Dimitris A. Georgoutsos

Benchmark Bonds Interactions Under Regime Shifts

In the present paper we examine interactions among five benchmark ten year government bonds, namely those of the US, Germany, France, Italy and the Netherlands. Our aim is to illustrate empirically a network of interactions existing among the major bond markets of Europe and the US market taking into account shifts in the underlying stochastic processes. For this purpose, and in contrast to the rest of the relevant empirical literature, after specifying the long-run equilibrium relations we estimate the linkages between the bond markets as subject to hidden Markov chains, by applying the Markov Switching Vector Error Correction framework (MS-VECM). This formulation is found to efficiently reflect the shifts brought about by significant economic events, such as the European monetary unification. As a result we illustrate different short-run relations referring to the periods before and after monetary union. Overall, our empirical results indicate that stronger interactions between the markets of the system exist in the period after the EMU. Also, by means of a variance decomposition analysis we assess leader-follower relations which indicate that the benchmark status of bonds has changed since the introduction of the common monetary policy framework in Europe.

The monetary model in the presence of I(2) components: long-run relationships, short-run dynamics and forecasting of the Greek drachma

This paper re-examines the long-run properties of the monetary exchange rate model using data for the drachma–dollar and drachma–mark exchange rates under the hypothesis that the system contains variables that are I(2). Using the recent I(2) test by Paruolo (On the determination of integration indices in I(2) systems. J. Economet. 72 (1996) 313–356) to examine the presence of I(2) and I(1) components in a multivariate context we find that the system contains two I(2) variables in both cases and this finding is reconfirmed by the estimated roots of the companion matrix (Do purchasing power parity and uncovered interest rate parity hold in the long-run? An example of likelihood inference in a multivariate time-series model. Juselius, J. Economet. 69 (1995) 211–240). The I(2) component led to the transformation of the estimated model by imposing long-run but not short-run proportionality between domestic and foreign money. Two statistically significant cointegrating vectors were found and, by imposing linear restrictions on each vector as suggested by Johansen and Juselius (Identification of the long-run and the short-run structure: an applicaion to the ISLM model. J. Economet. 63 (1994) 7–36) and Johansen (Identifying restrictions of linear equations with applications to simultaneous equations and cointegration. J. Economet. 69 (1995b) 111–132), the order and rank conditions for identification are satisfied, but the test for overidentifying restrictions was not significant only for the case of the drachma/mark rate. The main findings suggest that we reject the forward-looking version of the monetary model for the drachma/dollar case but not when the drachma/mark rate is used, a result that is attributed to the monetary and exchange rate policy followed by the Greek authorities since Greeces joining of the European Union. Furthermore, we test for parameter stability using the tests developed by Hansen and Johansen (Recursive estimation in cointegrated VAR-models. Working paper (1993) University of Copenhagen) and it is shown that the dimension of the cointegration rank is sample independent while the estimated coefficients do not exhibit instabilities in recursive estimations. Finally, it is shown that the monetary model outperforms the random walk model in an out-of-sample forecasting contest.

The monetary approach to the exchange rate: Long-run relationships, identification and temporal stability*

This paper re-examines the monetary model of exchange rate determination from a long-run perspective using data for three key U.S. dollar bilateral exchange rates. A novel feature of the analysis is the implementation of the testing procedure suggested by Paruolo (1996) to examine for the presence of I(2) and I(1) components in a multivariate context. Furthermore, we consider the cointegration rank utilizing the maximum likelihood cointegration technique proposed by Johansen, 1988 , Johansen, 1991 as well as the estimated roots of the companion matrix ( Juselius 1995 ). Two statistically significant cointegrating vectors were identified and by imposing linear restrictions on each vector as suggested by Johansen and Juselius (1994) the order and rank conditions for identification are satisfied, but all tests for overidentifying restrictions were significant. The main findings suggest that we reject the forward-looking version of the monetary model but the unrestricted monetary model is a valid framework for explaining the long-run movements of these exchange rates. Finally, we test for parameter stability using the tests developed by Hansen and Johansen (1993) and it is shown that the dimension of the cointegration rank may be sample dependent while the estimated coefficients do not exhibit instabilities in recursive estimations.

