On the conditional behavior of stock market volatility: a sub-sample analysis using the FIGARCH approach for developed and emerging markets

Long memory has always played a central role in physics since it was first discovered by Hurst while studying the flow of the River Nile. Interestingly, after his seminal work, many other researchers found the same pattern in other domains of science, such as biology, economics and finance. These studies have mainly relied on the use of the Hurst exponents as a measure of the degree of memory in a process. In this paper we use a different approach based on the FIGARCH (fractional integrated generalized autoregressive conditionally heteroskedasticity) model proposed by Baillie et al. in order to analyze the long memory behavior of stock market volatility. More specifically, we compare how the long memory parameter evolves before and after the 2008 and 2012 crises in both developed and emerging markets. Specifically, we consider the daily returns of the S&P 500, STOXX 50, FTSE 100, NIKKEI 225, HSI, BUX, WIG, SSE, IDX and KLCI indices for the period from October 1, 2003 to October 2, 2015 and then split the whole sample into four sub-samples of roughly three years each. Results show different patterns for the pre and post crisis periods revealing that the degree of memory differs in accordance with the country’s development and the level of market turbulence. In particular, we found that major mature economies present higher levels of long memory than emerging countries and were more affected by the 2008 and 2012 crises.info:eu-repo/semantics/publishedVersio

Entropy: a new measure of stock market volatility?

WOS:000312545800033 (Nº de Acesso Web of Science)When uncertainty dominates understanding stock market volatility is vital. There are a number of reasons for that. On one hand, substantial changes in volatility of financial market returns are capable of having significant negative effects on risk averse investors. In addition, such changes can also impact on consumption patterns, corporate capital investment decisions and macroeconomic variables. Arguably, volatility is one of the most important concepts in the whole finance theory. In the traditional approach this phenomenon has been addressed based on the concept of standard-deviation (or variance) from which all the famous ARCH type models - Autoregressive Conditional Heteroskedasticity Models- depart. In this context, volatility is often used to describe dispersion from an expected value, price or model. The variability of traded prices from their sample mean is only an example. Although as a measure of uncertainty and risk standard-deviation is very popular since it is simple and easy to calculate it has long been recognized that it is not fully satisfactory. The main reason for that lies in the fact that it is severely affected by extreme values. This may suggest that this is not a closed issue. Bearing on the above we might conclude that many other questions might arise while addressing this subject. One of outstanding importance, from which more sophisticated analysis can be carried out, is how to evaluate volatility, after all? If the standard-deviation has some drawbacks shall we still rely on it? Shall we look for an alternative measure? In searching for this shall we consider the insight of other domains of knowledge? In this paper we specifically address if the concept of entropy, originally developed in physics by Clausius in the XIX century, which can constitute an effective alternative. Basically, what we try to understand is, which are the potentialities of entropy compared to the standard deviation. But why entropy? The answer lies on the fact that there is already some research on the domain of Econophysics, which points out that as a measure of disorder, distance from equilibrium or even ignorance, entropy might present some advantages. However another question arises: since there is several measures of entropy which one since there are several measures of entropy, which one shall be used? As a starting point we discuss the potentialities of Shannon entropy and Tsallis entropy. The main difference between them is that both Renyi and Tsallis are adequate for anomalous systems while Shannon has revealed optimal for equilibrium systems

Market integration and globalization of financial markets: Evidence from Portugal, Spain, UK, Japan and US

This paper analyzes the stock market globalization on the basis of the price theory. This leads to the concept of market integration which, under the nonstationarity of price level variables, can be empirically tested by using cointegration techniques. An error correction model incorporating prices and returns is specified and empirically tested. The results show that the five stock markets under analysis are cointegrated and there is just one cointegrating vector that explains the longrun relationship between these markets. Market integration holds for the system as a whole but full price transmission is only accepted for some pairs. The results show that price movements between pairwise stock markets are usually highly nonlinear.info:eu-repo/semantics/publishedVersio

Gold prices and equity market crises: how accurate are the forecasts from a nonlinear model?

