國立虎尾科技大學 |

Hedge Fund Performance and Derivative Hedging.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Hedge Fund Performance and Derivative Hedging./
作者:	Li, Yongjia.
面頁冊數:	1 online resource (138 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.
Contained By:	Dissertation Abstracts International78-12A(E).
標題:	Finance. -
電子資源:	click for full text (PQDT)
ISBN:	9780355098600

Hedge Fund Performance and Derivative Hedging.
Li, Yongjia.

Hedge Fund Performance and Derivative Hedging. - 1 online resource (138 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: A.

Thesis (Ph.D.)--University of Arkansas, 2017.

Includes bibliographical references

This dissertation is comprised of three essays which focus on hedge fund performance and derivative hedging. The first essay uses ETF returns as proxies for tradable risk factors in hedge fund performance evaluation and identifies contemporaneously relevant risk factors from the entire universe of ETFs. The model provides more informative estimates of alpha and beta coefficients for predicting hedge fund out-of-sample performance compared with other widely used hedge fund factor models. Portfolios of top alpha hedge funds selected by the model generate statistically significant out-of-sample performance that is substantially higher compared with portfolios selected by other models. In addition, the beta-weighted clone portfolios exhibit substantially higher out-of-sample correlations with underlying hedge funds than clone portfolios formed using alternative models.

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

Mode of access: World Wide Web

ISBN: 9780355098600Subjects--Topical Terms:

559073
Finance.
Index Terms--Genre/Form:

554714
Electronic books.

Hedge Fund Performance and Derivative Hedging.
LDR:03341ntm a2200349Ki 4500 001 919100
005 20181116131020.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355098600
035 $a (MiAaPQ)AAI10603298
035 $a (MiAaPQ)uark:12631
035 $a AAI10603298
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Li, Yongjia. $3 1193591
245 1 0 $a Hedge Fund Performance and Derivative Hedging.
264 0 $c 2017
300 $a 1 online resource (138 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: 78-12(E), Section: A.
500 $a Adviser: Alexey Malakhov.
502 $a Thesis (Ph.D.)--University of Arkansas, 2017.
504 $a Includes bibliographical references
520 $a This dissertation is comprised of three essays which focus on hedge fund performance and derivative hedging. The first essay uses ETF returns as proxies for tradable risk factors in hedge fund performance evaluation and identifies contemporaneously relevant risk factors from the entire universe of ETFs. The model provides more informative estimates of alpha and beta coefficients for predicting hedge fund out-of-sample performance compared with other widely used hedge fund factor models. Portfolios of top alpha hedge funds selected by the model generate statistically significant out-of-sample performance that is substantially higher compared with portfolios selected by other models. In addition, the beta-weighted clone portfolios exhibit substantially higher out-of-sample correlations with underlying hedge funds than clone portfolios formed using alternative models.
520 $a The second essay shows that only hedge funds whose returns are driven by beta management of exposures to latent risk factors could be successfully replicated. I develop a methodology for creating a portfolio of ETFs that replicates risk factor exposures taken by successful beta active cloneable hedge funds. The methodology allows any investor to access active factor strategies employed by hedge funds. It could be interpreted as cloning beta exposures of the best beta active hedge funds, delivering outstanding long-term risk-adjusted performance. The active factor ETF portfolio only requires annual rebalancing, and is constructed with a transparent algorithmic approach, which conforms to a definition of a smart beta strategy.
520 $a The third essay investigates the use of derivatives among firms. A careful study of hedging motives and hedging effectiveness is critical to understanding the financial impact of derivative use by firms. I examine the use of commodity derivatives by oil and gas producers and show that, on average, these firms report gains from their derivative positions. The profits from derivatives, particularly non-hedge profits, are positively associated with the extent of hedging that is classified as market timing activities.
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
655 7 $a Electronic books. $2 local $3 554714
690 $a 0508
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Arkansas. $b Finance. $3 1193592
773 0 $t Dissertation Abstracts International $g 78-12A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10603298 $z click for full text (PQDT)