Stochastic volatility (SV) models provide a natural framework for a representation of time series for financial asset returns. As a result, they have become increasingly popular in the finance literature, although they have also been applied in other fields such as signal processing, telecommunications, engineering, biology, and other areas. In working with the SV models, an important issue arises as how to estimate their parameters efficiently and to assess how well they fit real data. In the literature, commonly used estimation methods for the SV models include general methods of moments, simulated maximum likelihood methods, quasi Maximum likelihood method, and Markov Chain Monte Carlo (MCMC) methods. Among these approaches, MCMC methods are most flexible in dealing with complicated structure of the models. However, due to the difficulty in the selection of the proposal distribution for Metropolis-Hastings methods, in general they are not easy to implement and in some cases we may also encounter convergence problems in the implementation stage. In the light of these concerns, we propose in this thesis new estimation methods for univariate and multivariate SV models. In the simulation of latent states of the heavy-tailed SV models, we recommend the slice sampler algorithm as the main tool to sample the proposal distribution when the Metropolis-Hastings method is applied. For the SV models without heavy tails, a simple Metropolis-Hastings method is developed for simulating the latent states. Since the slice sampler can adapt to the analytical structure of the underlying density, it is more efficient. A sample point can be obtained from the target distribution with a few iterations of the sampler, whereas in the original Metropolis-Hastings method many sampled values often need to be discarded. In the analysis of multivariate time series, multivariate SV models with more general specifications have been proposed to capture the correlations between the innovations of the asset returns and those of the latent volatility processes. Due to some restrictions on the variance-covariance matrix of the innovation vectors, the estimation of the multivariate SV (MSV) model is challenging. To tackle this issue, for a very general setting of a MSV model we propose a straightforward MCMC method in which a Metropolis-Hastings method is employed to sample the constrained variance-covariance matrix, where the proposal distribution is an inverse Wishart distribution. Again, the log volatilities of the asset returns can then be simulated via a single-move slice sampler. Recently, factor SV models have been proposed to extract hidden market changes. Geweke and Zhou (1996) propose a factor SV model based on factor analysis to measure pricing errors in the context of the arbitrage pricing theory by letting the factors follow the univariate standard normal distribution. Some modification of this model have been proposed, among others, by Pitt and Shephard (1999a) and Jacquier et al. (1999). The main feature of the factor SV models is that the factors follow a univariate SV process, where the loading matrix is a lower triangular matrix with unit entries on the main diagonal. Although the factor SV models have been successful in practice, it has been recognized that the order of the component may affect the sample likelihood and the selection of the factors. Therefore, in applications, the component order has to be considered carefully. For instance, the factor SV model should be fitted to several permutated data to check whether the ordering affects the estimation results. In the thesis, a new factor SV model is proposed. Instead of setting the loading matrix to be lower triangular, we set it to be column-orthogonal and assume that each column has unit length. Our method removes the permutation problem, since when the order is changed then the model does not need to be refitted. Since a strong assumption is imposed on the loading matrix, the estimation seems even harder than the previous factor models. For example, we have to sample columns of the loading matrix while keeping them to be orthonormal. To tackle this issue, we use the Metropolis-Hastings method to sample the loading matrix one column at a time, while the orthonormality between the columns is maintained using the technique proposed by Hoff (2007). A von Mises-Fisher distribution is sampled and the generated vector is accepted through the Metropolis-Hastings algorithm. Simulation studies and applications to real data are conducted to examine our inference methods and test the fit of our model. Empirical evidence illustrates that our slice sampler within MCMC methods works well in terms of parameter estimation and volatility forecast. Examples using financial asset return data are provided to demonstrate that the proposed factor SV model is able to characterize the hidden market factors that mainly govern the financial time series. The Kolmogorov-Smirnov tests conducted on the estimated models indicate that the models do a reasonable job in terms of describing real data.

