Dynamic asset beta measurement
The recent advent of high-frequency data and advances in financial econometrics allow market participants to evaluate the accuracy of different beta (systematic risk) measurements. Benchmarking against the monthly realized beta formed by 30-minute data, we compare the popular Fama-MacBeth betas, the...
Gespeichert in:
| Veröffentlicht in: | Applied financial economics 2012-10, Vol.22 (19), p.1655-1664 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1664 |
|---|---|
| container_issue | 19 |
| container_start_page | 1655 |
| container_title | Applied financial economics |
| container_volume | 22 |
| creator | Chen, Brandon Reeves, Jonathan J. |
| description | The recent advent of high-frequency data and advances in financial econometrics allow market participants to evaluate the accuracy of different beta (systematic risk) measurements. Benchmarking against the monthly realized beta formed by 30-minute data, we compare the popular Fama-MacBeth betas, the monthly realized betas formed by daily returns and our Hodrick-Prescott filtered betas, with the smoothing parameter, λ, set to 100. We find our filtered betas reduce the measurement error substantially relative to other beta measures. These results enable market participants to measure betas with greater precision and efficiency even with only daily returns in hand. |
| doi_str_mv | 10.1080/09603107.2012.674203 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_repec</sourceid><recordid>TN_cdi_proquest_journals_1011301029</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1267028952</sourcerecordid><originalsourceid>FETCH-LOGICAL-c417t-2de7a321dd5dd92b568b4197e9f8bf04c9ffbff8f25426ec147b02d5ca0d37553</originalsourceid><addsrcrecordid>eNp9kEtLxDAUhYMoOI7-A5EBN2463ptX25XI-IQRN7oOaZpgh75MOsr8e1OqLly4uA8u3zlcDiGnCEuEDC4hl8AQ0iUFpEuZcgpsj8yQS5lwBmKfzEYkGZlDchTCBiKYSZyRs5tdq5vKLHQIdlgUdtCLxuqw9bax7XBMDpyugz35nnPyenf7snpI1s_3j6vrdWI4pkNCS5tqRrEsRVnmtBAyKzjmqc1dVjjgJneucC5zVHAqrUGeFkBLYTSULBWCzcnF5Nv77n1rw6CaKhhb17q13TYopDIFmuWCRvT8D7rptr6N3ykERAYINI8UnyjjuxC8dar3VaP9LkJqDE39hKbG0NQUWpQ9TTJve2t-NYN2undVvHwopimNbTcuo5LpKhbmsfXjIoVQKCVXb0MT_a4mv6p1nW_0Z-frMtrt6s47r1tTBcX-_egLmGqKMQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1011301029</pqid></control><display><type>article</type><title>Dynamic asset beta measurement</title><source>RePEc</source><source>Business Source Complete</source><creator>Chen, Brandon ; Reeves, Jonathan J.</creator><creatorcontrib>Chen, Brandon ; Reeves, Jonathan J.</creatorcontrib><description>The recent advent of high-frequency data and advances in financial econometrics allow market participants to evaluate the accuracy of different beta (systematic risk) measurements. Benchmarking against the monthly realized beta formed by 30-minute data, we compare the popular Fama-MacBeth betas, the monthly realized betas formed by daily returns and our Hodrick-Prescott filtered betas, with the smoothing parameter, λ, set to 100. We find our filtered betas reduce the measurement error substantially relative to other beta measures. These results enable market participants to measure betas with greater precision and efficiency even with only daily returns in hand.</description><identifier>ISSN: 0960-3107</identifier><identifier>EISSN: 1466-4305</identifier><identifier>DOI: 10.1080/09603107.2012.674203</identifier><language>eng</language><publisher>London: Routledge</publisher><subject>Benchmarking ; Benchmarks ; Capital market ; CAPM beta ; Comparative studies ; Econometrics ; Economic efficiency ; Market economy ; Measurement errors ; Rates of return ; realized beta ; Returns to scale ; Risk assessment ; systematic risk ; time-varying risk</subject><ispartof>Applied financial economics, 2012-10, Vol.22 (19), p.1655-1664</ispartof><rights>Copyright Taylor & Francis Group, LLC 2012</rights><rights>Copyright Routledge 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c417t-2de7a321dd5dd92b568b4197e9f8bf04c9ffbff8f25426ec147b02d5ca0d37553</citedby><cites>FETCH-LOGICAL-c417t-2de7a321dd5dd92b568b4197e9f8bf04c9ffbff8f25426ec147b02d5ca0d37553</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,3994,27901,27902</link.rule.ids><backlink>$$Uhttp://econpapers.repec.org/article/tafapfiec/v_3a22_3ay_3a2012_3ai_3a19_3ap_3a1655-1664.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Brandon</creatorcontrib><creatorcontrib>Reeves, Jonathan J.</creatorcontrib><title>Dynamic asset beta measurement</title><title>Applied financial economics</title><description>The recent advent of high-frequency data and advances in financial econometrics allow market participants to evaluate the accuracy of different beta (systematic risk) measurements. Benchmarking against the monthly realized beta formed by 30-minute data, we compare the popular Fama-MacBeth betas, the monthly realized betas formed by daily returns and our Hodrick-Prescott filtered betas, with the smoothing parameter, λ, set to 100. We find our filtered betas reduce the measurement error substantially relative to other beta measures. These results enable market participants to measure betas with greater precision and efficiency even with only daily returns in hand.