Long range dependence in an emerging stock market’s sectors: volatility modelling and VaR forecasting

This study evaluates the sector risk of the Qatar Stock Exchange (QSE), a recently upgraded emerging stock market, using value-at-risk models for the 7 January 2007–18 October 2015 period. After providing evidence for true long memory in volatility using the log-likelihood profile test of Qu and splitting the sample and dth differentiation tests of Shimotsu, we compare the FIGARCH, HYGARCH and FIAPARCH models under normal, Student-t and skewed-t innovation distributions based on in and out-of-sample VaR forecasts. The empirical results show that the skewed Student-t FIGARCH model generates the most accurate prediction of one-day-VaR forecasts. The policy implications for portfolio managers are also discussed.     

New estimates of time-varying currency betas: A trivariate BEKK approach

This paper examines the conditional time-varying currency betas from five developed markets and four emerging markets. We employ a modified trivariate BEKK-GARCH-in-mean model of Engle and Kroner (1995) to estimate the time-varying conditional variance and covariance of returns of stock index, the world market portfolio and changes in bilateral exchange rate between the US dollar and the local currency. It is found that currency betas are more volatile than those of the world market betas. Currency betas in emerging markets are more volatile than those in the developed markets. Moreover, we find evidence of long-memory in currency betas. The usefulness of time-varying currency betas are illustrated by two applications.     

银行危机与货币危机共生性关系的实证研究

1 997— 1 998年的亚洲金融风暴中 ,银行危机与货币危机的同时爆发 ,即共生性危机的发生引发国际社会与学术界对这种现象的重新思考 :这种共生性现象是否确实具有普遍性 ?从理论的角度来看 ,银行危机与货币危机之间的确存在着一定的联系 ,但到目前为止 ,很少有研究从实证的角度来证明这种联系的确存在。正是基于此 ,本文从实证的角度出发 ,旨在揭示出银行危机与货币危机之间的确存在着相互影响 ,换言之 ,共生性危机的发生是具有显著性的。具体来说 ,本文以 1 975— 2 0 0 0年期间 53个国家危机的发生情况为研究对象 ,分别运用频率分布、信号法 ,以及概率回归模型来分析两种危机的共生性 ,并得到非常一致的结论 :在新兴市场国家中 ,银行危机与货币危机之间的确存在着明显的相互关系 ,同时银行危机更趋向于作为货币危机即将发生的同步或预警指标 ,而反之则不然。     

Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash

Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.     

German stock market dynamics

This article estimates generalized ARCH (GARCH) models for German stock market indices returns, using weekly and monthly data, various GARCH specifications and (non)normal error densities, and a variety of diagnostic checks. German stock return series exhibit significant levels of second-order dependence. Our results clearly demonstrate that for both weekly as well as monthly return series the Student-t distribution is superior to the standard normal distribution. In particular, the estimated GARCH-t models appear to be reasonably successful in accounting for both observed leptokurtosis and conditional heteroskedasticity from German stock return movements.     

Global money market interrelationships

This study extends the literature dealing with money market interrelationships by analyzing the behavior of yields on assets denominated in five major world currencies in three different geographic markets within a multivariate cointegration framework. Basic findings include: (1) same currency money market yields are cointegrated across countries; (2) domestic markets and the Eurocurrency markets are closely linked, as are the Eurocurrency markets and the Asian currency markets; (3) the relationships between domestic markets and the Asian offshore markets are the weakest of those tested; and (4) only one common factor in three geographic markets indicates a global market, whereas significant causal effects suggest that a degree of market segmentation remains.     

Dynamic conditional score models: a review of their applications

ABSTRACT

In this paper, applications of dynamic conditional score (DCS) models are reviewed and those models are discussed in relation to classical time series models from the literature. DCS models are robust to outliers, which improves their statistical performance compared to classical models. Three applications are presented in order to compare the statistical performances of DCS and classical models in three very different contexts: (i) The QAR (quasi-autoregressive) plus Beta-t-EGARCH (exponential autoregressive conditional heteroscedasticity) model is presented, which is a score-driven expected return plus volatility model. This model is used for daily returns on the DAX (Deutscher Aktienindex) equity index for the period of January 1988 to December 2017. (ii) The score-driven local level and seasonality plus Beta-t-EGARCH model is presented, which is used for daily AFN/USD (Afghan Afghani/United States Dollar) currency exchange rates for the period of March 2007 to July 2017. (iii) The Seasonal-t-QVAR (quasi-vector autoregressive) model is presented, which is a score-driven multivariate dynamic model of location. For this model, monthly US inflation rate and US unemployment rate are used for the period of January 1948 to December 2017. For all applications, the statistical performance of each DCS model is superior to that of a corresponding classical alternative.     

