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Abstract: Summarized by the efcient market hypothesis, the idea that stock prices fully refect all available information is always confronted with the behavior of real-world markets. While there is plenty of evidence indicating and quantifying the efciency of stock markets, most studies assume this efciency to be constant over time so that its dynamical and collective aspects remain poorly understood. Here we defne the time-varying efciency of stock markets by calculating the permutation entropy within sliding time-windows of log-returns of stock market indices. We show that major world stock markets can be hierarchically classifed into several groups that display similar long-term efciency profles. However, we also show that efciency ranks and clusters of markets with similar trends are only stable for a few months at a time. We thus propose a network representation of stock markets that aggregates their short-term efciency patterns into a global and coherent picture. We fnd this fnancial network to be strongly entangled while also having a modular structure that consists of two distinct groups of stock markets. Our results suggest that stock market efciency is a collective phenomenon that can drive its operation at a high level of informational efciency, but also places the entire system under risk of failure.
Keywords: collective dynamics, social physics, econophysics, stock market
Published in DKUM: 14.01.2025; Views: 0; Downloads: 0
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Abstract: The thesis is dealing with the question if the U.S. technology sector is in the bubble. Besides the main aim of this thesis, we are also interested in what the changes are in recent stock market bubbles. The analysis of the sector is key to the investors, because with the early identification of a bubble, they can allocate their funds to other less risky investments. On the other hand, the investors can with the analysis of the sector find out if specific sector is undervalued and thus make above average revenue. Our analysis is based on the study of relative indicators, such as: P/E, P/B, CAPE, P/B, P/S and MarketCap/GDP. We studied the last two historic bubbles and analyzed the current state on the U.S. stock markets. The analysis is focused on the last part of the thesis, where we evaluated what is the current market sentiment in the U.S. stock market, especially in the technology sector. The results are compared to the technology bubble of 2000. In the analysis, we are using U.S. stock market indices as well as the global ones. U.S. stock market is overvalued, which can be argued with high values of the relative indicators compared to the historical average. Some of them show, that market was valued higher only during the Great Depression in 1929 and during the technological bubble in 2000. Remarkably high values are the result of low interest rates and quantitative easing of central banks. The current expansive monetary politics is encouraging risky businesses and increasing credit businesses. The indicator, showing this kind of operations, is the value of investment financed with credit, which is constantly rising in the U.S. since 2009. As a result, stocks and stock indices are increasing as well. With potential abatement of tax rates and other measures of expansive fiscal politics, stock markets could reach even higher values. Currently, we are in the ninth year of bull trend, which is close to the record of 1991, which lasted for nearly a decade. Since 2009, there is optimism prevailing in U.S. stock market, which is reflecting in above average revenue. The feature of the stock market bubble is that it is developing slowly and persistently, thus the main question arises, when will this optimism turn into fear and pessimism, or better said, when will the stock market bubble burst. Still, no one has the answer to that yet.
Keywords: stock market bubble, technology sector, overvalued, stock market, stock market index, dot.com bubble, housing bubble
Published in DKUM: 08.12.2017; Views: 2032; Downloads: 91
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Abstract: The objective of this paper is to analyze dependence structure between the returns of Croatian and five European stock markets (Austrian, French, German, Italian, and the U.K.ʼs). We propose a copula GARCH approach, where the return series are modeled as univariate GARCH processes and the dependence structure between the return series is defined by a copula function. Four different copulas are fitted - a constant and conditional normal and symmetric Joe-Clayton (SJC) copulas - and estimated by a semi-parametric method. We found that the time-varying normal copula yields the best fit for CROBEX-CAC40, CROBEX-DAX, and CROBEX-FTSE-MIB stock indices pairs, while the time-varying SJC copula is the best fit for CROBEX-ATX and CROBEX-FTSE100. Further, we found that the probability of simultaneous extreme positive and negative returns in Croatian and other European stock markets can increase to 0.77 during turbulent times. The lower and upper tail dependence dynamics between Croatian and other European stock markets is similar in pattern, differing only in scale. The basic conclusion of the research is that the dependence between the stock markets of Croatia and five major European stock markets is dynamic and can be properly captured by either a dynamic normal or symmetrized Joe-Clayton copula GARCH models.
Keywords: stock market, stock companies, econometric models, Croatia, EU, dependence, copula GARCH
Published in DKUM: 17.07.2017; Views: 1184; Downloads: 136
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