Andreia Dionísio

An econophysics approach to analyse uncertainty in financial markets:an application to the Portuguese stock market

Abstract.In recent years there has been a closer interrelationship between several scientific areas trying to obtain a more realistic and rich explanation of the natural and social phenomena. Among these it should be emphasized the increasing interrelationship between physics and financial theory. In this field the analysis of uncertainty, which is crucial in financial analysis, can be made using measures of physics statistics and information theory, namely the Shannon entropy. One advantage of this approach is that the entropy is a more general measure than the variance, since it accounts for higher order moments of a probability distribution function. An empirical application was made using data collected from the Portuguese Stock Market.

On the integrated behaviour of non-stationary volatility in stock markets

This paper analyses the behaviour of volatility for several international stock market indexes, namely the SP 500 (USA), the Nikkei (Japan), the PSI 20 (Portugal), the CAC 40 (France), the DAX 30 (Germany), the FTSE 100 (UK), the IBEX 35 (Spain) and the MIB 30 (Italy), in the context of non-stationarity. Our empirical results point to the evidence of the existence of integrated behaviour among several of those stock market indexes of different dimensions. It seems, therefore, that the behaviour of these markets tends to some uniformity, which can be interpreted as the existence of a similar behaviour facing to shocks that may affect the worldwide economy. Whether this is a cause or a consequence of market globalization is an issue that may be stressed in future work.

Revisiting serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece

This article uses several tests to analyse serial dependence in financial data, trying to confirm the existence of some kind of nonlinear dependence in stock markets. In an attempt to provide a better explanation of the behaviour of stock markets, we used tests based on mutual information and detrended fluctuation analysis (DFA). Applying these tests to the series of stock market indexes of 10 countries, we concluded for the absence of linear autocorrelation. However, with other tests, we found nonlinear serial dependence that affects the rates of return. With DFA, we found out that most return rate series have long-range dependence, which appears to be more pronounced for Spain, Greece and Portugal. To confirm the inefficiency of those markets, based on our results, we should prove the existence of abnormal profits.

Revisiting Covered Interest Parity in the European Union: the DCCA Approach

Abstract This paper analyzes the evidence of financial integration, with covered interest parity (CIP), for a group of countries that have already adopted the euro and another group of countries that kept their currencies. We use detrended cross-correlation analysis, which allows analyzing the behavior of time series even when they are not stationary. The main results indicate that countries that adopted the euro do not show much evidence in favor of CIP, before joining the Eurozone, which could imply they will not benefit from all common currency advantages. In the group of countries that did not adopt the euro, Denmark, Sweden, the UK and the Czech Republic are the ones presenting better conditions for financial integration with the euro, while Bulgaria has also some evidence of this. Some possible explanations of CIP deviations are agents not considering all countries’ assets as similar and also the underdevelopment of markets and liquidity problems (more pronounced due to periods of turmoil).

Utility function estimation: The entropy approach

The maximum entropy principle can be used to assign utility values when only partial information is available about the decision maker’s preferences. In order to obtain such utility values it is necessary to establish an analogy between probability and utility through the notion of a utility density function. In this paper we explore the maximum entropy principle to estimate the utility function of a risk averse decision maker.

Assessment of 48 Stock markets using adaptive multifractal approach

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,

GDP growth and convergence determinants in the European Union: a crisp-set analysis

h(q=2)>1

Estimating utility functions using generalized maximum entropy

, we find that all underlying data sets belong to non-stationary process. According to EMH, only 8 markets are classified in uncorrelated processes at

The Relation Between Entrepreneurial Behaviour and Entrepreneurship Rates Over Time: An Approach Using Qualitative Comparative Analysis

2\sigma

EQUITY MARKETS INTEGRATION IN ASIA

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