This dissertation contains four papers in the field of financial econometrics. In the first paper, A Smooth Transition ARCH Model for Asset Returns, a new class of ARCH models is introduced. The model class allows for non-linearity in the equation for the conditional variance. Two forms of non-linearity are considered: (i) asymmetry regarding the sign of residuals, and (ii) non-linearity regarding the size of residuals. Furthermore, specification tests for the models are presented. The second paper, Specification Tests for Asymmetric GARCH, presents two new Lagrange multiplier test statistics designed for testing the null of GARCH(1,1), against the alternative of asymmetric GARCH. Small sample properties for the statistics are presented and the power of both tests is shown to be superior to that of previously proposed tests. This is true for a large group of asymmetric GARCH models, providing that the proposed tests can detect general GARCH asymmetry. The third paper, Modeling Nordic Stock Returns with Asymmetric GARCH models, investigates the presence of asymmetric GARCH effects in a number of equity return series, and compares the modeling performance of seven different asymmetric GARCH models. The data consists of daily returns for 45 Nordic stocks, for the period July 1991 to July 1996. The paper also introduces three new procedures for asymmetry testing. The proposed LM tests allow for heterokurtosis under the null. The final paper, Discrete Time Hedging of OTC Options in a GARCH Environment: A Simulation Experiment, examines the effect of using the Black and Scholes formula for pricing and hedging options in a discrete time heteroskedastic environment using a simulation procedure. It is shown that the variance of the returns on the hedged position is considerably higher in a GARCH(1,1) environment than in a homoskedastic environment. The variance of returns is heavily dependent on the level of kurtosis in the returns process and on the first-order autocorrelation in centered and squared returns.Each paper is self-contained and can be read in an order chosen by the reader.In an introductory chapter, the reader is given a general summary of the ARCH literature and will gain a clear understanding of how the four essays relate to previous work in the econometrics and finance literature, and to practical considerations of econometric modeling. / Diss. Stockholm : Handelshögsk.

This study examines the frequency of extreme trading days and investment behaviour in Sweden. We show that the frequency, as well as the magnitude of extreme trading days has increased over time. We also show that the frequency of extreme trading days in a year is positively correlated to the frequency the preceding year. Furthermore, we show that aggregate cash flows into equity and bond funds are unrelated to risk measured by standard deviation of return. Our findings show that investors, individuals as well as corporations, use simple passive investment strategies and hence, do not believe in market timing or wish to risk capital on capturing far tail or black swan type returns.

This paper uses a new measure of volatility based on extreme day return occurrences and examines the relative prevailing volatility among worldwide stock markets during 1997-2009. Using several global stock market indexes of countries categorized as an emerging and developed capital markets are utilized. Additionally this study investigates well known anomalies namely Monday effect and January effect. Further using correlation analysis of co movement and extent of integration highlights the opportunities for international diversification among those markets. Evidences during this time period suggest volatility is not the only phenomena of emerging capital markets. Emerging markets offer opportunities of higher returns during volatility. Cross correlation analysis depicts markets have become more integrated during this time frame; still opportunities for higher returns prevail through global portfolio diversification.

