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PL
W tym artykule została przedstawiona dyskusja hipotezy Brody sformułowanej w 1997 roku, a dotyczącej szybkości zbieżności do stanu równowagi (proporcji produkcji wyznaczonych przez wektor własny Frobeniusa) dużych systemów input-output lub systemów von Neumanna w zależności od ich wymiarów. Brody napisał, iż im większa macierz nakładów A, to znaczy im więcej zawiera ona elementów (sektorów i branż) tym szybciej system, w którym występuje ta macierz jest zbieżny do stanu równowagi. Od tego czasu toczy się dyskusja nad matematycznymi aspektami tej hipotezy. W tym artykule został zamieszczony przegląd prac nawiązujących do rozważanej hipotezy. Część z nich dostarcza dowodów na prawdziwość hipotezy, część zaś dowodzi, że hipoteza na ogół nie jest prawdziwa. W artykule zostały wyróżnione dwa kierunki badań stochastyczny i deterministyczny. Tylko przy bardzo wyszukanych założeniach odnośnie losowości macierzy A zachodzi hipoteza Brody. Jednakowoż w ogólnym przypadku, jak pokazaliśmy w tym artykule, hipoteza Brody nie jest prawdziwa. Jest to wniosek z obliczeń dla różnych agregacji (16, 30 i 59) wykonanych dla całej Unii Europejskiej, strefy Euro i poszczególnych krajów członkowskich. Zwiększenie stopnia agregacji nie spowodowało na ogół wzrostu stosunku drugiej do pierwszej wartości własnej macierzy A. Najmniejszy stosunek obu wartości własnych miał miejsce w przypadku całej Unii Europejskiej, potem strefy Euro i dalej poszczególnych państw. Stąd wysnuto wniosek, że szybkość zbieżności danej gospodarki do stanu równowagi nie zależy od liczby wyróżnionych w niej sektorów, lecz od jej wielkości i być może stopnia współzależności tych sektorów (duże gospodarki szybciej zmierzają do stanu równowagi niż mniejsze gospodarki).
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This paper presents discussion about the importance of degree of aggregation in input-output systems for speed of convergence to the equilibrium. The basis is the hypothesis stated by Brody (1997) that the greater the dimension of flow coefficients matrix A is, the faster the economy convergences to the equilibrium because the ratio between modulus of the subdominant and dominant eigenvalue declines to zero. Since then, several papers have been published to verify mathematical aspects of the hypothesis. The development of random matrices theory provided theorems that confirm the hypothesis in the case of i.i.d. elements of flow coefficients matrix.. However, in the case of deterministic input-output table, there were constructed counterexamples where the ratio between subdominant and dominant eigenvalue does not decline when the size of the matrix increases to infinity and the degree of aggregation does not influence the speed of convergence to the equilibrium. This paper verifies how the hypothesis fits to empirical data. Analysis of different aggregation of input-output tables for European Union, Euro zone and several European countries shows that increasing the number of branches in IO table does not reduce the ratio of modulus of subdominant and dominant eigenvalues of the flow coefficients matrix A. Hence, the speed of convergence to the equilibrium does not depend on the number of sectors in IO table but rather on the size of economy and relationships between its sectors. (i.e. large economies converge faster to equilibrium than small economies).
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This paper examines the role of export diversification for economic growth in CEE transition economies. The results prove that before the outbreak of 2008 financial crisis export specialization rather than diversification was an important growth factor, especially in those countries which followed more specialized export patterns. However, after the outbreak of the crisis the direction of this causal link changed essentially. All three main aspects of export diversification turned out to play a significant role in reducing the growth slowdown effects of the 2008 financial crisis.
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This study examines the causal links between improvements in economic freedom and changes in GDP per capita of new EU members in transition in the period 2000-2009. The empirical results suggest significant causality running from changes in monetary and fiscal freedom, trade openness, regulation of credit, labour, and business, legal structure and security of property rights, and access to sound money to movements in GDP per capita, especially in less and moderately developed CEE transition countries. Moreover, we find evidence that improvements in economic freedom are one of the main factors stimulating the convergence of these economies towards rich EU members. The evidence of causality in the opposite direction is much weaker.