This paper examines the role of gold as a hedge during financial crises using daily data for the period 1976-2015. Although it is known that gold prices tend to increase during equity market crashes and that price volatility is symmetric or, at most, exhibits positive asymmetry; relatively little is known about the nonlinear nature of this behaviour. In fact, it seems that the magnitude of cross-correlations and the degree of shock’s persistency not only varies over time but also changes from the pre-crisis and the post-crisis period. This behaviour suggests that structural changes play an important role in this process of adjustment and hedging. Therefore, we use a combined STAR-IGARCH (Smooth Transition AutoRegressive – Integrated GARCH) type model to obtain forecasts of gold prices and their underlying volatility according to the nature of each crisis event. These results are compared with those obtained from the traditional IGARCH volatility specifications and the encompassing forecast accuracy is tested. The analysis is carried out over the entire sample period and over subsamples obtained from the succession of main crisis that occurred between 1976 and 2015. Our findings show that the STAR-IGARCH forecasts outperform the traditional IGARCH volatility forecasts in most cases and that the consideration of fractional persistency improves the quality of our forecasts. The role of gold prices as a hedge, even under the presence of structural changes, is thus confirmed by our results.info:eu-repo/semantics/publishedVersio

Cointegration and structural breaks in the PIIGS economies

Due to the economic recession which started in 2008, several members of the European Union became historically known as PIIGS. These states include Portugal, Italy, Ireland, Greece and Spain and if ombined together, they form the acronym PIIGS. The reason why these countries were grouped together is the substantial instability of their economies, which was an evident problem in 2009. The reason why the five countries gained popularity is a serious concern within the EU, with regard to their national debts, especially for Greece. The latter country was involved in a controversial affair after allegedly falsifying its public financial data. In the year 2010, it was evident that the five states were in need of corrective action in order to regain their former financial stability. Because of the dirty farm animal associated with the acronym, several country leaders from the financially troubled countries have voiced out disagreement with the use of the term. However, there are quite a number of reporters and columnists who still refer to it when talking about the widespread economic crisis within the European Union. Although some prominent politicians have criticized the practice, the use of the word is very hard to shake off

Globalization, regime-switching, and EU stock markets: the impact of the sovereign debt crises

The most recent models learn over time, making the necessary adjustments to a new level of peaks or troughs, which enables the more accurate prediction of turning points. The Smooth Regression Model may be regarded as having a linear and a nonlinear component and may over time determine whether there is only a linear or nonlinear component or, in some cases, both. The present study focuses on the impact effect analysis of the European markets contamination by sovereign debt (particularly in Portugal, Spain, France and Ireland). The smooth transition regression approach applied in this study has proved to be a viable alternative for the analysis of the historical behavioural adjustment between interest rates and stock market indices. We found evidence in the crisis regime, i.e., large negative returns, especially in the case of Portugal, where we obtained the greatest nonlinear threshold adjustment between interest rates and stock market returns

Cointegration and Structural Breaks in the EU Sovereign Debt Crisis

First signs of a sovereign debt crisis spread among financial players in the late 2009 as a result of the growing private and government debt levels worldwide. Late 2010, Trichet (then President of the ECB) stated that the sovereign debt crisis in Europe had become systemic. In an established crisis context, it was searched for evidence of structural breaks and cointegration between interest rates and stock market prices. A 13 year time-window was used in six European markets under stress. The results identified significant structural breaks at the end of 2010 and consistently rejected the null hypothesis of no cointegration.info:eu-repo/semantics/publishedVersio

Organizational social capital Scale based on Nahapiet and Ghosal model: development and validation

The goal of this work is to develop and validate a scale to identify workers' behaviors as well as those of organizations, and to understand how they develop and build enterprise competitiveness through organizational social capital, a complex network of relationship that is critical to business success. For this the present theories were mapped out to identify the similarities and differences within social capital, focusing on organizational social capital. With this background a Nahapiet and Ghosal three dimensional model was chosen as the most suitable construct with which to create the instrument. All methodological research steps for behavioral instrument creation were taken into account. The questionnaire created was refined and validated for semantic and content validity, then it was tested using statistical tools for items reduction through Exploratory Factor Analysis to refine the instrument. The scale was approved in the tests and the findings of this process also led to the conclusion that social capital is a one-dimensional construct.info:eu-repo/semantics/publishedVersio

Organizational anomie, professional self-concept and organizational support perception: theoretical model evidences for management

Employees need reliability and predictability in the organization's moral order to properly engage in labor, which has become critical for organizations’ success. Its absence creates a rupture in the firm's capacity to thrive in the market, named anomie. With the aim of looking more deeply into this subject, we have studied the relationship between anomie and social support at work, as well as professional self-concept, to understand and measure the cause-and-effect process. For this purpose, a model has been created to test this hypothesis, which has been analyzed through Structural Equation Modeling. The scales used have already been validated by other researches. The results provide evidence that the proposed model is suitable to identify and measure the relationship between the studied variables, and showing the level of impact that occurs on the system, created by organizational anomie, on social support at work and professional self-concept, together with their component parts.info:eu-repo/semantics/publishedVersio