Whether or not currency markets may be regarded as efficient or not has been a hotly debated issue in the academic literature over recent decades. Economic theory would suggest that these markets should be efficient because they are apparently good examples of a perfectly competitive market structure. On the other hand, empirical tests of the efficient market hypothesis within these currency markets unequivocally find them to be inefficient. There is still no good explanation for this conundrum and as a result a fair amount of effort is still expended on refining the empirical studies of market efficiency, a task which is taken up in the four empirical studies that comprise this thesis. Within efficient markets, prices are predicted to respond &quotquickly" with the arrival of new information and the empirical work in the thesis focuses on these issues by identifying three key areas for research, namely, price adjustment and volatility, volatility and the &quotnews", and the speed of price adjustment. In essence, the studies examine whether there is inefficient adjustment to news in terms of excessive volatility, whether or not news is actually the main driver of exchange rate volatility and whether or not &quotquickly" can be measured empirically. The empirical results reported within this thesis confirm that the Australian dollar has not been an excessively volatile currency, even though the level of volatility has been increasing; that the pattern of information flow explains a significant degree of the non constant variance in the returns of the world's most actively traded currencies, (i.e. information explains price innovation); that the reaction time to macroeconomic news occurs within seconds of a pre-scheduled announcement, and that the bulk of adjustment to fundamental value occurs within the hour. These findings are consistent with what would be expected within an efficient market. The results reported within this thesis therefore suggest that the currency markets studied are efficient, at least for the sample periods of the data used in the studies. Exchange rates adjust rapidly with information arrival albeit not completely. It is also the case that a number of additional research questions emerge from this research. For example we know that volatility is not excessive and that it is increasing. What we do not know is the point at which increasing volatility becomes excessive. We know that exchange rates react quickly with the arrival of macroeconomic news, but we do not know precisely how long it takes for volatility to return to preannouncement levels, or why the reaction to news is inconsistent. We also do not know what type of information best explains volatility above that which is explained by the systematic dissemination of information or why full adjustment to fundamental value does not occur? Answers to these questions provide a future research agenda. Answers may provide insight that will help financial economists explain the apparent failure of the speculative efficient hypothesis.

This dissertation consists of three stand-alone essays on fundamental uncertainty, stock return volatility and earnings management. The first study investigates the role of information about firms?? fundamentals contained in analysts?? forecasts (which I label ??non-accounting information??) in understanding stock return volatility. When combined with Ohlson??s (1995) linear information dynamics, the accounting version of the Campbell-Shiller model (Campbell and Shiller 1988a, 1988b; Vuolteenaho 2002) implies that if current non-accounting information is more uncertain, then future stock returns are expected to be more volatile. The empirical evidence supports the theoretical predictions, and the results are valid for measures of both systematic and idiosyncratic volatility. Additional analysis yields some evidence that both favourable and unfavourable news from non-accounting information increases future stock return volatility. Overall, the results highlight the value relevance of information in analysts?? forecasts beyond what is contained in the current financial statements. The second essay extends the theoretical framework of Callen and Segal (2004) and Vuolteenaho (2002) to investigate the association between the uncertainty of accrual information and stock return volatility. The empirical evidence supports the theoretical prediction that the extent of uncertainty in accounting accruals is increasing with the volatility of future stock returns, and the results are valid for measures of both systematic and idiosyncratic volatility. However, when accrual variability is decomposed into fundamental and unexpected portions, I find that the positive relationship between accrual variability and future stock return volatility is dominated by the fundamental component of accrual variability. The findings therefore suggest that the market places little weight on information conveyed by that component of accounting accruals that is most likely to reflect accounting choices, implementation decisions and managerial opportunism. The final essay argues that the presumed articulation among accruals, cash flows and revenues does not capture decisions on expected accruals when large external financing activities are present. The analysis provides evidence that managers?? ??normal?? operating decisions associated with net external financing activities are likely to lead to measurement errors in unexpected accruals that are part of expected accruals, and erroneous conclusions that significant earnings management exists when in fact there is none. This is especially pertinent in cases where the partitioning variable used to identify instances of earnings management is supposed to be uncorrelated with external financing, when in fact it is correlated. The results underscore the importance of additional specification tests being conducted to control for estimation biases in unexpected accruals associated with external financing. I suggest the use of matched-firm approach using industry and external financing matches in order that reliable and warranted inferences are made.