PL
Artykuł jest jednym z pierwszych opracowań analizujących na poziomie regionalnym związki pomiędzy stopą inflacji a wzrostem gospodarczym w Polsce po wejściu do UE. Wyniki potwierdziły, że w okresie 2004-2010 występował nieliniowy związek przyczynowy pomiędzy stopą inflacji a tempem wzrostu gospodarczego w polskich województwach. Badania potwierdziły występowanie dwóch statystycznie istotnych progowych poziomów inflacji związanych z równoczesnymi i opóźnionymi efektami czasowymi.
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This paper is one of the first contributions which examine the nexus between inflation rate and economic growth of Poland after EU accession based on the regional data. The results prove that in the period 2004-2010 the causal link between inflation rate and economic growth among Polish regions was of a nonlinear nature. The empirical analysis confirmed the existence of two statistically significant inflation threshold levels related to contemporaneous as well as one-year-lagged causal effects.
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The goal of this research was the survival analysis of enterprises founded in Lesser Poland Voivodship between years 2006–2014. The sample comprising 267 thousands firms was used to examine whether certain factors such as the size of the company, area of its activity and registration place had statistically significant impact on their duration time. All of those proved to be substantial in the course of our study. In general companies belonging to the sector of finance and insurance survived the shortest, whereas the longest duration (even four times longer than in finance and insurance) was among companies from mining sector, public administration, national defense and social insurance. Moreover, the research has proved that while moving further from Cracow, the survival of companies was likely to shorten. The only exception was Tatra Country, where duration was relatively long despite the distance factor. Additionally companies in urban areas were active approximately 9% longer than firms founded in rural ones. To the best of our knowledge this is the first application of an AFT (accelerated failure time)model to survival analysis of companies based on the data from Central European country. In this case its application proves existence of the heterogeneity of the hazard function.
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Celem artykułu było przeprowadzenie analizy przeżycia przedsiębiorstw rejestrowanych na terenie województwa małopolskiego w latach 2006–2014. Wykorzystany w tym celu zbiór danych zawierał informacje na temat ponad 267 tys. podmiotów gospodarki narodowej i posłużył zbadaniu wpływu wybranych czynników na długość czasu funkcjonowania na rynku. Zgodnie z wiedzą autorów są to jedne z pierwszych badań tego typu na obszarze Europy Środkowo-Wschodniej w których wykorzystano modele przyspieszonej porażki. Istotnymi czynnikami mającymi wpływ na długość okresu istnienia firmy jest jego wielkość, rodzaj działalności gospodarczej oraz miejsce zarejestrowania. Przedsiębiorstwa średnie istnieją statystycznie ponad dwukrotnie dłużej od małych, natomiast małe ponad dwukrotnie dłużej od mikro. Najkrócej działają firmy zajmujące się działalnością finansową i ubezpieczeniową, zaś najdłużej (czterokrotnie dłużej) firmy z obszarów górnictwo i wydobywanie surowców oraz administracja publiczna i obrona narodowa, a także obowiązkowe zabezpieczenia społeczne. Badania wykazały, że im większa odległość od Krakowa tym krótszy okres działania firmy. Firmy zakładane w miastach działają średnio o 9% dłużej niż te zakładane na wsi. Badania za pomocą modeli przyspieszonej porażki jednoznacznie wskazują na występowanie zjawiska heterogeniczności funkcji hazardu.
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Content available remote The structure of contemporaneous price-volume relationships in financial markets.
