Geopolitical risk and excess stock returns predictability: New evidence from a century of data
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DOI: 10.1016/j.frl.2022.103211
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- Dario Caldara & Matteo Iacoviello, 2022.
"Measuring Geopolitical Risk,"
American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
- Matteo Iacoviello, 2018. "Measuring Geopolitical Risk," 2018 Meeting Papers 79, Society for Economic Dynamics.
- Dario Caldara & Matteo Iacoviello, 2018. "Measuring Geopolitical Risk," International Finance Discussion Papers 1222r1, Board of Governors of the Federal Reserve System (U.S.), revised 23 Mar 2022.
- 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.
- Wen, Fenghua & Cao, Jiahui & Liu, Zhen & Wang, Xiong, 2021. "Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets," International Review of Financial Analysis, Elsevier, vol. 76(C).
- Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
- John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
- Timmermann, Allan, 2006.
"Forecast Combinations,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196,
Elsevier.
- Timmermann, Allan, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
- Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, Department of Economics and Business Economics, Aarhus University.
- Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
- Capistrán, Carlos & Timmermann, Allan, 2009.
"Forecast Combination With Entry and Exit of Experts,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
- Timmermann Allan & Capistrán Carlos, 2006. "Forecast Combination with Entry and Exit of Experts," Working Papers 2006-08, Banco de México.
- Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
- Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014.
"Forecasting the Equity Risk Premium: The Role of Technical Indicators,"
Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
- Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.
- Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2011. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Working Papers CoFie-02-2011, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
- Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
- Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
- Amit Goyal & Ivo Welch, 2003.
"Predicting the Equity Premium with Dividend Ratios,"
Management Science, INFORMS, vol. 49(5), pages 639-654, May.
- Amit Goyal & Ivo Welch, 1999. "Predicting the Equity Premium with Dividend Ratios," Yale School of Management Working Papers amz2437, Yale School of Management, revised 01 Nov 2002.
- Amit Goyal & Ivo Welch, 2002. "Predicting the Equity Premium With Dividend Ratios," NBER Working Papers 8788, National Bureau of Economic Research, Inc.
- Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
- Alex Chinco & Adam D. Clark‐Joseph & Mao Ye, 2019. "Sparse Signals in the Cross‐Section of Returns," Journal of Finance, American Finance Association, vol. 74(1), pages 449-492, February.
- 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.
- R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
- Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
- Lauren Cohen & Andrea Frazzini, 2008. "Economic Links and Predictable Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1977-2011, August.
- Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
- Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Ma, Feng & Lu, Xinjie & Liu, Jia & Huang, Dengshi, 2022. "Macroeconomic attention and stock market return predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
- Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
- David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
- Wen, Fenghua & Tong, Xi & Ren, Xiaohang, 2022. "Gold or Bitcoin, which is the safe haven during the COVID-19 pandemic?," International Review of Financial Analysis, Elsevier, vol. 81(C).
- Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
- Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
- Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
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- Shaobin, Guo & Ahmad, Khalil & Khan, Naqib Ullah, 2024. "Natural resources, geopolitical conflicts, and digital trade: Evidence from China," Resources Policy, Elsevier, vol. 90(C).
- Wahyono, Budi & Rapih, Subroto & Boungou, Whelsy, 2023. "Unleashing the wordsmith: Analysing the stock market reactions to the launch of ChatGPT in the US Education sector," Finance Research Letters, Elsevier, vol. 58(PC).
- Wang, Lu & Ruan, Hang & Hong, Yanran & Luo, Keyu, 2023. "Detecting the hidden asymmetric relationship between crude oil and the US dollar: A novel neural Granger causality method," Research in International Business and Finance, Elsevier, vol. 64(C).
- Zhang, Yaojie & He, Jiaxin & He, Mengxi & Li, Shaofang, 2023. "Geopolitical risk and stock market volatility: A global perspective," Finance Research Letters, Elsevier, vol. 53(C).
- Babaei, Hamid & Hübner, Georges & Muller, Aline, 2023. "The effects of uncertainty on the dynamics of stock market interdependence: Evidence from the time-varying cointegration of the G7 stock markets," Journal of International Money and Finance, Elsevier, vol. 139(C).
- Sheenan, Lisa, 2023.
"Green bonds, conventional bonds and geopolitical risk,"
Finance Research Letters, Elsevier, vol. 58(PC).
- Sheenan, Lisa, 2023. "Green Bonds, Conventional Bonds and Geopolitical Risk," QBS Working Paper Series 2023/05, Queen's University Belfast, Queen's Business School.
- Hossain, Ashrafee T. & Masum, Abdullah-Al & Saadi, Samir, 2024. "The impact of geopolitical risks on foreign exchange markets: Evidence from the Russia–Ukraine war," Finance Research Letters, Elsevier, vol. 59(C).
- Hao, Xinlei & Ma, Yong & Pan, Dongtao, 2024. "Geopolitical risk and the predictability of spillovers between exchange, commodity and stock markets," Journal of Multinational Financial Management, Elsevier, vol. 73(C).
- Wang, Kai-Hua & Wen, Cui-Ping & Liu, Hong-Wen & Liu, Lu, 2023. "Promotion or hindrance? Exploring the bidirectional causality between geopolitical risk and green bonds from an energy perspective," Resources Policy, Elsevier, vol. 85(PB).
- Zhang, Yaojie & Zhang, Yuxuan & Ren, Xinrui & Jin, Meichen, 2024. "Geopolitical risk exposure and stock returns: Evidence from China," Finance Research Letters, Elsevier, vol. 64(C).
- Jana, Rabin K. & Ghosh, Indranil, 2023. "Time-varying relationship between geopolitical uncertainty and agricultural investment," Finance Research Letters, Elsevier, vol. 52(C).
- Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Saâdaoui, Foued & Ben Jabeur, Sami & Goodell, John W., 2023. "Geopolitical risk and the Saudi stock market: Evidence from a new wavelet packet multiresolution cross-causality," Finance Research Letters, Elsevier, vol. 53(C).
- Yu, Fanchao, 2023. "Macroeconomic information, global economic policy uncertainty and gold futures return predictability," Finance Research Letters, Elsevier, vol. 55(PA).
- Gao, Bin & Zhang, Jinlong & Xie, Jun & Zhang, Wenjie, 2023. "The impact of carbon risk on the pricing efficiency of the capital market: Evidence from a natural experiment in china," Finance Research Letters, Elsevier, vol. 57(C).
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Keywords
Geopolitical risks; Geopolitical threats; Excess stock returns; Portfolio performance;All these keywords.
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