Evaluating direction-of-change forecasting: Neurofuzzy models vs. neural networks

This paper investigates the nonlinear predictability of technical trading rules based on a recurrent neural network as well as a neurofuzzy model. The efficiency of the trading strategies was considered upon the prediction of the direction of the market in case of NASDAQ and NIKKEI returns. The sample extends over the period 2/8/1971-4/7/1998 while the sub-period 4/8/1998-2/5/2002 has been reserved for out-of-sample testing purposes. Our results suggest that, in absence of trading costs, the return of the proposed neurofuzzy model is consistently superior to that of the recurrent neural model as well as of the buy & hold strategy for bear markets. On the other hand, we found that the buy & hold strategy produces in general higher returns than neurofuzzy models or neural networks for bull periods. The proposed neurofuzzy model which outperforms the neural network predictor allows investors to earn significantly higher returns in bear markets.

Extreme returns and the contagion effect between the foreign exchange and the stock market: evidence from Cyprus

In this article we apply the Extreme Value Theory (EVT) in order to estimate the Value-at-Risk (VaR) and the correlation of extreme returns for two inherently unstable markets; the foreign exchange and the stock market. We also derive the corresponding VaR estimates from more ‘traditional’ methods of estimation on daily returns of the US dollar/Cyprus pound exchange rate and the Cyprus stock exchange general index. The main conclusion we reach is that the more heavy-tailed distributed a series is the more accurate the loss predictions are from the application of the EVT. We also show that the conditional correlation index of the extreme returns of those two markets remained almost constant throughout the backtesting period that was characterized by ‘bear’ market conditions.

Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index

In this paper we attempt to predict the direction of change of the S&P500 index over the period 8 April 1998 to 5 February 2002 by means of a recurrent neural network (RNN). We demonstrate that the incorporation in the trading rule of the Chicago Board Options Exchange (CBOE) volatility index changes strongly enhances its profitability during ‘bear’ market periods. This improvement is measured in comparison with a RNN including changes of estimated conditional volatility measures, a linear autoregressive model as well as to a buy-and-hold strategy. We suggest a number of theories that are consistent with our findings.

A Multivariate I(2) cointegration analysis of German hyperinflation

This paper re-examines the Cagan model of German hyperinflation during the 1920s under the twin hypotheses that the system contains variables that are I(2) and that a linear trend is required in the cointegrating relations. Using the recently developed I(2) cointegration analysis developed by Johansen (1992, 1995, 1997) extended by Paruolo (1996) and Rahbek et al. (1999) we find that the linear trend hypothesis is rejected for the sample. However, we provide conclusive evidence that money supply and the price level have a common I(2) component. Then, the validity of Cagans model is tested via a transformation of the I(2) to an I(1) model between real money balances and money growth or inflation. This transformation is not imposed on the data but it is shown to satisfy the statistical property of polynomial cointegration. Evidence is obtained in favour of cointegration between the two sets of variables which is however weakened by the sample dependence of the trace test that the application of the recursive stability tests for cointegrated VAR models show.

Long-run purchasing power parity in the 1920s: the Greek experience

A test is made for the existence of long-run purchasing power parity (PPP) for three drahma bilateral exchange rates during the 1920s. Maximim likelihood estimation techniques of cointegration vectors are employed and they produce strong evidence in favour or PPP.

Temporal aggregation in structural VAR models

This paper examines the effects of temporal aggregation on the estimated time series properties of economic data. Theory predicts that temporal aggregation loses information about the underlying data processes. We derive low frequency, quarterly and annual, models implied by high frequency, monthly, structural vector autoregressive (SVAR) models and we find that these losses in information are substantial. It is shown that the accuracy of both the estimates and the forecasts of this class of models improve substantially when monthly data are used. Moreover, the aggregated data show more long‐run persistence than the underlying disaggregated data.

European sovereign bond spreads: financial integration and market conditions

In the present article, we examine the dynamics of euro-area sovereign bond yield spreads focusing on issues related to financial integration and market conditions. The property of a root falling near the unity threshold, in the data generation process of the underlying bond yields, marks the necessity for careful econometric specification. Thus, we formulate the sovereign bond yield spreads, for 10 Economic and Monetary Union (EMU), countries against the Bund as autoregressive processes with nonlinear properties, with the use of both Markov switching and smooth transition autoregression techniques. This way we examine, rather than assume, whether stable parity conditions existed in the underling bond yields and the effects of various events, for a period extending to early 1990s and the Maastricht Treaty. The results validate the presence of nonlinear characteristics in the stochastic processes of the series and that the case of a slow mean reverting process cannot be rejected irrespective of the regime we examine.