Com and Sub-Prime crises. This paper is the first empirical study that considers the effects of these financial crises. It is of critical importance as it changes the specificity of the empirical models for different periods, significantly affecting the results compared to previous research work. The main findings include a general negative change in fear over all of the sub-periods. Secondly, no consistent positive trend was observed in any of the risk premiums over time. After each crisis, the relationships between the endogenous variables had significant changes. More specifically, investors' fear, on the first day of the week, appears to be systematically higher across all sub-periods except during the Sub-Prime crisis. Finally, after the Sub-Prime financial crisis, there is an almost complete loss of the explanatory power of the VAR models. Although fear does not seem to affect risk premiums or momentum, it was nevertheless found that the results are sensitive to the specification of the models. [ABSTRACT FROM AUTHOR]

This paper examines the correlation between three prospective investing options: the Bitcoin cryptocurrency price, gold, and the Dow Jones stock index. The main research question is whether there is a causal effect of gold and the DWJ on Bitcoin and how this effect varies on time. The study begins with a background analysis that explains the definitions and operation of cryptocurrencies, followed by a brief overview of gold and its derivatives. In addition, a historical review of stock markets is provided, with a focus on the Dow Jones index. Then, a literature review follows. Daily data from three separate periods are used, each spanning four years. The first period, running from October 2014 to September 2018, provides an overview of the introduction of official cryptocurrency price data. The second period, running from Oct 2018 to Sept 2022, captures more recent trends preceding COVID-19. The third period, from January 2020 to December 2023, is the whole COVID-19 period with the initiation, embedded, and terminal phases. Classical inductive statistical methods (descriptive, correlations, multiple linear regression) as well as time series analysis methods (autocorrelation, cross-correlation, Granger causality tests, and ARIMA modeling) are used to analyze the data. Rigorous testing for autocorrelation, multicollinearity, and homoskedasticity is performed on the estimated models. The results show a correlation of Bitcoin with gold and the DWJ. This correlation varies over time, as in the first period the correlation mainly concerns the DWJ and in the second it mainly concerns gold. By using ARIMA models, it was possible to make a forecast in a time horizon of a few days. In addition, the structure of the forecasting mechanism of gold and DWJ on Bitcoin seems to have changed during the COVID-19 crisis. The findings suggest that future research should encompass a broader dataset, facilitating comprehensive comparisons and enhancing the reliability of the conclusions drawn. [ABSTRACT FROM AUTHOR]

The effectiveness of the economic policies implemented by a country/region directly affects its economic growth potential. Cultural Heritage Festivals are a sector of the creative economy that, by promoting culture, may have a significant impact on national/regional sustainable economic development. This study assesses the implementation of the Contingent Valuation Method (CVM) and the estimation of the Willingness To Pay (WTP) demand curve, using data collected for the Kalamata Dance Festival as a case study, in order to evaluate creative economy investments. The results obtained indicate that the CVM is an appropriate method for evaluating festivals and suggest that females, spectators with high incomes and high educational levels, and visitors to Kalamata (non-residents) show an increased Willingness To Pay. These findings can be useful to cultural heritage festival organizers in developing appropriate policy strategies: targeting the social groups with the greatest Willingness To Pay; adjusting the pricing mechanism accordingly; modifying annual memberships/donations/sponsorships, indirect resources, and tax revenues and grants; and optimizing investments and allocating resources. Furthermore, the findings of this study will be particularly useful for Greece in designing relevant cultural sustainable development policies for exploiting the potential of the Cultural Heritage Festival, in synergy with the tourism sector, which already contributes a major share to the country's GDP. [ABSTRACT FROM AUTHOR]

A mathematical model based on regression analysis has been developed for bank branch planning. The model uses the stepwise multiple regression technique to evaluate the different factors that could affect the performance of bank branches, such as the branch age, the presence of a night deposit facility and professional and commercial character of the location.

We develop and present a model for pricing GDP-linked bonds that takes into account both GDP fluctuations and fiscal default. The indexation is based on the size of GDP deviations from the trend and default is based on the size of sovereign debt. We consider a mapping of these instruments to normal fixed-income securities, and a bond equivalent yield is calculated as well as a default premium. We construct various indexed bond products with different coupon variations and we price them via Monte-Carlo simulations for the case of Greece. The model can be applied to other countries provided that the data are adjusted. One of the main results is that GDP-linked bonds are more conducive to debt management. In particular, replacing conventional bond instruments with carefully designed GDP-linked bonds of equivalent yield can lead to lower terminal values of debt-to-GDP ratio, provided that the macroeconomic environment is the same. [ABSTRACT FROM AUTHOR]