Angelos Kanas

Linkages between the US and European equity markets: further evidence from cointegration tests

The paper employs the multivariate trace statistic P-super-ˆz, the Johansen method, and the recently proposed Bierens nonparametric approach to test for pairwise cointegration between the US and each of the six largest European equity markets, namely those of the UK, Germany, France, Switzerland, Italy, and the Netherlands. The analysis covers the period 03/01/83-29/11/96. The results from these tests are robust and consistent in suggesting that the US market is not pairwise cointegrated with any of the European markets, which is in contrast to previous evidence on the linkages between the US and European markets. This finding implies that there exist potential long-run benefits in risk reduction from diversifying in US stocks and stocks in any of the major European markets.

Volatility Spillovers Between Stock Returns and Exchange Rate Changes: International Evidence

We investigate interdependencies between stock returns and exchange rate changes for six industrialised countries, namely the US, the UK, Japan, Germany, France and Canada, by testing for volatility spillovers using a bivariate EGARCH model. Volatility spillovers from stock returns to exchange rate changes are found for all countries except Germany. These spillovers are symmetric in nature. No evidence is found of volatility spillovers from exchange rate changes to stock returns for any country. Spillovers from stock returns to exchange rate changes have increased since October 1987. This finding is consistent with the notion that international financial markets have become increasingly integrated. Copyright Blackwell Publishers Ltd 2000.

Volatility spillovers across equity markets: European evidence

This paper examines the issue of volatility spillovers across the three largest European stock markets, namely London, Frankfurt and Paris. The Exponential Generalized Autoregressive Conditional Heteroscedasticity model is used to capture potential asymmetric effects of innovations on volatility. During the period from 01/01/84 to 07/12/93, reciprocal spillovers are found to exist between London and Paris, and between Paris and Frankfurt, and unidirectional spillovers from London to Frankfurt. In almost all cases, spillovers are asymmetric in the sense that bad news in one market has a greater effect on the volatility of another market than good news. An analysis for the pre-crash (01/01/84 - 15/09/87) and post-crash (15/11/87 - 07/12/93) periods suggests that more spillovers and spillovers with higher intensity exist during the latter period. These findings suggest that these markets became more interdependent during the post-crash period.

Testing for a nonlinear relationship among fundamentals and exchange rates in the ERM

We employ two nonparametric nonlinear testing methodologies, namely a nonparametric nonlinear cointegration approach and a nonlinear Granger causality approach, to test for a nonlinear relationship between macroeconomic fundamentals and exchange rates for two country-pairs, namely the Netherlands–Germany and France–Germany. The results suggest that there is nonlinear cointegration among money, output and exchange rates for Netherlands–Germany, which can be interpreted as evidence of a long-run nonlinear relationship. For France–Germany, we fail to find evidence of nonlinear cointegration, but we find nonlinear Granger causality from French money to the FFr/DM exchange rate. These findings may be interpreted as evidence of a dynamic nonlinear relationship and are consistent with the German dominance hypothesis. On the basis of estimated fractional ARIMA models, we rejected the hypothesis that these nonlinearities are due to bubbles.

Comparing linear and nonlinear forecasts for stock returns

Abstract We compare the out-of-sample performance of monthly returns forecasts for two indices, namely the Dow Jones (DJ) and the Financial Times (FT) indices. A linear and a nonlinear artificial neural network (ANN) model are used to generate the out-of-sample competing forecasts for monthly returns. Stationary transformations of dividends and trading volume are considered as fundamental explanatory variables in the linear model and the input variables in the ANN model. The comparison of out-of-sample forecasts is done on the basis of forecast accuracy, using the Diebold and Mariano test [J. Bus. Econ. Stat. 13 (1995) 253.], and forecast encompassing, using the Clements and Hendry approach [J. Forecast. 5 (1998) 559.]. The results suggest that the out-of-sample ANN forecasts are significantly more accurate than linear forecasts of both indices. Furthermore, the ANN forecasts can explain the forecast errors of the linear model for both indices, while the linear model cannot explain the forecast errors of the ANN in either of the two indices. Overall, the results indicate that the inclusion of nonlinear terms in the relation between stock returns and fundamentals is important in out-of-sample forecasting. This conclusion is consistent with the view that the relation between stock returns and fundamentals is nonlinear.

Modeling Traffic Volatility Dynamics in an Urban Network

This article discusses the application of generalized autoregressive conditional heteroscedasticity (GARCH) time series models for representing the dynamics of traffic flow volatility. The methods encountered in the literature focus on the levels of traffic flows and assume that variance is constant through time. The approach adopted in this paper concentrates primarily on the autoregressive properties of traffic variability, with the aim to provide better confidence intervals for traffic flow forecasts. The model-building procedure is illustrated with 7.5-min average traffic flow data for a set of 11 loop detectors located at major arterials that direct to the center of the city of Athens, Greece. A sensitivity analysis for coefficient estimates is undertaken with respect to both time and space.

Purchasing Power Parity and Markov Regime Switching

We revisit the evidence on PPP in the twentieth century allowing for Markov regime switching in the ADF regression. Using Lopez et al.s (2005) extension of Taylors (2002) original data set, our results are: (1) For most countries, there are periods over which the real exchange rate is stationary and PPP holds, and periods over which the real exchange rate is non-stationary and PPP does not hold, namely, regime-dependent stationarity. Thus, real exchange rate stationarity is a stochastic event itself. (2) The probability that the real exchange rate is stationary is less than 50% for most countries. (3) There is evidence of non-stationarity during both the Bretton Woods and the recent float periods for the majority countries. The comparative performance of PPP is slightly better during Bretton Woods than the recent float.

Is exchange rate volatility influenced by stock return volatility? Evidence from the US, the UK and Japan

This study investigates whether the volatility of exchange rate changes is affected by the volatility of stock returns for three industrialized countries, namely the US, the UK and Japan. These findings suggest that the volatility of home stock returns is a significant determinant of the volatility of exchange rate changes in all three countries, supporting the validity of the asset approach models to exchange rates for the US, the UK and Japan. Moreover, these results can be interpreted as evidence that the financial markets in these countries are integrated, in line with Zapatero (1995).

Is economic exposure asymmetric between long-run depreciations and appreciations? Testing using cointegration analysis

Abstract Theoretical models of pricing-to-market suggest that the profile of economic exposure may be asymmetric between periods when the real exchange rate appreciates and periods when it depreciates. We test this hypothesis using time-series data on export prices for eight commodities exported from the UK to the US during the period 1981–1988. During this period, there was a long-term real depreciation of the £ against the

Mean and Variance Causality between Official and Parallel Currency Markets: Evidence from Four Latin American Countries

(1981 I–1985 I) followed by a long-term real appreciation (1985 II–1988 IV). To test for cointegration between the export price of each commodity and the real exchange rate, we apply the Phillips and Ouliaris (1990) and Johansen and Juselius (1990) methods. As the latter allows linear restrictions on the cointegrating vector to be imposed and tested for directly, we adopt the Johansen and Juselius method and impose a linear restriction on the cointegrating vector to test for asymmetry. The results are generally in favour of this hypothesis. The implication for financial hedging against economic exposure is that currency options should be preferred to forwards, futures or swaps contracts.