Exchange-rate pass-through and market structure

We consider a situation in whichn firms located in market 1 andm firms located in market 2 each sell a commodity which is homogeneous within each market but may differ between markets. All firms sell on both markets. Each market has its own currency. The market demand functions differ. We give some basic results on the effects of exchange-rate changes and then show the following. When these markets are independent on the cost side (constant marginal costs) and demands are linear, a reduction in the number of firms (which might result from a merger) in market 1 increases the pass-through (of an appreciation of currency 2) in market 1 and decreases the pass-through in market 2. A similar occurrence in market 2 has the opposite effect. We give conditions under which, with identical economies of scope linking the markets, the sign of the price changes will be reversed when the number of foreign firms is small enough compared to the number of local firms. However, such sign reversals cannot occur in the two markets simultaneously.     

The Role of Foreign Bond Issuance: The Case of Australia

We examined the recent development of the foreign bond—termed Kangaroo bond—market in Australia. Overwhelmingly, issuers in this market are of high credit quality and comprise sovereign, supranational and major international financial institutions. Local institutional investors have a preference for simple, fixed‐rate pricing structures, with foreign issuers reliant upon converting their Australian dollar‐denominated bond proceeds into the currency and coupon type of choice using cross‐currency swaps. The Kangaroo bond issuers provide a natural counterparty to Australian residents issuing in foreign currency in offshore markets, where cross‐currency swaps allow them to easily convert their proceeds into Australian dollars.     

Time-varying global and local sources of market and currency risks in Russian stock market

In this paper we study international asset pricing models and the pricing of global and local market risks as well as currency risk in the Russian stock market from an international investors' point of view using weekly data from 1999 to 2009. In our empirical specification, we utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). We find currency risk to be priced in the Russian market. The price of currency risk is found to be time-varying and affected for example by the price of oil. Moreover, our results suggest that the Russian market is partially segmented and the local market risk is priced in the market. Our model implies in-sample risk premium for the Russian equity market that is, on average, almost ten times higher than that of the US and that the Russian risk premium is on average caused mostly by the local and currency risk components.     

When Carry Trades in Currency Markets are not Profitable

The success of the carry trade in international currency and money markets is related to the extent of the forward premium anomaly. We present evidence that the anomaly is a very time dependent phenomenon. We also formulate a model where the ex post returns from the carry trade are functionally related to the relative difference between the interest rate on the funding currency and the interest rate associated with the target currency; i.e. the relative interest rate opportunity (RIRO). We estimate a nonlinear smooth transition regime model that relates the RIRO to the returns on the carry trade, and the estimated transition function then represents the time periods when the carry trade was profitable and when it was not. The analysis indicates that the desirability of carry trading has declined and for many currencies has actually become unprofitable since the financial crisis of 2008.     

Stock market comovements in Central Europe: Evidence from the asymmetric DCC model

We examine time-varying stock market comovements in Central Europe employing the asymmetric dynamic conditional correlation multivariate GARCH model. Using daily data from 2001 to 2011, we find that the correlations among stock markets in Central Europe and between Central Europe vis-à-vis the euro area are strong. The correlations increased over time, particularly after their EU entry and largely remained at these levels during the financial crisis. The stock markets exhibit asymmetry in the conditional variances and to a certain extent in the conditional correlations as well, pointing to the importance of applying a sufficiently flexible econometric framework. The conditional variances and correlations are positively related, suggesting that the diversification benefits decrease disproportionally during volatile periods.     

Exchange Rate Movements and Unemployment in the EU Accession Countries—A Panel Analysis

According to the traditional “optimum currency area” approach, not much will be lost from a very hard peg to a currency union if there has been little reason for variations in the exchange rate. This paper takes a different approach, and highlights the fact that high exchange rate volatility may as well signal high costs for labor markets. The impact of exchange rate volatility on labor markets in the CEECs is put to the test, finding that volatility vis‐à‐vis the euro significantly increases unemployment. Hence, the elimination of exchange rate volatility could be considered as a substitute for a removal of employment protection legislation. However, labor market reform could be argued to be an equally worthy strategy, backed up by central bank independence and the adoption of an anti‐inflation monetary policy rule.     

The demise of commodity price agreements: the role of exchange rates and special interests

We derive the equilibrium joint distribution of exchange rate and commodity price in a two-country rational expectations model. The correlation between commodity price and exchange rate appears crucial for the stability of commodity markets. This result arises from the common practice to quote commodity prices in consuming countries' currency, which subjects producing countries to the currency risk. Welfare results of commodity price stabilization are obtained and facilitate the interpretation of the position taken by industrialized countries long opposed to international commodity agreements. We apply our model to the Philippines and investigate the potential effects of the International Sugar Agreement (ISA) on the various conditional volatilities of the model. We conclude on the relative ineffectiveness of these agreements in limiting fluctuations of sugar prices.     

