Can energy security predict energy stock returns?
We hypothesize that energy security contains valuable information that can predict energy stock returns. To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns. We find that, at most, all 10 energy security indexes can predict returns. We further show that the...
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| Veröffentlicht in: | Energy economics 2021-02, Vol.94, p.105052, Article 105052 |
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| container_title | Energy economics |
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| creator | Iyke, Bernard Njindan Tran, Vuong Thao Narayan, Paresh Kumar |
| description | We hypothesize that energy security contains valuable information that can predict energy stock returns. To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns. We find that, at most, all 10 energy security indexes can predict returns. We further show that the return forecasts generated using the energy security indexes as a predictor are economically significant. A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees to access the additional information contained in return forecasts generated using the energy security indexes. These findings survive several robustness tests.
•We hypothesize that energy security can predict energy stock returns.•To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns.•We find that, at most, all 10 energy security indexes can predict returns.•We show that our return forecasts are economically significant.•A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees for our forecast information. |
| doi_str_mv | 10.1016/j.eneco.2020.105052 |
| format | Article |
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•We hypothesize that energy security can predict energy stock returns.•To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns.•We find that, at most, all 10 energy security indexes can predict returns.•We show that our return forecasts are economically significant.•A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees for our forecast information.</description><identifier>ISSN: 0140-9883</identifier><identifier>EISSN: 1873-6181</identifier><identifier>DOI: 10.1016/j.eneco.2020.105052</identifier><language>eng</language><publisher>Kidlington: Elsevier B.V</publisher><subject>Economic significance ; Energy ; Energy economics ; Energy security ; Energy stocks ; Fees & charges ; Indexes ; Portfolio management ; Predictability ; Return on investment ; Robustness ; Security ; Stock returns ; Stocks ; Willingness to pay</subject><ispartof>Energy economics, 2021-02, Vol.94, p.105052, Article 105052</ispartof><rights>2020</rights><rights>Copyright Elsevier Science Ltd. Feb 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-4f3d4f3116eb7c2f86c76af38f0b3bfedb8f3ebfe7ed3ce010925b9043d9375f3</citedby><cites>FETCH-LOGICAL-c396t-4f3d4f3116eb7c2f86c76af38f0b3bfedb8f3ebfe7ed3ce010925b9043d9375f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0140988320303923$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27843,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Iyke, Bernard Njindan</creatorcontrib><creatorcontrib>Tran, Vuong Thao</creatorcontrib><creatorcontrib>Narayan, Paresh Kumar</creatorcontrib><title>Can energy security predict energy stock returns?</title><title>Energy economics</title><description>We hypothesize that energy security contains valuable information that can predict energy stock returns. To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns. We find that, at most, all 10 energy security indexes can predict returns. We further show that the return forecasts generated using the energy security indexes as a predictor are economically significant. A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees to access the additional information contained in return forecasts generated using the energy security indexes. These findings survive several robustness tests.
•We hypothesize that energy security can predict energy stock returns.•To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns.•We find that, at most, all 10 energy security indexes can predict returns.•We show that our return forecasts are economically significant.•A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees for our forecast information.</description><subject>Economic significance</subject><subject>Energy</subject><subject>Energy economics</subject><subject>Energy security</subject><subject>Energy stocks</subject><subject>Fees & charges</subject><subject>Indexes</subject><subject>Portfolio management</subject><subject>Predictability</subject><subject>Return on investment</subject><subject>Robustness</subject><subject>Security</subject><subject>Stock returns</subject><subject>Stocks</subject><subject>Willingness to pay</subject><issn>0140-9883</issn><issn>1873-6181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNp9UE1LxDAQDaLguvoLvBQ8d51kmjQ9iMjiFyx40XNo04m0aluTrLD_3qwVjx6GGR7vzcx7jJ1zWHHg6rJf0UB2XAkQe0SCFAdswXWJueKaH7IF8ALySms8Zich9AAgldQLxtf1kCWxf91lgezWd3GXTZ7azsY_PI72LfMUt34I16fsyNXvgc5--5K93N0-rx_yzdP94_pmk1usVMwLh20qzhU1pRVOK1uq2qF20GDjqG20Q0pDSS1aAg6VkE0FBbYVltLhkl3Meyc_fm4pRNOP6YF00ggphC5KUJhYOLOsH0Pw5Mzku4_a7wwHs8_G9OYnG7PPxszZJNXVrKJk4Ksjb4LtaLDJticbTTt2_-q_AQFlbYs</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Iyke, Bernard Njindan</creator><creator>Tran, Vuong Thao</creator><creator>Narayan, Paresh Kumar</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TA</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>JG9</scope><scope>SOI</scope></search><sort><creationdate>20210201</creationdate><title>Can energy security predict energy stock returns?</title><author>Iyke, Bernard Njindan ; Tran, Vuong Thao ; Narayan, Paresh Kumar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-4f3d4f3116eb7c2f86c76af38f0b3bfedb8f3ebfe7ed3ce010925b9043d9375f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Economic significance</topic><topic>Energy</topic><topic>Energy economics</topic><topic>Energy security</topic><topic>Energy stocks</topic><topic>Fees & charges</topic><topic>Indexes</topic><topic>Portfolio management</topic><topic>Predictability</topic><topic>Return on investment</topic><topic>Robustness</topic><topic>Security</topic><topic>Stock returns</topic><topic>Stocks</topic><topic>Willingness to pay</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Iyke, Bernard Njindan</creatorcontrib><creatorcontrib>Tran, Vuong Thao</creatorcontrib><creatorcontrib>Narayan, Paresh Kumar</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Materials Business File</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><collection>Environment Abstracts</collection><jtitle>Energy economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Iyke, Bernard Njindan</au><au>Tran, Vuong Thao</au><au>Narayan, Paresh Kumar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Can energy security predict energy stock returns?</atitle><jtitle>Energy economics</jtitle><date>2021-02-01</date><risdate>2021</risdate><volume>94</volume><spage>105052</spage><pages>105052-</pages><artnum>105052</artnum><issn>0140-9883</issn><eissn>1873-6181</eissn><abstract>We hypothesize that energy security contains valuable information that can predict energy stock returns. To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns. We find that, at most, all 10 energy security indexes can predict returns. We further show that the return forecasts generated using the energy security indexes as a predictor are economically significant. A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees to access the additional information contained in return forecasts generated using the energy security indexes. These findings survive several robustness tests.
•We hypothesize that energy security can predict energy stock returns.•To test this hypothesis, we construct 10 energy security indexes and nine energy stock returns.•We find that, at most, all 10 energy security indexes can predict returns.•We show that our return forecasts are economically significant.•A mean-variance investor is willing to pay a maximum of 4.88% per annum in extra portfolio management fees for our forecast information.</abstract><cop>Kidlington</cop><pub>Elsevier B.V</pub><doi>10.1016/j.eneco.2020.105052</doi></addata></record> |
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| identifier | ISSN: 0140-9883 |
| ispartof | Energy economics, 2021-02, Vol.94, p.105052, Article 105052 |
| issn | 0140-9883 1873-6181 |
| language | eng |
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| source | PAIS Index; Elsevier ScienceDirect Journals |
| subjects | Economic significance Energy Energy economics Energy security Energy stocks Fees & charges Indexes Portfolio management Predictability Return on investment Robustness Security Stock returns Stocks Willingness to pay |
| title | Can energy security predict energy stock returns? |
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