Search

A presente dissertação tem como principal objetivo a identificação dos entraves que as empresas da Região de Leiria consideram importantes à implementação da economia circular (EC), tratando-se, portanto, de um estudo de natureza exploratória. Com base nos resultados de pesquisas anteriores e revisão de literatura, são identificadas 30 barreiras e agrupadas em 5 categorias: barreiras culturais e de mercado (BCM), barreiras financeiras (BF), barreiras políticas e regulamentares (BPR), barreiras estruturais e tecnológicas (BET) e barreiras organizacionais e de gestão (BOG). Posteriormente, incluem-se 17 das 30 barreiras inicialmente identificadas num questionário, colocado às empresas da Região de Leiria. Com base nas respostas obtidas conclui-se que as 3 principais barreiras à implementação da EC para as empresas são: (1) a falta de cooperação e colaboração entre empresas (BOG); (2) os clientes não se preocupam com questões relacionadas com o ambiente (BCM); e (3) falta de subsídios ou benefícios fiscais para investir em sistemas produtivos circulares (BPR). A escala utilizada ao nível da categorização das barreiras foi validada com recurso à análise fatorial e os resultados revelam que as empresas da região de Leiria não priorizam nenhum tipo de barreira comparativamente com os outros. No entanto, o presente estudo permite destacar algumas ações prioritárias a realizar, a fim de facilitar a implementação generalizada da EC nas empresas da Região de Leiria.

We analyze the auto-correlations of all European Union (EU) indices and the cross-correlation between the UK stock market and the other EU markets. This analysis took into account the BREXIT referendum, on the 23rd of June 2016 and the entire period was partitioned in two periods, before and after the BREXIT referendum. First of all, we applied the Detrended Fluctuation Analysis method (with the regular and with a sliding windows approach) in order to evaluate market efficiency. In this case, we found that in general the referendum did not change efficiency levels significantly. With the main purpose of measuring the markets interdependence in relation to the UK index, following the referendum, we calculated the Δ ρ D C C A coefficient. Our results point to a decrease in the cross-correlation coefficient ( Δ ρ D C C A 0 ), meaning that the UK is more segmented now, in relation to other EU partners, than in the past. With Δ ρ D C C A it was possible to identify how much the referendum influenced the interdependence, but not the efficiency, of European markets.

Stock market comovements are examined using cointegration, Granger causality tests and nonlinear approaches in context of mutual information and correlations. Underlying data sets are affected by non-stationarities and trends, we also apply AMF-DFA and AMF-DXA. We find only 170 pair of Stock markets cointegrated, and according to the Granger causality and mutual information, we realize that the strongest relations lies between emerging markets, and between emerging and frontier markets. According to scaling exponent given by AMF-DFA, $h(q=2)>1$, we find that all underlying data sets belong to non-stationary process. According to EMH, only 8 markets are classified in uncorrelated processes at $2\sigma$ confidence interval. 6 Stock markets belong to anti-correlated class and dominant part of markets has memory in corresponding daily index prices during January 1995 to February 2014. New-Zealand with $H=0.457\pm0.004$ and Jordan with $H=0.602\pm 0.006$ are far from EMH. The nature of cross-correlation exponents based on AMF-DXA is almost multifractal for all pair of Stock markets. The empirical relation, $H_{xy}\le [H_{xx}+H_{yy}]/2$, is confirmed. Mentioned relation for $q>0$ is also satisfied while for $q, Comment: 16 pages, 13 figures and 4 tables, major revision and match to published version

Football is a sport that moves thousands of people and millions of euros. Since 1983, several clubs entered the stock markets with shares, and now twenty two clubs are listed in the Stoxx Football Index. In this study, we analyse the behaviour of the return rates of such shares, with Detrended Fluctuation Analysis and Detrended Cross-Correlation Analysis (and its correlation coefficient). With Detrended Fluctuation Analysis, we are able to observe that the shares of several clubs are far from the behaviour of a random walk, which is expected by the theory. Using Detrended Cross-Correlation Analysis, we calculate the cross correlations of clubs’ returns with national indexes and then with the Stoxx Football Index. Although almost all of them are positive, they do not seem to be strong.

The Efficient Market Hypothesis (EMH), one of the most important hypothesis in financial economics, argues that return rates have no memory (correlation) which implies that agents cannot make abnormal profits in financial markets, due to the possibility of arbitrage operations. With return rates for the US stock market, we corroborate the fact that with a linear approach, return rates do not show evidence of correlation. However, linear approaches might not be complete or global, since return rates could suffer from nonlinearities. Using detrended cross-correlation analysis and its correlation coefficient, a methodology which analyzes long-range behavior between series, we show that the long-range correlation of return rates only ends in the 149th lag, which corresponds to about seven months. Does this result undermine the EMH?

This paper analyzes stock market relationships among the G7 countries between 1973 and 2009 using three different approaches: (i) a linear approach based on cointegration, Vector Error Correction (VECM) and Granger Causality; (ii) a nonlinear approach based on Mutual Information and the Global Correlation Coefficient; and (iii) a nonlinear approach based on Singular Spectrum Analysis (SSA). While the cointegration tests are based on regression models and capture linearities in the data, Mutual Information and Singular Spectrum Analysis capture nonlinear relationships in a non-parametric way. The framework of this paper is based on the notion of market integration and uses stock market correlations and linkages both in price levels and returns. The main results show that significant co-movements occur among most of the G7 countries over the period analyzed and that Mutual Information and the Global Correlation Coefficient actually seem to provide more information about the market relationships than the Vector Error Correction Model and Granger Causality. However, unlike the latter, the direction of causality is difficult to distinguish in Mutual Information and the Global Correlation Coefficient. In this respect, the nonlinear Singular Spectrum Analysis technique displays several advantages, since it enabled us to capture nonlinear causality in both directions, while Granger Causality only captures causality in a linear way. The results also show that stock markets are closely linked both in terms of price levels and returns (as well as lagged returns) over the 36 years analyzed.