Stock return predictability and market integration: The role of global and local information
Author
Abstract
Suggested Citation
DOI: 10.1080/23322039.2016.1178363
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Ivo Welch & Amit Goyal, 2008.
"A Comprehensive Look at The Empirical Performance of Equity Premium Prediction,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
- Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
- Amit Goyal & Ivo Welch & Athanasse Zafirov, 2021. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction II," Swiss Finance Institute Research Paper Series 21-85, Swiss Finance Institute.
- Amit Goval & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," NBER Working Papers 10483, National Bureau of Economic Research, Inc.
- Rangvid, Jesper & Schmeling, Maik & Schrimpf, Andreas, 2014.
"Dividend Predictability Around the World,"
Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(5-6), pages 1255-1277, December.
- Jesper Rangvid & Maik Schmeling & Andreas Schrimpf, 2010. "Dividend predictability around the world," CREATES Research Papers 2010-03, Department of Economics and Business Economics, Aarhus University.
- John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
- Clark, Todd E. & West, Kenneth D., 2007.
"Approximately normal tests for equal predictive accuracy in nested models,"
Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
- Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
- Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
- Goh, Jeremy C. & Jiang, Fuwei & Tu, Jun & Wang, Yuchen, 2013. "Can US economic variables predict the Chinese stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 22(C), pages 69-87.
- David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
- Bekaert, Geert & Hodrick, Robert J, 1992.
"Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets,"
Journal of Finance, American Finance Association, vol. 47(2), pages 467-509, June.
- Geert Bekaert & Robert J. Hodrick, 1991. "Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets," NBER Working Papers 3790, National Bureau of Economic Research, Inc.
- Bekaert, Geert, 1995. "Market Integration and Investment Barriers in Emerging Equity Markets," The World Bank Economic Review, World Bank, vol. 9(1), pages 75-107, January.
- John H. Cochrane, 2008.
"The Dog That Did Not Bark: A Defense of Return Predictability,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
- John H. Cochrane, 2006. "The Dog That Did Not Bark: A Defense of Return Predictability," NBER Working Papers 12026, National Bureau of Economic Research, Inc.
- Kellard, Neil M. & Nankervis, John C. & Papadimitriou, Fotios I., 2010. "Predicting the equity premium with dividend ratios: Reconciling the evidence," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 539-551, September.
- John Y. Campbell & Samuel B. Thompson, 2008.
"Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
- Campbell, John & Thompson, Samuel P., 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Scholarly Articles 2622619, Harvard University Department of Economics.
- Lior Menzly & Tano Santos & Pietro Veronesi, 2004. "Understanding Predictability," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 1-47, February.
- David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
- Ilan Cooper & Richard Priestley, 2013. "The World Business Cycle and Expected Returns," Review of Finance, European Finance Association, vol. 17(3), pages 1029-1064.
- David G. Mcmillan & Mark E. Wohar, 2013. "A Panel Analysis Of The Stock Return–Dividend Yield Relation: Predicting Returns And Dividend Growth," Manchester School, University of Manchester, vol. 81(3), pages 386-400, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
- McMillan, David G., 2019. "Predicting firm level stock returns: Implications for asset pricing and economic links," The British Accounting Review, Elsevier, vol. 51(4), pages 333-351.
- McMillan, David G., 2014. "Stock return, dividend growth and consumption growth predictability across markets and time: Implications for stock price movement," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 90-101.
- Tsiakas, Ilias & Li, Jiahan & Zhang, Haibin, 2020.
"Equity premium prediction and the state of the economy,"
Journal of Empirical Finance, Elsevier, vol. 58(C), pages 75-95.
- Ilias Tsiakas & Jiahan Li & Haibin Zhang, 2020. "Equity Premium Prediction and the State of the Economy," Working Paper series 20-16, Rimini Centre for Economic Analysis.
- Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
- Gonçalo Faria & Fabio Verona, 2016.
