Purpose This paper aims to empirically investigate the volatility of Bitcoin, Litecoin and the Euro. Design/methodology/approach The authors use quantitative methodologies to assess the annualized volatility of two cryptocurrencies and one international fiat currency. The exchange rate of the currencies is monitored on a daily basis using 1,460 observations from January 1, 2014 to December 31, 2017. The models used include the augmented Dickey–Fuller test, Akaike Information Criteria, autocorrelation function and exchange rate changes determining which currency is the most volatile. Findings The findings indicate, based on the statistical measures used, including the standard deviation of selected currencies and annualized volatility, that Litecoin is more volatile than Bitcoin and the Euro and that Bitcoin is more volatile than the Euro. This furthers previous research on cryptocurrency volatility. Originality/value The paper provides compelling evidence about the volatility of Litecoin and Bitcoin. The volatility of cryptocurrencies is furthered with data that are more current. The findings are important for investors, financial markets and central banks.
Decision-making about capital structure is one of the basic decisions in each company, and therefore its analysis is the subject of this article. The importance of this theme corresponds to countless literature. This article aims to assess the impact of four determinants, selected by a review of earlier studies, on the choice of funding sources. The examined sample contains the energy companies of the Visegrád Group during the period 2009-2017. The data was obtained from Orbis and Eurostat database. The main research methods are correlation analyses and Generalized Method of Moments that are performed using EViews. The debt-equity ratio is used as the dependent variable. The independent variables are the growth rate of GDP, profitability, asset structure, and liquidity. For all countries, the influence of profitability on indebtedness was found. For Hungary, this relationship was negative, for remaining countries positive.
This research builds on previous studies in the field of financial structure and develops knowledge for the construction industry in eight selected countries in Central and Eastern Europe – Visegrád Group, Austria, Bulgaria, Slovenia, and Romania. The aim of the research is to examine the influence of profitability, asset structure, the GDP growth rate and the reference interest rate on the level of total, long-term and short-term debt of companies. The research period is from 2009 to 2018. The main conclusion of the research is the finding that the amount of debt of selected construction companies is most affected by the determinants of the external environment – the development of the economy and the reference interest rate. This conclusion applies regardless of the size of the companies. The direction of the resulting impact differs, as each of the economies underwent a different economic development during the period under review. The interest rate negatively affected the amount of debt of Polish, Romanian and Hungarian companies, given the higher interest rates in these economies; the remaining companies have a positive impact. The impact of the GDP growth rate on the amount of debt is mainly negative for Romanian companies regardless of size, medium-sized Polish and Austrian companies, and large Czech companies; a positive effect was found for the remaining companies. Economies have grown for most of the period under review, and negative impacts may mean taking advantage of profits, which usually grow during periods of prosperity and are a cheap source of funding. This does not necessarily mean economic problems and, as a result, declining debt due to the unavailability of debt financing.
Analyzing and deciding on capital structure is one of the core activities of any company, as evidenced by the vast amount of research. Each sector is characterized by a different capital structure. This article deals with the impact of profitability, non-debt tax shield, GDP growth rate, and inflation rate on the overall, long-term, and short-term debt of medium and large civil engineering companies. The analysis is carried out for the period 2009–2018 on eleven selected economies, including the extended Visegrád Group and Estonia, Lithuania, and Latvia. The input data is obtained from the Orbis database and the World Bank database. Panel regression using the Generalized Method of Moment is used to analyze the influence of selected determinants on debt.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.