Analysis of contagion from the dynamic conditional correlation model with Markov Regime switching

Over the last decades, the transmissions of international financial events have been the subject of many academic studies focused on multivariate volatility models. This study evaluates the financial contagion between stock market returns. The econometric model employed, regime switching dynamic correlation (RSDC). A modification was made in the original RSDC model, the introduction of the GJR-GARCH-N and also GJR-GARCH-t models, on the equation of conditional univariate variances, thus allowing us to capture the asymmetric effects in volatility and also heavy tails. A database was built using series of indices in the United States (S&P500), the United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) from 1 February 2003 to 20 September 2012. Throughout this study the methodology is compared with those frequently found in literature, and the model RSDC with two regimes was defined as the most appropriate for the selected sample with t-Student distribution in the disturbances. The adapted RSDC model used in this article can be used to detect contagion – considering the definition of financial contagion from the World Bank called very restrictive – with the help of the empirical exercise.     

State dependence,serial correlation and heterogeneity in the union membership dynamics

In order to distinguish the true and spurious state dependence from the complicated dynamics of union membership, the simulation estimators incorporating the lagged dependent variables, unobserved individual heterogeneity and correlations among the errors are implemented in this article to study union membership dynamics. It is found that the true state dependence of union membership under multivariate t assumption is much higher than the standard dynamic panel probit estimators which are under multivariate normal assumptions. On the other hand, the spurious state dependence (the variance of the unobserved individual heterogeneity) is estimated to be higher when using the standard dynamic panel probit estimators than under multivariate t assumption. Moreover, blacks and married men are found to have higher union membership true state dependence than whites and unmarried men.     

Inconsistency of estimate of the degree of freedom of multivariate student-t disturbances in linear regression models

A moment estimator for the degree of freedom of the jointly multivariate student-t distribution of the disturbances in a linear regression model has been suggested by Singh [Economic letters (1988) 27, 47–53]. In this paper we will show that the distribution of the moment estimate is independent of the true value of the degree of freedom and the estimate converges to infinite in probability as the sample size goes to infinite. Our results show that the moment estimate does not provide any information on the degree of freedom.     

Financial crises and dynamic linkages across international stock and currency markets

This paper investigates contagion across stock and currency markets of China, Eurozone, India, Japan and US during global financial crisis and Eurozone crisis. The crisis periods are selected using Markov-switching models for US and Eurozone markets. We, then, utilize the DCC-GARCH model to estimate conditional correlation among the assets and test for contagion/flight to quality effects during the crises. The results show significant contagion as well as flight to quality effects both across and within asset classes. We examine the impact of financial stress index on the correlation across markets and find that portfolio diversification benefits for equity markets may be non-existent.     

Are exchange rates interdependent? Evidence using wavelet analysis

We examine the co-movement in daily returns of USD–INR, EUR–INR, GBP–INR, and JPY–INR currency pair futures contracts traded on the National Stock Exchange of India (NSE) using the wavelet cohesion approach. This study contributes to the literature by examining the scantly studied area of co-movement in exchange rates and using the wavelet approach, which allows us to analyse time–frequency-wise co-movement of the time series. The empirical results indicate that the currency futures markets are nearly perfectly integrated in the long run (monthly, quarterly and biannual scales) offering little potential gains from international portfolio diversification. The discrepancies between currency futures markets are small and almost fade away within 3–6 months. Moreover, international currency diversification might offer relatively higher potential gains at intraweek, weekly, and fortnightly time horizons owing to lower correlations among the currencies under consideration. Finally, our multiple-wavelet correlation and cross-correlation analysis shows that GBP acts as a potential leader/follower across scales. The results of our analysis indicate the dynamic pattern of co-movement among the major currency futures contracts, which provides several implications for portfolio managers and international investors participating in the Indian market.     

Return and volatility transmission between oil prices and oil-exporting and oil-importing countries

This paper provides further evidence of the comovements and dynamic volatility spillovers between stock markets and oil prices for a sample of five oil-importing countries (USA, Italy, Germany, Netherland and France) and four oil-exporting countries (United Arab Emirates, Kuwait, Saudi Arabia and Venezuela). We make use of a multivariate GJR-DCC-GARCH approach developed by Glosten et al. (1993). The results show that: i) dynamic correlations do not differ for oil-importing and oil-exporting economies; ii) cross-market comovements as measured by conditional correlation coefficients increase positively in response to significant aggregate demand (precautionary demand) and oil price shocks due to global business cycle fluctuations or world turmoil; iii) oil prices exhibit positive correlation with stock markets; and iv) oil assets are not a good ‘safe haven’ for protection against stock market losses during periods of turmoil.