</description><subject>Benchmarking</subject><subject>Benchmarks</subject><subject>Capital market</subject><subject>CAPM beta</subject><subject>Comparative studies</subject><subject>Econometrics</subject><subject>Economic efficiency</subject><subject>Market economy</subject><subject>Measurement errors</subject><subject>Rates of return</subject><subject>realized beta</subject><subject>Returns to scale</subject><subject>Risk assessment</subject><subject>systematic risk</subject><subject>time-varying risk</subject><issn>0960-3107</issn><issn>1466-4305</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNp9kEtLxDAUhYMoOI7-A5EBN2463ptX25XI-IQRN7oOaZpgh75MOsr8e1OqLly4uA8u3zlcDiGnCEuEDC4hl8AQ0iUFpEuZcgpsj8yQS5lwBmKfzEYkGZlDchTCBiKYSZyRs5tdq5vKLHQIdlgUdtCLxuqw9bax7XBMDpyugz35nnPyenf7snpI1s_3j6vrdWI4pkNCS5tqRrEsRVnmtBAyKzjmqc1dVjjgJneucC5zVHAqrUGeFkBLYTSULBWCzcnF5Nv77n1rw6CaKhhb17q13TYopDIFmuWCRvT8D7rptr6N3ykERAYINI8UnyjjuxC8dar3VaP9LkJqDE39hKbG0NQUWpQ9TTJve2t-NYN2undVvHwopimNbTcuo5LpKhbmsfXjIoVQKCVXb0MT_a4mv6p1nW_0Z-frMtrt6s47r1tTBcX-_egLmGqKMQ</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Chen, Brandon</creator><creator>Reeves, Jonathan J.</creator><general>Routledge</general><general>Taylor and Francis Journals</general><general>Routledge, Taylor & Francis Group</general><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>201210</creationdate><title>Dynamic asset beta measurement</title><author>Chen, Brandon ; Reeves, Jonathan J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c417t-2de7a321dd5dd92b568b4197e9f8bf04c9ffbff8f25426ec147b02d5ca0d37553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Benchmarking</topic><topic>Benchmarks</topic><topic>Capital market</topic><topic>CAPM beta</topic><topic>Comparative studies</topic><topic>Econometrics</topic><topic>Economic efficiency</topic><topic>Market economy</topic><topic>Measurement errors</topic><topic>Rates of return</topic><topic>realized beta</topic><topic>Returns to scale</topic><topic>Risk assessment</topic><topic>systematic risk</topic><topic>time-varying risk</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Brandon</creatorcontrib><creatorcontrib>Reeves, Jonathan J.</creatorcontrib><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Applied financial economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Brandon</au><au>Reeves, Jonathan J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic asset beta measurement</atitle><jtitle>Applied financial economics</jtitle><date>2012-10</date><risdate>2012</risdate><volume>22</volume><issue>19</issue><spage>1655</spage><epage>1664</epage><pages>1655-1664</pages><issn>0960-3107</issn><eissn>1466-4305</eissn><abstract>The recent advent of high-frequency data and advances in financial econometrics allow market participants to evaluate the accuracy of different beta (systematic risk) measurements. Benchmarking against the monthly realized beta formed by 30-minute data, we compare the popular Fama-MacBeth betas, the monthly realized betas formed by daily returns and our Hodrick-Prescott filtered betas, with the smoothing parameter, λ, set to 100. We find our filtered betas reduce the measurement error substantially relative to other beta measures. These results enable market participants to measure betas with greater precision and efficiency even with only daily returns in hand.</abstract><cop>London</cop><pub>Routledge</pub><doi>10.1080/09603107.2012.674203</doi><tpages>10</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0960-3107 |
| ispartof | Applied financial economics, 2012-10, Vol.22 (19), p.1655-1664 |
| issn | 0960-3107 1466-4305 |
| language | eng |
| recordid | cdi_proquest_journals_1011301029 |
| source | RePEc; Business Source Complete |
| subjects | Benchmarking Benchmarks Capital market CAPM beta Comparative studies Econometrics Economic efficiency Market economy Measurement errors Rates of return realized beta Returns to scale Risk assessment systematic risk time-varying risk |
| title | Dynamic asset beta measurement |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-12T22%3A47%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_repec&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Dynamic%20asset%20beta%20measurement&rft.jtitle=Applied%20financial%20economics&rft.au=Chen,%20Brandon&rft.date=2012-10&rft.volume=22&rft.issue=19&rft.spage=1655&rft.epage=1664&rft.pages=1655-1664&rft.issn=0960-3107&rft.eissn=1466-4305&rft_id=info:doi/10.1080/09603107.2012.674203&rft_dat=%3Cproquest_repec%3E1267028952%3C/proquest_repec%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1011301029&rft_id=info:pmid/&rfr_iscdi=true |