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- W2174194260 abstract "<p class=MsoNormal style=text-align: justify; margin: 0in 37.3pt 0pt 35.4pt;><span style=mso-bidi-font-style: italic;><span style=font-size: x-small;><span style=font-family: Batang;>We re-examine the Dow dividend yield anomaly to ascertain if data errors create the superior returns of the trading rule.<span style=mso-spacerun: yes;> </span>Empirical testing, using both parametric and nonparametric methods, suggests that the trading rule outperforms the index.<span style=mso-spacerun: yes;> </span>Additionally, data errors are not the drivers of superior trading rule returns.<span style=mso-spacerun: yes;> </span>Moreover, the Chow breakpoint test of structural stability suggests that neither window dressing nor data mining explain this phenomenon.<span style=mso-spacerun: yes;> </span>Finally, a turn of the year formation date fails to explain superior trading rule returns, further mitigating the data mining explanation. </span></span></span></p>" @default.
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- W2174194260 date "2011-01-31" @default.
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- W2174194260 title "Window Dressing, Data Mining, Or Data Errors: A Re-Examination Of The Dogs Of The Dow Theory" @default.
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- W2174194260 doi "https://doi.org/10.19030/jabr.v18i2.2122" @default.
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