International Stock Return Predictability: On the Role of the United States in Bad and Good Times PDF Download
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Author: Boriss Siliverstovs
Publisher:
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Languages : en
Pages :
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Author: Boriss Siliverstovs
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Category :
Languages : en
Pages :
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Author: Andreas Schrimpf
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predictive variables, whereas valuation ratios perform rather poorly. Yet, predictability of market excess returns weakens substantially, once model uncertainty is accounted for. We document notable differences in the degree of in-sample and out-of-sample predictability across different stock markets. Overall, these findings suggest that return predictability is neither a uniform, nor a universal feature across international capital markets.
Author: Pierre Giot
Publisher:
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Category :
Languages : en
Pages : 64
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Author: Pierre Giot
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Category :
Languages : en
Pages : 65
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The predictability of stock returns in ten countries is assessed taking into account recently developed out-of-sample statistical tests and risk-adjusted metrics. Predictive variables include both valuation ratios and interest rate variables. Out-of-sample predictive power is found to be greatest for the short-term and long-term interest rate variables. Given the importance of trading profitability in assessing market efficiency, we show that such statistical predictive power is economically meaningless across countries and investment horizons. All in all, no common pattern of stock return predictability emerges across countries, be it on statistical or economic grounds.
Author: Amélie Charles
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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We investigate whether stock returns of international markets are predictable from a range of fundamentals including key financial ratios (dividend-price ratio, dividend-yield, earnings-price ratio, dividend-payout ratio), technical indicators (price pressure, change in volume), and short-term interest rates. We adopt two new alternative testing and estimation methods: the improved augmented regression method and wild bootstrapping of predictive model based on a restricted VAR form. Both methods take explicit account of endogeneity of predictors, providing bias-reduced estimation and improved statistical inference in small samples. From monthly data of 16 Asia-Pacific (including U.S.) and 21 European stock markets from 2000 to 2014, we find that the financial ratios show weak predictive ability with small effect sizes and poor out-of-sample forecasting performances. In contrast, the price pressure and interest rate are found to be strong predictors for stock return with large effect sizes and satisfactory out-of-sample forecasting performance.
Author: Hui Guo
Publisher:
ISBN:
Category : Stock price forecasting
Languages : en
Pages : 44
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Author: David G. McMillan
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on principal components analysis. Results identify three global expected returns factors, one related to the major stock markets of the US, UK and Asia and one related to the other markets analysed. The third component is related to dividend growth. A single dominant realised returns factor is also noted. A forecasting exercise comparing the principal components based factors to a US return factor and local market only factors, as well as the historical mean benchmark find supportive evidence for the former approach. It is hoped that the results from this paper will be informative on three counts. First, to academics interested in understanding the dynamics asset price movement. Second, to market participants who aim to time the market and engage in portfolio and risk management. Third, to those (policy makers and others) who are interested in linkages across international markets and the nature and degree of integration.
Author: Juan M. Londono
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Category :
Languages : en
Pages :
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Author: Graham Elliott
Publisher: Elsevier
ISBN: 0444627405
Category : Business & Economics
Languages : en
Pages : 667
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The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics
Author: Nikos C. Papapostolou
Publisher:
ISBN:
Category :
Languages : en
Pages : 78
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Stock return predictability by investor sentiment has been subject to constant updating, but reaching a decisive conclusion seems rather challenging as academic research relies heavily on US data. We provide fresh evidence on stock return predictability in an international setting and show that shipping investor sentiment is a common leading indicator for financial markets. We establish out-of-sample predictability and demonstrate that investor sentiment is also economically significant in providing utility gains to a mean-variance investor. Finally, we find evidence that the predictive power of sentiment works best when negative forecasts are also taken into account.
