Beta Risk and Regime Shift in Market Volatility

In this paper, we relate the returns in the thirty securities in the Dow Jones index to regime shifts in stock market volatility. We apply a Markov switching process of order one to market volatility and examine the variation in the securities' returns in different volatility regimes. We test the significance of the risk premium in different market regimes and we find evidence of relationship between market volatility and securities beta risk.Markov regime-switching, market volatility, beta risk

Sudden changes in volatility: The case of five central European stock markets

This is the post-print version of the final paper published in Journal of International Financial Markets, Institutions and Money. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2007 Elsevier B.V.This paper investigates sudden changes in volatility in the stock markets of new European Union (EU) members by utilizing the iterated cumulative sums of squares (ICSS) algorithm. Using weekly data over the sample period 1994–2006, the time period of sudden change in variance of returns and the length of this variance shift are detected. A sudden change in volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises. Evidence also reveals that when sudden shifts are taken into account in the GARCH models, the persistence of volatility is reduced significantly in every series. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series

Sudden changes in volatility: The case of five central European stock markets

This paper investigates sudden changes in volatility in the stock markets of new European Union (EU) members by utilizing the iterated cumulative sums of squares (ICSS) algorithm. Using weekly data over the sample period 1994-2006, the time period of sudden change in variance of returns and the length of this variance shift are detected. A sudden change in volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises. Evidence also reveals that when sudden shifts are taken into account in the GARCH models, the persistence of volatility is reduced significantly in every series. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series

Essays on Macro-Finance Relationships

In my dissertation, I study relationships between macroeconomics and financial markets. In particular, I empirically investigate the links between key macroeconomic indicators, such as output, inflation, and the business cycle, and the pricing of financial assets. The dissertation comprises three essays. The first essay investigates how the entire term structure of interest rates is influenced by regime-shifts in monetary policy. To do so, we develop and estimate an arbitrage-free dynamic term-structure model which accounts for regime shifts in monetary policy, volatility, and the price of risk. Our results for U.S. data from 1985-2008 indicate that: i) the Fed\u27s reaction to inflation has changed over time, switching between more active and less active monetary policy regimes,: ii) the yield curve in the more active regime was considerably more volatile than in the less active regime, and: iii) on average, the slope of the yield curve in the more active regime was steeper than in the less active regime. The steeper yield curve in the more active regime reflects higher term premia that result from the risk associated with a more volatile future short-term rate given a more sensitive response to inflation. The second essay examines the predictive power of the entire yield curve for aggregate output. Many studies find that yields for government bonds predict real economic activity. Most of these studies use the yield spread, defined as the difference between two yields of specific maturities, to predict output. In this paper, I propose a different approach that makes use of information contained in the entire term structure of U.S. Treasury yields to predict U.S. real GDP growth. My proposed dynamic yield curve model produces better out-of-sample forecasts of real GDP than those produced by the traditional yield spread model. The main source of this improvement is in the dynamic approach to constructing forecasts versus the direct forecasting approach used in the traditional yield spread model. Although the predictive power of yield curve for output is concentrated in the yield spread, there is also a gain from using information in the curvature factor for the real GDP growth prediction. The third essay investigates time variation in CAPM betas for book-to-market and momentum portfolios across stock market volatility regimes. For our analysis, we jointly model market and portfolio returns using a two-state Markov-switching process, with beta and the market risk premium allowed to vary between low and high volatility regimes. Our empirical findings suggest strong time variation in betas across volatility regimes in most of the cases for which the unconditional CAPM can be rejected. Although the regime-switching conditional CAPM can still be rejected in many cases, the time-varying betas help explain portfolio returns much better than the unconditional CAPM, especially when market volatility is high

