Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/102732
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Accounting and Finance | en_US |
| dc.creator | Huang, S | en_US |
| dc.creator | Song, Y | en_US |
| dc.creator | Xiang, H | en_US |
| dc.date.accessioned | 2023-11-14T01:15:43Z | - |
| dc.date.available | 2023-11-14T01:15:43Z | - |
| dc.identifier.issn | 0022-1090 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/102732 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Cambridge University Press | en_US |
| dc.rights | © The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. | en_US |
| dc.rights | The following publication Huang, S., Song, Y., & Xiang, H. (2024). The Smart Beta Mirage. Journal of Financial and Quantitative Analysis, 59(6), 2515–2546 is available at https://doi.org/10.1017/S0022109023000674. | en_US |
| dc.title | The smart beta mirage | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 2515 | en_US |
| dc.identifier.epage | 2546 | en_US |
| dc.identifier.volume | 59 | en_US |
| dc.identifier.issue | 6 | en_US |
| dc.identifier.doi | 10.1017/S0022109023000674 | en_US |
| dcterms.abstract | We document and explain the sharp performance deterioration of smart beta indexes after the corresponding exchange-traded funds (ETFs) are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% “on paper” before ETF listings to about −0.50% to −1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to backtests. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Journal of financial and quantitative analysis, Sept 2024, v. 59, no. 6, p. 2515-2546 | en_US |
| dcterms.isPartOf | Journal of financial and quantitative analysis | en_US |
| dcterms.issued | 2024-09 | - |
| dc.identifier.eissn | 1756-6916 | en_US |
| dc.description.validate | 202311 bckw | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_TA | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.TA | CUP (2023) | en_US |
| dc.description.oaCategory | TA | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Huang_Smart_Beta_Mirage.pdf | 518.04 kB | Adobe PDF | View/Open |
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