"Forecasting the equity risk premium with frequency-decomposed predictors,"
Working Papers de Economia (Economics Working Papers)
06, Católica Porto Business School, Universidade Católica Portuguesa.
- Faria, Gonçalo & Verona, Fabio, 2017. "Forecasting the equity risk premium with frequency-decomposed predictors," Bank of Finland Research Discussion Papers 1/2017, Bank of Finland.
- Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
- Gonçalo Faria & Fabio Verona, 2016.
"Forecasting the equity risk premium with frequency-decomposed predictors,"
Working Papers de Economia (Economics Working Papers)
06, Católica Porto Business School, Universidade Católica Portuguesa.
- Faria, Gonçalo & Verona, Fabio, 2017. "Forecasting the equity risk premium with frequency-decomposed predictors," Research Discussion Papers 1/2017, Bank of Finland.
- Mingwei Sun & Paskalis Glabadanidis, 2022. "Can technical indicators predict the Chinese equity risk premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 114-142, March.
- repec:zbw:bofrdp:2017_001 is not listed on IDEAS
- Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
- Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
- David Haab & Dr. Thomas Nitschka, 2017. "Predicting returns on asset markets of a small, open economy and the influence of global risks," Working Papers 2017-14, Swiss National Bank.
- repec:zbw:bofrdp:2018_007 is not listed on IDEAS
- Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2019.
"International tail risk and World Fear,"
Journal of International Money and Finance, Elsevier, vol. 93(C), pages 244-259.
- Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "International Tail Risk and World Fear," Hannover Economic Papers (HEP) dp-620, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- Narayan, Paresh Kumar & Narayan, Seema & Phan, Dinh Hoang Bach, 2022. "Terrorism and international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
- Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
- Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019.
"Manager sentiment and stock returns,"
Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
- Fuwei Jiang & Joshua Lee & Xiumin Martin & Guofu Zhou, 2019. "Manager sentiment and stock returns," CEMA Working Papers 677, China Economics and Management Academy, Central University of Finance and Economics.
- Ruan, Qingsong & Wang, Zilin & Zhou, Yaping & Lv, Dayong, 2020. "A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China," Economic Modelling, Elsevier, vol. 88(C), pages 47-58.
- Faria, Gonçalo & Verona, Fabio, 2018.
"Forecasting stock market returns by summing the frequency-decomposed parts,"
Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
- Gonçalo Faria & Fabio Verona, 2016. "Forecasting stock market returns by summing the frequency-decomposed parts," Working Papers de Economia (Economics Working Papers) 05, Católica Porto Business School, Universidade Católica Portuguesa.
- Faria, Gonçalo & Verona, Fabio, 2016. "Forecasting stock market returns by summing the frequency-decomposed parts," Research Discussion Papers 29/2016, Bank of Finland.
- Gonçalo Faria & Fabio Verona, 2017. "Forecasting stock market returns by summing the frequency-decomposed parts," CEF.UP Working Papers 1702, Universidade do Porto, Faculdade de Economia do Porto.
- repec:zbw:bofrdp:2016_029 is not listed on IDEAS
- Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
- Faria, Gonçalo & Verona, Fabio, 2018.
"Forecasting stock market returns by summing the frequency-decomposed parts,"
Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
- Gonçalo Faria & Fabio Verona, 2016. "Forecasting stock market returns by summing the frequency-decomposed parts," Working Papers de Economia (Economics Working Papers) 05, Católica Porto Business School, Universidade Católica Portuguesa.
- Faria, Gonçalo & Verona, Fabio, 2016. "Forecasting stock market returns by summing the frequency-decomposed parts," Bank of Finland Research Discussion Papers 29/2016, Bank of Finland.
- Gonçalo Faria & Fabio Verona, 2017. "Forecasting stock market returns by summing the frequency-decomposed parts," CEF.UP Working Papers 1702, Universidade do Porto, Faculdade de Economia do Porto.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:oaefxx:v:4:y:2016:i:1:p:1178363. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/OAEF20 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.