In this thesis I study the investment climate in the four rapidly growing emerging economies Brazil, Russia, India and China (BRIC). The first study, Chapter 2, uses a bivariate EGARCH methodology with time varying conditional correlation to study the global and regional integration of the BRICs and to identify the existence of diversification opportunities for international investors. The second study, Chapter 3, employs a restricted version of the model to explore the relationship between equity market returns and volatility of equity returns in the BRIC countries and global oil prices. Chapter 4 is an extension of Chapter 3, and focuses on the sustainability of Russia???s economic growth in view of its large dependence on oil income. A qualitative analysis of the oil industry in Russia, including an overview of the operations of the largest oil producing companies, government regulations, oil production and proven oil reserves, is conducted for the purpose of this study. The last study, Chapter 5, uses a panel data methodology to explore the determinants of changes in sovereign bond spreads for the BRICs as an asset class and for each of the BRIC countries individually. I conclude that the regional and global level of integration of the BRICs is relatively low, and portfolio investors can enjoy sound diversification benefits particularly by taking investment positions in the Indian and Chinese equity markets. Despite the aggressive economic growth of the BRICs and their increased oil consumption, the volatility of stock returns from the BRICs does not have a significant impact on global oil prices; however, oil prices do impact the volatility of equity returns in India and China, and particularly the level of returns and volatility of equity returns in Russia. Based on this and the qualitative analysis in Chapter 4, it is concluded that in the short to medium term Russia???s continued economic growth will depend on increased reinvestment in the oil industry and in the longer term the government should diversify its revenue sources and focus on development of other sectors within the economy. Lastly, it is concluded that sovereign risk in the BRICs is driven by different global and country-specific factors, hence risk should be observed on an individual country basis and not for the BRICs as an asset class.

This thesis examines the return volatility of Hong Kong stock market on the firm-level, industry-level, and market-level during a fifteen year sample period between 1991 and 2005. The identified patterns of stock return volatilities contribute to the understanding of an important Asian market.

Στη συγκεκριμένη διπλωματική εργασία θα αναλύσω τον ρόλο που παίζει η αστάθεια στην ευρύτερη χρηματιστηριακή αγορά, σε συνδυασμό με τους θεσμικούς επενδυτές. Δηλαδή θα αναλύσουμε κατά πόσο οι συναλλαγές των θεσμικών επενδυτών επηρεάζουν την αστάθεια που παρατηρείται στις αποδόσεις των δεικτών των χρηματιστηρίων. / In this desertation will analyze the rule to play the volatility in the stocks markets, in combination with the institutional investors. I analyze that how the trading of institutional investors affected the volatility of equity returns of index of stock markets.

As pesquisas em finanças tem focado nos últimos anos a modelagem da variância devido à dificuldade de se obter boa previsão dos retornos na média, negligenciando o uso deste último, quanto informação necessária, no estabelecimento de estratégias de alocação de ativos em carteiras de renda variável. Seguindo DeMiguel, Nogales e Uppal (2014), esse trabalho adota o VAR como meio de se obter previsões dos retornos um passo à frente, e então, usá-las na alocação dos ativos. Para a inserção do VAR em finanças, foi permitido que os parâmetros variassem no tempo, o que conseguiu captar com sucesso a dinâmica volátil do mercado de ações. Ainda foram incorporadas técnicas bayesianas de estimação, a fim de driblar a sobreparametrização e obter estimações mais suavizadas, evitando deste modo que a variância das carteiras fossem muito altas. O método teve sucesso na aplicação e mostrou que o uso da previsão um passo à frente para os retornos pode ser usada como uma boa estratégia, expressa nos altos índices de Sharpe encontrados. / Research in finance has focused in recent years in variance modelling due to the difficulty of obtaining good forecasts of mean returns, neglecting the use of this latter on the establishment of asset allocation strategies in the equity portfolios. Following DeMiguel, Nogales e Uppal (2014), this work adopts the VAR as a way of obtaining forecasts of returns one step ahead and to get use of them in the allocation of assets. For insertion of the VAR in finance, the parameters was allowed to vary over time, which successfully captured the volatile dynamics of the stock market. Bayesian estimation techniques was incorporated in order to surmount overparameterization and to get more smoothed estimates, thereby preventing the variance of the portfolio to be very high. The method was successful in this application and showed that the making of one step ahead prediction of returns can be used as a good strategy, which can be expressed in high levels of Sharpe.