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The main goal of this paper is an examination of the interdependence stuctures of stock returns, volatility and trading volumes of companies listed on the CAC40 and FTSE100. The authors establish that the mean values of respective measures are different on the markets under study. In general, they are larger for equities from CAC40 than from FTSE100. The Mixture of Distributions Hypothesis with long memory is rejected for about 70 % of stocks from both markets. Additionally fractional cointegration was tested. The lack of fractional cointegration, suggests a rejection of the last variant of MDH in all cases, i.e. the time series under study do not exhibit common long-run dependence. The analyzed time series are not driven by a common information arrival process with long memory. Correlation between volatility and trading volume is present for all the stocks of companies from these markets. The mixtures of rotated copulas and Kendall correlation coefficient allowed the checking of extreme return-volume dependence structures. The empirical results reflect significant dependencies between high volatility and high trading volume. In general, the dependence structures of stock returns and trading volume are different. In the case of CAC40 companies high trading volume is not correlated as frequently with high stock returns as with low stock returns. For companies listed on the FTSE100 high stock returns are mostly related with high trading volume.
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One of the main goals of ATMs’ management is a thorough analysis of the structure of withdrawals for individual ATM and groups of ATMs installed in similar places. This type of research constitutes a necessary background for decision making about the installation or de‑installation of ATMs in each location type. The most important factors from the point of view of the profitability of the ATM is the number of withdrawals and the value of a single withdrawal. A number of withdrawals from ATM determine the revenue of ATM owners due to interchange fees and advertisements displayed in ATMs at the time of withdrawal. A large number of withdrawals generate large revenues. The value of a single withdrawal has an impact on costs. The larger withdrawals generate larger costs including preparation and delivery of cash for an ATM and “freezing” of funds in the ATM. The main goal of this research was to identify locations of the ATMs generating largest revenues i.e. locations with a large number of withdrawals and small value of single withdrawal. In addition, we tested hypotheses concerning differences in a number of withdrawals and values of single withdrawals from ATMs installed in different types of locations. In this paper, we used a time series of numbers and values of withdrawals from ATMs supplied by one of the largest ATMs networks in Poland. The data set concerns ATM’s located in Małopolskie and Podkarpackie provinces in Poland. In the research concerning the structure of withdrawals, we have used basic descriptive statistics and selected statistical tests. The study concluded with the selection of locations where with high probability installation of ATM would generate profits. The results of the analysis may be of interest to owners of networks with respect of the choice of location type.
PL
Jednym z elementów procesu zarządzania siecią bankomatową jest dogłębna analiza struktury wypłat z poszczególnych bankomatów oraz z określonych grup bankomatów o zbliżonej lokalizacji. Jest to element niezbędny przy podejmowaniu decyzji o wyborze lokalizacji dla nowych bankomatów oraz o likwidacji określonego bankomatu lub bankomatów z jakiegoś typu lokalizacji. Ważnymi elementami struktury wypłat, zwłaszcza w ujęciu opłacalności funkcjonowania bankomatu, są liczba oraz wielkość wypłat z bankomatu. Liczba wypłat z bankomatu jest związana bezpośrednio z przychodami operatora z tytułu opłaty interchange oraz reklam wyświetlanych podczas korzystania z bankomatu przez klienta. Im większa liczba operacji wypłat, tym większe przychody dla operatora sieci. Z kolei wielkość wypłat powiązana jest bezpośrednio z kosztami, jakie ponosi operator. Większe wypłaty z danego bankomatu oznaczają wyższe koszty związane z przygotowaniem i dostarczeniem gotówki do bankomatu oraz jej „zamrożeniem” w bankomacie. Celem przeprowadzonych badań jest wskazanie tych typów lokalizacji bankomatów, które potencjalnie przynoszą największe zyski, tzn. występuje w nich najwięcej wypłat o stosunkowo niskiej wartości. Dodatkowo zweryfikowano, czy występuje istotne zróżnicowanie w liczbie wypłat oraz w wielkości wypłat pomiędzy grupami bankomatów z różnych typów lokalizacji. W analizie wykorzystano szeregi czasowe liczby i wielkości wypłat z bankomatów jednego z największych operatorów sieci bankomatowych w Polsce. Dane dotyczą bankomatów zlokalizowanych w województwach małopolskim i podkarpackim. W celu porównania struktury wypłat oraz wykazania ich zróżnicowania w poszczególnych bankomatach i grupach bankomatów wykorzystano podstawowe miary statystyczne oraz wybrane testy statystyczne. W wyniku przeprowadzonych badań zostały wyodrębnione te typy lokalizacji, w których instalowanie bankomatów z dużym prawdopodobieństwem przyniesie większy dochód. Przeprowadzone analizy mogą posłużyć operatorom bankomatowym przy wyborze typu lokalizacji.
