Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies

Bredin, Don; Hyde, Stuart

doi:10.1111/j.1468-036x.2007.00361.x

Cited by 23 publications

(21 citation statements)

References 52 publications

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“…Within this framework we examine the existence of common trends in the system and attempt to detect shifts that follow unobserved Markov chain probabilistic functions, in the underlying VECM. Similar investigations can be found in other studies investigating for example the interactions between international and small stock markets as subject to regime switches by using the smooth transition regression model or in studies that formulate a Markov switching framework for the examination of spillover effects among major equity market indices and the corresponding futures contracts written on them (Bredin and Hyde, 2008; Sarno and Valente, 2005).…”

Section: Introductionsupporting

confidence: 58%

Benchmark Bonds Interactions under Regime Shifts

Georgoutsos¹,

Migiakis²

2012

Euro Fin Management

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In the present paper we examine the interactions among five benchmark ten year government bonds, namely those of the USA, Germany, France, Italy and the Netherlands. Our aim is to illustrate empirically a net 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, differing from 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 the monetary union. Overall, our empirical results indicate that stronger interactions among 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.

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Section: Introductionsupporting

confidence: 58%

Benchmark Bonds Interactions under Regime Shifts

Georgoutsos¹,

Migiakis²

2012

Euro Fin Management

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“…() find that stronger relations between comovement and the business cycle exist in poor countries, countries with less developed financial markets, and countries with weaker accounting and transparency standards. Bredin and Hyde () find that both global and regional macroeconomic variables are important influences on stock returns in Ireland and Denmark. Financial variables incorporate market reaction to macroeconomic news.…”

Section: Literature Reviewmentioning

confidence: 99%

Time‐Varying World and Regional Integration in Emerging European Equity Markets

Wang

Shih

2011

Euro Fin Management

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This study investigates time-varying world and regional integration in emerging European markets. Categorising global and regional effects into return and volatility spillovers, we also examine the impact of time variation in these spillover effects based on the conditions of economic growth. Our results show that growth and currency depreciation can predict the degree of integration and spillover effects for these markets. The impact of growth on the level of regional integration is greater in countries with floating exchange rate regimes than in those with exchange controls. The world effect on European returns is stronger when the developed European region is in a recession. However, regional effects on the volatility of emerging European markets are greater during faster growth or weaker than expected economic growth.

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“…In terms of financial theory, notice that (11) corresponds not to the absence of change in asset prices, but to the existence of a constant factor of change in log-prices, i.e., Obviously, even if only a crude description of the stochastic process for log-asset prices, (11) may represent an excellent forecasting model because the presence of only one parameter to be estimated (α j ) has a chance to reduce the amount of parameter uncertainty affecting the predictions.…”

Section: Other Standard Benchmarksmentioning

confidence: 99%

“…To increase the set of useful benchmarks to be used to compute relative forecasting performances, (11) and (12) are also estimated incorporating simple (Gaussian) GARCH(1,1)-in mean effects:…”

Section: Other Standard Benchmarksmentioning

confidence: 99%

Non-Linear Predictability in Stock and Bond Returns: When and Where is it Exploitable?

et al. 2009

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractWe systematically examine the comparative predictive performance of a number of alternative linear and non-linear models for stock and bond returns in the G7 countries. Besides Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regime switching (predictive) regression models, we also estimate univariate models in which conditional heteroskedasticity is captured through GARCH, TARCH and EGARCH models and ARCH-in mean effects appear in the conditional mean. Although we fail to find a consistent winner/out-performer across all countries and asset markets, it turns out that capturing non-linear effects is of extreme importance to improve forecasting performance. U.S. and U.K. asset return data are "special" in the sense that good predictive performance seems to loudly ask for models that capture non-linear dynamics, especially of the Markov switching type. Although occasionally also stock and bond return forecasts for other G7 countries appear to benefit from non-linear modeling (especially of TAR and STAR type), data from France, Germany, and Italy express interesting predictive results on the basis of simpler benchmarks. U.S. and U.K. data are also the only two data sets in which we find statistically significant differences between forecasting models. Results appear to be remarkably stable over time, and robust to the specification of the loss function used in statistical evaluations as well as to the methodology employed to perform pairwise comparisons. How to quote or cite this document AbstractWe systematically examine the comparative predictive performance of a number of alternative linear and non-linear models for stock and bond returns in the G7 countries. Besides Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regime switching (predictive) regression models, we also estimate univariate models in which conditional heteroskedasticity is captured through GARCH, TARCH and EGARCH models and ARCH-in mean effects appear in the conditional mean. Although we fail to find a consistent winner/out-performer across all countries and asset markets, it turns out that capturing non-linear effects is of extreme importance to improve forecasting performance. U.S. and U.K. asset return data are "special" in the sense that good predictive performance seems to loudly ask for models that capture non-linear dynamics, especially of the ...

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Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies

Cited by 23 publications

References 52 publications

Benchmark Bonds Interactions under Regime Shifts

Benchmark Bonds Interactions under Regime Shifts

Time‐Varying World and Regional Integration in Emerging European Equity Markets

Non-Linear Predictability in Stock and Bond Returns: When and Where is it Exploitable?

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