Guglielmo Maria Caporale

Global and Regional Spillovers in Emerging Stock Markets: A Multivariate Garch-in-Mean Analysis

This paper examines global (mature market) and regional (emerging market) spillovers in local emerging stock markets. Tri-variate VAR-GARCH(1,1)-in-mean models are estimated for 41 emerging market economies (EMEs) in Asia, Europe, Latin America, and the Middle East. The models capture a range of possible transmission channels: spillovers in mean returns, volatility, and cross-market GARCH-in-mean effects. Hypotheses about the importance of different channels are tested. The results suggest that spillovers from regional and global markets are present in the vast majority of EMEs. However, the nature of cross-market linkages varies across countries and regions. While spillovers in mean returns dominate in emerging Asia and Latin America, spillovers in variance appear to play a key role in emerging Europe. There is also some evidence of cross-market GARCH-in-mean effects. The relative importance of regional and global spillovers varies too, with global spillovers dominating in Asia, and regional spillovers in Latin America and the Middle East.

Causality and forecasting in incomplete systems

In this paper we examine how causality inference and forecasting within a bivariate VAR, consisting of y(t) and x(t), are affected by the omission of a third variable, w(t), which causes (a) none, (b) one, and (c) both variables in the bivariate system. We also derive conditions under which causality inference and forecasting are invariant to the selection of a bivariate or a trivariate model. The most general condition for the invariance of both causality and forecasting to model selection is shown to require the omitted variable not to cause any of the variables in the bivariate system, although it allows the omitted variable to be caused by the other two. We also show that the conditions for one-way causality inference to be invariant to model selection are not sufficient to ensure that forecasting will also be invariant to the model selected. Finally, we present a numerical illustration of the potential losses, in terms of the variance of the forecast, as a function of the forecast horizon and for alternative parameter values—they can be rather large, as the omission of a variable can make the incomplete model unstable.

Volatility transmission and financial crises

In this paper we examine the international transmission of the 1997 South East Asia financial crisis. We estimate a bivariate GARCH-BEKK model, and carry out LR tests for causality-in-variance with bootstrapped critical values. Three pairwise models are estimated for US, European, Japanese and South East Asian daily stock market returns. Volatility spillovers are found in all cases. The dynamics of the conditional volatilities differ, but causality links in the variance are found to be strong and bidirectional in normal periods, and unidirectional (from the markets in turmoil to the others) following the onset of the crisis, consistently with crisiscontingent models.

Stock Market Integration between Three CEECs, Russia and the UK

This paper estimates a tri-variate VAR-GARCH(1,1)-in-mean model to examine linkages between the stock markets of three Central and Eastern European countries (CEECs), specifically the Czech Republic, Hungary, and Poland, and both the UK and Russia. The adopted framework allows to analyse interdependence by estimating volatility spillovers, and also contagion by testing for possible shifts in the transmission of volatility following the introduction of the euro and EU accession. Further evidence on possible changes in the transmission mechanism (namely, on whether there is contagion) can be obtained by examining the conditional correlations implied by the estimated model over different time periods. The empirical findings suggest that there is significant co-movement (interdependence) of these CEEC markets with both the Russian and the UK ones. Furthermore, whilst the introduction of the euro has had mixed effects, EU accession has resulted in an increase in volatility spillovers between the three CEECs considered and the UK (contagion).

EU Banks Rating Assignments: Is there Heterogeneity between New and Old Member Countries?

We model EU countries’ bank ratings using financial variables and allowing for intercept and slope heterogeneity. Our aim is to assess whether “old” and “new” EU countries are rated differently and to determine whether “new” ones are assigned lower ratings, ceteris paribus, than “old” ones. We find that country-specific factors (in the form of heterogeneous intercepts) are a crucial determinant of ratings. Whilst “new” EU countries typically have lower ratings than “old” ones, after controlling for financial variables we also discover that all countries have significantly different intercepts, confirming our prior belief. This intercept heterogeneity suggests that each country’s rating is assigned uniquely, after controlling for differences in financial factors, which may reflect differences in country risk and the legal and regulatory framework that banks face (such as foreclosure laws). In addition, we find that ratings may respond differently to the liquidity and operating expenses to operating income variables across countries. Typically ratings are more responsive to the former and less sensitive to the latter for “new” EU countries compared with “old” EU countries.

