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We analyze the effectiveness of intervention in the European Monetary System by using daily data on the DEM-intervention activity of six European central banks, covering the period from August 1993 to April 1998. To test for the influence of intervention we apply EGARCH models. To allow for regime specific intervention effects we also estimate Markov Switching autoregressive conditional heteroscedasticity (MS-ARCH) models. The results from the EGARCH models show that interventions influenced the conditional mean in only one case. Both volatility increasing and decreasing effects are found for the conditional variance. In the MS-ARCH model more effects on the mean are found. If significant, intervention tends to affect the level of the six ERM I exchange rates only in periods of low and medium volatility. For the conditional variance more volatility decreasing than increasing effects are found. Overall, given our approaches (EGARCH and MS-ARCH), the results show that even in the same institutional framework, intervention does not seem to affect the means and variances in a consistent and predictable manner.

We propose a new time series representation of persistence in conditional variance called a long memory stochastic volatility (LMSV) model. The LMSV model is constructed by incorporating an ARFIMA process in a standard stochastic volatility scheme. Strongly consistent estimators of the parameters of the model are obtained by maximizing the spectral approximation to the Gaussian likelihood. The finite sample properties of the spectral likelihood estimator are analyzed by means of a Monte Carlo study. An empirical example with a long time series of stock prices demonstrates the superiority of the LMSV model over existing (short-memory) volatility models. info:eu-repo/semantics/publishedVersion

International financial integration effects on Spanish stock market are studied, both for the conditional mean and conditional variance. New institutional regulations in Spain are taken into account and its efficiency consequences are addressed. Results suggest an increasing international integration but nontrivial opportunities for financial diversification may still be relevant.

During the last few years there has been an increasing interest in modelling time-varying volatilities of high frequency financial time series. Several models have been proposed, being the most popular between econometricians the autoregressive conditional heteroscedasticity (ARCH) based models. However, in the financial literature stochastic volatility (SV) models have been widely used, mainly when dealing with option valuation models. Both kinds of models imply similar statistical properties on the returns series and both are able of explaining the stilized facts often observed in empirical time series of returns (high kurtosis, autocorrelations of the squares etc;). It is of interest to apply each of these alternative models to the same data set, with the aim of investigating the different implications each might have for the predictability of volatility. In particular, we consider three models, GARCH(l,l), EGARCH(l,l) and AR(l)-SV, and fit each of them to four daily exchange rates. Comparisons are made between the corresponding univariate models. The main conclusion is that there are important differences between the models in the one-step-ahead predictions of volatility. SV models fit better in the center of the distribution of returns while GARCH and EGARCH models are better in the tails of the distribution.

This paper analyzes the time-series variation in the return volatility of non-US stocks from emerging markets that are cross-listed on US exchanges. Unlike previous studies in the cross-listing literature, return volatility is modeled using conditional heteroscedasticity models. We find that firms' exposure to risks such as local and global market betas remain unchanged after cross-listing. Moreover, we do not identify notable changes in the dynamics of the volatility of cross-listed stocks after cross-listing except for leverage effects. We further show that the mean level of conditional variance is not affected after cross-listing. Thus, our results provide counter-evidence to the belief that foreign investor participation drives volatility upward.

This study examines the return and volatility behaviour of Borsa Istanbul Real Estate Investment Trusts (REITs) Index and Borsa Istanbul 100 (BIST 100) Index. It focuses on three main points. First, we search whether there are variations in index returns and volatilities by days of the week, months of the year, and turn of the month patterns. Second, we ask whether REITs Index performance is closely related to stock market performance. Third, we test whether the abnormal returns in the process have significant effects on the index returns and volatilities. Results reveals that calendar anomalies still exist and the volatility pattern across days of the week and months of the year are statistically different. The return pattern observed between REITs and BIST 100 index is strong enough. REITs performance is closely related to stock market performance. BIST 100 abnormal returns have also significant effects on BIST 100 and REITs returns and volatilities. This study performs GARCH and EGARCH methodologies to and finds significant implications for local and international investors for designing trading strategies, drawing investment decisions, risk management, timing of security issuances by firms, asset pricing and performance evaluation. © 2015, Institute foe Economic Forecasting. All rights reserved.

Namibia introduced the “Small Stock Marketing Scheme†(SSMS) in 2004 which replaced 15% export duty on live sheep exports to South Africa with progressively demanding quantitative restrictions. This policy increased price volatility in the Namibian sheep market. We used relevant monthly price data and employed EGARCH modeling to determine if price volatility spilled-over from the sheep market in Namibia to South African sheep market. About 71 percent of the volatility in the Namibian sheep market is transmitted to the retail market in South Africa and the transmitted volatility remains persistent.

International audience; —Based on a survey of 203 Insurance equities from European capital markets over the 2001-2014 period, this article analyses the role of idiosyncratic risk in the pricing of European insurance equities. The capital asset pricing model predicts that in equilibrium, investors should hold the market portfolio. As a result, investors should only be rewarded for carrying undiversifiable systematic risk and not for diversifiable idiosyncratic risk. The framework of Fama and MacBeth is employed. Regressions of the cross-section of expected equity excess returns on idiosyncratic risk and other firm characteristics such as beta, size, book-to-market equity (BE/ME), momentum, liquidity and co-skewness are performed. The empirical models reveal that the largest part of total volatility is idiosyncratic and therefore firm specific in nature. Simple cross-correlations indicate that high beta, small size, high BE/ME, low momentum, low liquidity and high co-skewness equities have higher idiosyncratic risk.

Background The purpose of this study is to examine volatility spillover effects between stock market and foreign exchange market in selected Asian countries; Pakistan, India, Sri Lanka, China, Hong Kong and Japan. This study considered daily data from 4th January, 1999 to 1st January, 2014. Methods This study opted EGARCH (Exponential Generalized Auto Regressive Conditional Heteroskedasticity) model for the purpose of analyzing asymmetric volatility spillover effects between stock and foreign exchange market. Results The EGARCH analyses reveal bidirectional asymmetric volatility spillover between stock market and foreign exchange market of Pakistan, China, Hong Kong and Sri Lanka. The results reveal unidirectional transmission of volatility from stock market to foreign exchange market of India. The analysis reveals no evidence of volatility transmission between the two markets in reference to Japan. Conclusions The result of this study provide valuable insights to economic policy makers for financial stability perspective and to investors regarding decision making in international portfolio and currency risk strategies.

This paper utilizes three univariate ARCH-type models to empirically examine persistence and asymmetry in volatility of prices of primary agricultural commodities produced in Sub-Sahara Africa. Maximum likelihood estimation results of the three models ranked the GARCH version as the best statistical fit, lending support for hypotheses of persistence, symmetry and variability in volatility. This pattern of volatility could effectively jeopardize the success of traditional commodity price risk management policies used in this region. Policymakers should appreciate potential benefits associated with market-based strategies for managing commodity exposure of these countries.