Are disagreements agreeable? Evidence from information aggregation
Most studies on disagreement focus on cross-sectional asset returns and well-recognized disagreement measures generally cannot predict the stock market with a horizon less than 12 months. This paper proposes three aggregate disagreement indexes by aggregating information across 20 disagreement measu...
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sg-smu-ink.lkcsb_research-74682020-01-16T10:49:48Z Are disagreements agreeable? Evidence from information aggregation HUANG, Dashan LI, Jiangyuan WANG, Liyao Most studies on disagreement focus on cross-sectional asset returns and well-recognized disagreement measures generally cannot predict the stock market with a horizon less than 12 months. This paper proposes three aggregate disagreement indexes by aggregating information across 20 disagreement measures. We show that disagreement measures collectively have a common component that has significant power in predicting the stock market both in- and out-of-sample. Consistent with the theory developed by Atmaz and Basak (2017), the indexes asymmetrically forecast the market with greater power in high sentiment periods. Moreover, the indexes negatively predict economic activities, and positively predict market volatility, illiquidity, and trading volume. 2017-12-04T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/6469 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7468/viewcontent/SSRN_id3077938.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Disagreement Market risk premium Predictability Information aggregation PLS Finance and Financial Management |
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Disagreement Market risk premium Predictability Information aggregation PLS Finance and Financial Management HUANG, Dashan LI, Jiangyuan WANG, Liyao Are disagreements agreeable? Evidence from information aggregation |
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Most studies on disagreement focus on cross-sectional asset returns and well-recognized disagreement measures generally cannot predict the stock market with a horizon less than 12 months. This paper proposes three aggregate disagreement indexes by aggregating information across 20 disagreement measures. We show that disagreement measures collectively have a common component that has significant power in predicting the stock market both in- and out-of-sample. Consistent with the theory developed by Atmaz and Basak (2017), the indexes asymmetrically forecast the market with greater power in high sentiment periods. Moreover, the indexes negatively predict economic activities, and positively predict market volatility, illiquidity, and trading volume. |
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HUANG, Dashan LI, Jiangyuan WANG, Liyao |
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HUANG, Dashan LI, Jiangyuan WANG, Liyao |
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HUANG, Dashan |
title |
Are disagreements agreeable? Evidence from information aggregation |
title_short |
Are disagreements agreeable? Evidence from information aggregation |
title_full |
Are disagreements agreeable? Evidence from information aggregation |
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Are disagreements agreeable? Evidence from information aggregation |
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Are disagreements agreeable? Evidence from information aggregation |
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are disagreements agreeable? evidence from information aggregation |
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Institutional Knowledge at Singapore Management University |
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2017 |
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https://ink.library.smu.edu.sg/lkcsb_research/6469 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7468/viewcontent/SSRN_id3077938.pdf |
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