Common stochastic trends and inflation convergence in the EMS

Common Stochastic Trends and Inflation Convergence in the EMS. — This article seeks to clarify the relationship between the concept of convergence and univariate and cointegration analysis by looking at inflation convergence within the EMS. We take issue with the view put forward by Artis and Nachane, who hold that cointegration of inflation in Germany with inflation in the other EMS countries is a necessary condition for the “german leadership” thesis to stand. We think that, on the contrary, as long as convergence is still in the process of being achieved, inflation differentials are likely to be non-stationary and, if so, to exhibit common stochastic trends. However, our empirical results, based on Phillips-Perron tests and on the maximum likelihood framework developed by Johansen to test for common trends and cointegration, confirm the validity of the German leadership hypothesis.ZusammenfassungGemeinsame stochastische Trends und Konvergenz der Inflation im EWS. — In diesem Aufsatz soll die Beziehung zwischen dem Konzept der Konvergenz und univariater Kointegrations-Analyse geklärt werden, indem die Inflationskonvergenz im EWS betrachtet wird. Ausgangspunkt ist die Ansicht von Artis und Nachane, die die Kointegration der Inflation in Deutschland mit der in den anderen EWS-Ländern als eine notwendige Bedingung für die These von der “deutschen Führung” ansehen. Dagegen wird hier die Ansicht vertreten, daβ - solange sich die Konvergenz noch herausbildet - die Inflationsunterschiede eher nichtstationär sind und demnach gemeinsame stochastische Trends aufweisen. Die empirischen Ergebnisse, die auf Phillips-Perron-Tests und auf dem von Johansen im Rahmen der Methode der gröβten Dichte entwickelten Verfahren zur Prüfung von gemeinsamen Trends und Kointegration beruhen, bestätigen allerdings die Hypothese der deutschen Führungsrolle.

Time-Varying Spot and Futures Oil Price Dynamics

We investigate the role of crude oil spot and futures prices in the process of price discovery by using a cost-of-carry model with an endogenous convenience yield and daily data over the period from January 1990 to December 2008. We provide evidence that futures markets play a more important role than spot markets in the case of contracts with shorter maturities, but the relative contribution of the two types of market turns out to be highly unstable, especially for the most deferred contracts. The implications of these results for hedging and forecasting crude oil spot prices are also discussed.

Testing for convergence in stock markets: a non-linear factor approach

This paper applies the Phillips and Sul (2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US over the period 1973-2008. We carry out the analysis on both sectors and individual industries within sectors. As a first step, we use the Stock and Watson (1998) procedure to filter the data in order to extract the long-run component of the series; then, following Phillips and Sul (2007), we estimate the relative transition parameters. In the case of sectoral indices we find convergence in the middle of the sample period, followed by divergence, and detect four (two large and two small) clusters. The analysis at a disaggregate, industry level again points to convergence in the middle of the sample, and subsequent divergence, but a much larger number of clusters is now found. Splitting the cross-section into two subgroups including Euro area countries, the UK and the US respectively, provides evidence of a global convergence/divergence process not obviously influenced by EU policies.

Nonlinearities and Fractional Integration in the US Unemployment Rate

This paper proposes a model of the US unemployment rate which accounts for both its asymmetry and its long memory. Our approach, based on the tests of Robinson (1994), introduces fractional integration and nonlinearities simultaneously into the same framework (unlike earlier studies employing a sequential procedure), using a Lagrange Multiplier procedure with a standard limit distribution. The empirical results suggest that the US unemployment rate can be specified in terms of a fractionally integrated process, which interacts with some non-linear functions of the labour demand variables (real oil prices and real interest rates). We also find evidence of a long-memory component. Our results are consistent with a hysteresis model with path dependency rather than a NAIRU model with an underlying unemployment equilibrium rate, hence giving support to more activist stabilisation policies. However, any suitable model should also include business cycle asymmetries, with implications for both forecasting and policymaking.

Liquidity Risk, Credit Risk and the Overnight Interest Rate Spread: A Stochastic Volatility Modelling Approach

In this paper we model the volatility of the spread between the overnight interest rate and the central bank policy rate (the policy spread) for the euro area and the UK during the two main phases of the financial crisis that began in late 2007. During the crisis, the policy spread exhibited signs of volatility, owing to the breakdown in interbank market activity. The determinants of this volatility are assessed using Stochastic Volatility models to gauge the role played by liquidity risk, credit risk (financial and sovereign), and interest rate expectations. Our results suggest that liquidity risk is the main determinant of the volatility of the policy spread, but also that private bank credit risk has become more apparent in the post-Lehman collapse phase of the crisis for the euro area as financial CDS premia rose due to possible default fears. In addition, the ECB appears to have been more effective in addressing liquidity risk since the onset of the crisis, and this may be related to its greater direct access to a broader range of counterparties and its acceptance of a broader range of eligible collateral. The main implication is that, in crisis times, a sufficiently flexible operational framework for monetary policy implementation produces the most timely response to market tensions.