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Content available remote Modeling of withdrawals from selected ATMs of the "Euronet" network
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EN
This paper deals with the problem of withdrawals from Automated Teller Machines (ATMs), using daily data for selected ATMs installed by the Euronet network in the Polish provinces of Małopolska and Podkarpacie for the period from January 2008 to March 2012. The main aim of this paper is an estimation of the proper econometric models for withdrawals time series and attempt to forecast future demand on cash flow in ATMs in respect to their localization. This is necessary to establish a replenishment schedule. The results of computations suggest that models built on the basis of SARIMA methodology are useful tools for an modeling daily withdrawals time series. This kind of model can be applied independently of the localization of an ATM. The exercises for ex post data imply ex post forecast errors under 20%. This size of forecast errors is lower than the bias of actual replenishment scheduling.
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Information about the distribution of withdrawals is very essential for ATM networks. It sup- ports optimization of the replenishment process for ATMs. The conducted research showed that the daily distribution of withdrawals was similar among the examined ATMs owned by the Euronet company. Location was the main factor in determining empirical distribution on the same days of the week. Logistic distribution fit best to withdrawals from ATMs located in shopping centers, bank branches, shops, and supermarkets. In addition, uniform distri- bution was found to be the best alternative for withdrawals from ATMs operating at petrol stations.
EN
In the paper common long-term dynamics of return volatility and trading volume of the largest companies listed on Warsaw Stock Exchange in 2005-2011 is examined. The existence of contemporaneous relationship between volatility and volume is implied by the Mixture Distribution Hypothesis which states that volatility and trading volume are jointly generated by information flow process. In the study realized volatility computed on the basis of high frequency data is used as a measure of return volatility. It is more efficient measure of daily return volatility than commonly used absolute or squared returns.
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Content available remote The relationship between WIG-subindexes: evidence from the Warsaw Stock Exchange
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Evidence on links among the major Warsaw Stock Exchange subindexes using daily data from the period of 2011.03.01 to 2014.07.21 is provided in the paper. The empirical study for eleven WIG-sectoral subindexes with 844 observations was conducted by means of Regular Vine Copulas. The application of these copulas allowed us to identify the pairwise structure of the dependence of subindexes under study. The results confirm the leading role of the banking sector in the Polish economy. The dependence structure of the WIG-banking subindex and other subindexes is, in general, asymmetrical. The links between returns of the subindexes are more pronounced in the left tails; i.e., in the bear phase of financial markets. This study suggests the usefulness of Regular Vine Copulas in analyzing dependence structures of a number of financial time series.
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This paper analyses the reaction of stock returns on the Warsaw Stock Exchange to U.S. macroeconomic news announcements. The study is conducted on the basis of five-minute returns of WIG from January 2004 to December 2012. This nine-year period includes different stages of economic cycle and additionally the global financial crisis. Hence results of our analysis are not limited only to contraction or expansion and can be applied to bull and bear market. The application of event study analysis allows us to measure not only the strength of the impact of information release but also its duration.
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Content available remote The optimal portfolio in respect to Expected Shortfall: a comparative study.
