Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/237146 
Year of Publication: 
2018
Citation: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 4 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2018 [Pages:] 1-24
Publisher: 
Springer, Heidelberg
Abstract: 
By decomposing asset returns into potential maximum gain (PMG) and potential maximum loss (PML) with price extremes, this study empirically investigated the relationships between PMG and PML. We found significant asymmetry between PMG and PML. PML significantly contributed to forecasting PMG but not vice versa. We further explored the power of this asymmetry for predicting asset returns and found it could significantly improve asset return predictability in both in-sample and out-of-sample forecasting. Investors who incorporate this asymmetry into their investment decisions can get substantial utility gains. This asymmetry remains significant even when controlling for macroeconomic variables, technical indicators, market sentiment, and skewness. Moreover, this asymmetry was found to be quite general across different countries.
Subjects: 
Price extremes
Return decomposition
Asymmetry
Return predictability
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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