國立虎尾科技大學 |

登入

回首頁

Earnings Call Textual Information an...

ProQuest Information and Learning Co.

Earnings Call Textual Information and the Cross-Section of Stock Returns.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Earnings Call Textual Information and the Cross-Section of Stock Returns./
作者:	Bodmeier, Andreas.
面頁冊數:	1 online resource (54 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: A.
Contained By:	Dissertation Abstracts International79-03A(E).
標題:	Finance. -
電子資源:	click for full text (PQDT)
ISBN:	9780355519549

Earnings Call Textual Information and the Cross-Section of Stock Returns.
Bodmeier, Andreas.

Earnings Call Textual Information and the Cross-Section of Stock Returns. - 1 online resource (54 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: A.

Thesis (Ph.D.)

Includes bibliographical references

This paper investigates the informational value of corporate earnings calls in investment decision-making. I employ a computational linguistics approach to extract textual information from corporate earnings calls and show that it predicts returns beyond other previously identified predictors. Specifically, I find that portfolios sorted on the verbal information in earnings calls transcripts generate abnormal return spreads of up to 7.6% on an annualized basis. This text-based predictability is higher among firms subject to higher degrees of business change, as proxied by R&D spending, product market fluidity, and gross profit volatility. Further, I show that call information predicts firm fundamentals up to six months following the earnings call. In sum, textual information contained in the only panel data set documenting the interaction between firm management and investors contains highly value-relevant information to which investors underreact.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355519549Subjects--Topical Terms:

559073
Finance.
Index Terms--Genre/Form:

554714
Electronic books.

Earnings Call Textual Information and the Cross-Section of Stock Returns.
LDR:02251ntm a2200349Ki 4500 001 909927
005 20180426091050.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355519549
035 $a (MiAaPQ)AAI10636932
035 $a (MiAaPQ)uchicago:14085
035 $a AAI10636932
040 $a MiAaPQ $b eng $c MiAaPQ
099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Bodmeier, Andreas. $3 1180942
245 1 0 $a Earnings Call Textual Information and the Cross-Section of Stock Returns.
264 0 $c 2017
300 $a 1 online resource (54 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: A.
500 $a Adviser: Samuel M. Hartzmark.
502 $a Thesis (Ph.D.) $c The University of Chicago $d 2017.
504 $a Includes bibliographical references
520 $a This paper investigates the informational value of corporate earnings calls in investment decision-making. I employ a computational linguistics approach to extract textual information from corporate earnings calls and show that it predicts returns beyond other previously identified predictors. Specifically, I find that portfolios sorted on the verbal information in earnings calls transcripts generate abnormal return spreads of up to 7.6% on an annualized basis. This text-based predictability is higher among firms subject to higher degrees of business change, as proxied by R&D spending, product market fluidity, and gross profit volatility. Further, I show that call information predicts firm fundamentals up to six months following the earnings call. In sum, textual information contained in the only panel data set documenting the interaction between firm management and investors contains highly value-relevant information to which investors underreact.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Finance. $3 559073
650 4 $a Business administration. $3 1148568
655 7 $a Electronic books. $2 local $3 554714
690 $a 0508
690 $a 0310
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of Chicago. $b Business. $3 1179073
773 0 $t Dissertation Abstracts International $g 79-03A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10636932 $z click for full text (PQDT)

筆 0 讀者評論

多媒體

評論

新增評論分享你的心得

Export

取書館別