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Value at Risk plays a crucial role in the risk management. However, this risk measure has some drawbacks. The alternative risk measure is Expected Shortfall, which is rarely used, but exhibits desirable properties. In the paper, the estimation of both risk measures has been conducted, for pairs of index returns (DJIA, DAX, ATX), based on Markowitz model, the regime switching copula model and the multivariate GARCH model. The results suggest that a misspecification can cause many errors. Incorrect models cause bias of mean, especially models which do not as- sume dynamic structure of the market Both an underestimation and an overestimation of a risk has been observed. In the paper, it is shown that the measure of change in Expected Shortfall as a function of the expected return is strongly underestimated under the normal distribution assumption.
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This paper is concerned with a dependence analysis of returns, return volatility and trading volume for five companies listed on the Vienna Stock Exchange. Taking into account the high frequency data for these companies, tests based on a comparison of Bernstein copula densities using the Hellinger distance were conducted. It is worth noting that these tests can be used in general settings since there is no restrietion on the dimension of the data. The parameter which must be set up for the testing procedure is a bandwidth. It is necessary for estimation of the nonparametric copula. The paper presents some patterns of causal relationships between stock returns, realized volatility and expected and unexpected trading volume. There is linear causality running from realized volatility to expected trading volume, and a lack of nonlinear dependence in the opposite direction. The authors detected strong linear and nonlinear causality from stock returns to expected trading volume. Therefore, a knowledge of past stock returns can improve forecasts of expected trading volume. They did not find causality running in the opposite direction.
EN
While we would like to predict exact values, the information available, being incomplete, is rarely sufficient - usually allowing only conditional probability distributions to be predicted. This article discusses hierarchical correlation reconstruction (HCR) methodology for such a prediction using the example of bid-ask spreads (usually unavailable), but here predicted from more accessible data like closing price, volume, high/low price and returns. Using HCR methodology, as in copula theory, we first normalized marginal distributions so that they were nearly uniform. Then we modelled joint densities as linear combinations of orthonormal polynomials, obtaining their decomposition into mixed moments. Then we modelled each moment of the predicted variable separately as a linear combination of mixed moments of known variables using least squares linear regression. By combining these predicted moments, we obtained the predicted density as a polynomial, for which we can e.g. calculate the expected value, but also the variance to determine the uncertainty of the prediction, or we can use the entire distribution for, e.g. more accurate further calculations or generating random values. 10-fold cross-validation log-likelihood tests were conducted for 22 DAX companies, leading to very accurate predictions, especially when individual models were used for each company, as significant differences were found between their behaviours. An additional advantage of using this methodology is that it is computationally inexpensive; estimating and evaluating a model with hundreds of parameters and thousands of data points by means of this methodology takes only a second on a computer.
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Content available remote Modeling of returns and trading volume by regime switching copulas
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The structure of links between realized volatility and trading volume can be reflected by regime switching copulas. The estimation by means of copula based regime switching models delivered results concerning the interdependencies between realized return volatility and trading volume of selected companies listed in ATX. A copula in the first regime was chosen as an asymmetric copula with positive lower and upper tail dependencies. Conversely Gaussian copula in the second regime is a symmetric copula and variables linked with it are tail independent. For all analyzed stocks the probability of being at the first regime appeared to be vitally greater than being at the second regime. This result suggest that there is considerable dependence between realized volatility and daily volume in extreme values. The results suggest that interdependencies between realized volatility and trading volume do not probably depend on the size but rather on the branch of a company.
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Due to the high importance of the American economy, in the past, announcements of US macroeconomic data were shown to have a significant impact on financial markets in general, and on European stock markets in particular. However, as this effect may vary in time, this paper examines the changes in the impact of US macroeconomic news on the WIG20, the main index of the Warsaw Stock Exchange. Based on intraday data from 2004- 2019 we study the changes in significance and in the strength of the reaction of WIG20 to announcements of unexpected values of 13 indicators describing the American economy. On the basis of the event study analysis, we describe the reaction of the WIG20 index in the first few minutes after these kinds of announcements.
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