Effect of regulation, Islamic law and noise traders on the Saudi stock market

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Saudi stock market (SSM) has witnessed various market regulations and transformations taking place over the past decade. However, the impact of these reforms on market efficiency has not been addressed in the literature. Furthermore, idiosyncratic features of the market can play an important role on the market performance, yet these features have not been fully investigated. The aim of this thesis is to tackle these issues by empirically examining the market efficiency hypothesis and volatility behaviour of the Saudi stock market. Specifically, in order to better understand the relationship between stock returns and prohibition of interest (riba), both conditional and unconditional volatilities are investigated in the context of Islamic law and herd behaviour of noise traders. In Chapter 2 the efficient market hypothesis is tested on the basis of various market efficiency models. Results of both parametric and non-parametric tests reveal that despite the evidence of improved efficiency in the Saudi stock market the weak form of efficient market hypothesis theory is still generally rejected. Chapter 3 considers two types of the generalised autoregressive conditional heteroscedasticity (GARCH) model, a univariate and multivariate GARCH. Specifically, the univariate GARCH model is used to test the seasonality effect of the Ramadan month on each of the five stock market sectors. The multivariate GARCH is used instead to investigate the effect of interest (riba) prohibition in Islam on the volatility of the Saudi stock market. A distinction is made between stocks that are in agreement with Islamic Sharia’a law and interest paying stocks that are not allowed to devoted Muslim investors. The result demonstrates that the Islamic compliant sectors are more volatile than non-Islamic compliant ones. Further, Ramadan seasonality is more significant for non-Islamic compliant stocks. Chapter 4 investigates market inefficiency by considering two anomalies: investors’ herd behaviour and structural breaks in the Saudi stock market. The herd behaviour is investigated by estimating a nonlinear asymmetric cross-sectional absolute deviation model, whereas structural shifts are modelled by estimating a Markov regime switching model. The volatility models considered confirm that both Islamic law and immature behaviour of investors are important factors that contribute to informational imperfectness in the Saudi stock market

Modeling the volatility of Mediterranean stock markets: a regime-switching approach

In this paper we use the Markov regime-switching model to investigate the volatility behavior of six Mediterranean stock markets (France, Spain, Greece, Egypt, Tunisia, and Turkey) over the turbulent period 1995-2010. Our results show strong evidence of regime shifts in each of these markets. We also find that the Mediterranean developed markets are less affected by international market events such as Asian and Russian financial crisis than emerging markets.Stock return volatility, Markov regime-switching model, Mediterranean stock markets

ARE VOLATILITY EXPECTATIONS CHARACTERIZED BY REGIME SHIFTS? EVIDENCE FROM IMPLIED VOLATILITY INDICES

This paper examines nonlinearities in the dynamics of volatility expectations using benchmarks of implied volatility for the US and Japanese markets. The evidence from Markov regime-switching models suggests that volatility expectations are likely to be governed by regimes featuring a long memory process and significant leverage effects. Market volatility is expected to increase in bear periods and decrease in bull periods. Leverage effects constitute thus an important source of nonlinearities in volatility expectations. There is no evidence of long swings associated with financial crises, which do not have the potential of shifting volatility expectations from one regime to another for long protracted periods.Markov Regime Switching, Implied Volatility Index, Nonlinear Modelling.

Modelling exchange rate volatility with random level shifts

Recent literature has shown that the volatility of exchange rate returns displays long memory features. It has also been shown that if a short memory process is contaminated by level shifts, the estimate of the long memory parameter tends to be upward biased. In this article, we directly estimate a random level shift model to the logarithm of the absolute returns of five exchange rates series, in order to assess whether random level shifts (RLSs) can explain this long memory property. Our results show that there are few level shifts for the five series, but once they are taken into account the long memory property of the series disappears. We also provide out-of-sample forecasting comparisons, which show that, in most cases, the RLS model outperforms popular models in forecasting volatility. We further support our results using a variety of robustness checks

The Declining Equity Premium: What Role Does Macroeconomic Risk Play?

Aggregate stock prices, relative to virtually any indicator of fundamental value, soared to unprecedented levels in the 1990s. Even today, after the market declines since 2000, they remain well above historical norms. Why? We consider one particular explanation: a fall in macroeconomic risk, or the volatility of the aggregate economy. We estimate a two-state regime switching model for the volatility and mean of consumption growth, and find evidence of a shift to substantially lower consumption volatility at the beginning of the 1990s. We then show that there is a strong and statistically robust correlation between low macroeconomic volatility and high asset prices: the estimated posterior probability of being in a low volatility state explains 30 to 60 percent of the post-war variation in the log price-dividend ratio, depending on the measure of consumption analyzed. Next, we study a rational asset pricing model with regime switches in both the mean and standard deviation of consumption growth, where the probabilities of a regime change are calibrated to match estimates from post-war data. Plausible parameterizations of the model are found to account for a significant fraction of the run-up in asset valuation ratios observed in the late 1990s.Equity Premium, Macro Volatility