國立虎尾科技大學 |

Volatility forecasting using a decision-based attribution framework.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Volatility forecasting using a decision-based attribution framework./
作者:	Li, Tingting.
面頁冊數:	1 online resource (72 pages)
附註:	Source: Dissertation Abstracts International, Volume: 77-11(E), Section: A.
Contained By:	Dissertation Abstracts International77-11A(E).
標題:	Finance. -
電子資源:	click for full text (PQDT)
ISBN:	9781339922140

Volatility forecasting using a decision-based attribution framework.
Li, Tingting.

Volatility forecasting using a decision-based attribution framework. - 1 online resource (72 pages)

Source: Dissertation Abstracts International, Volume: 77-11(E), Section: A.

Thesis (Ph.D.)

Includes bibliographical references

This research develops a portfolio volatility forecasting method for absolute return equity strategies with consideration of managers' investment skills. Besides the portfolio holdings and prices that are commonly used by existing volatility forecast methodologies, the method proposed in this research takes account of investment skills and their volatility attribution. Investment skills are indicated by decisions of constructing portfolio overtime. Portfolio volatility is attributed to investment decisions through use of decision-based performance attribution model. It is shown that tracking the information contained in the time series of investment decision attribution leads to better volatility forecasts than commonly used forecasting methods which directly use returns and holdings. The forecasting method proposed has advantage of explaining risk forecast in terms of actual investment decisions, and changes to those decisions in real time.

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

Mode of access: World Wide Web

ISBN: 9781339922140Subjects--Topical Terms:

559073
Finance.
Index Terms--Genre/Form:

554714
Electronic books.

Volatility forecasting using a decision-based attribution framework.
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245 1 0 $a Volatility forecasting using a decision-based attribution framework.
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500 $a Source: Dissertation Abstracts International, Volume: 77-11(E), Section: A.
500 $a Adviser: Ricky Cooper.
502 $a Thesis (Ph.D.) $c Illinois Institute of Technology $d 2016.
504 $a Includes bibliographical references
520 $a This research develops a portfolio volatility forecasting method for absolute return equity strategies with consideration of managers' investment skills. Besides the portfolio holdings and prices that are commonly used by existing volatility forecast methodologies, the method proposed in this research takes account of investment skills and their volatility attribution. Investment skills are indicated by decisions of constructing portfolio overtime. Portfolio volatility is attributed to investment decisions through use of decision-based performance attribution model. It is shown that tracking the information contained in the time series of investment decision attribution leads to better volatility forecasts than commonly used forecasting methods which directly use returns and holdings. The forecasting method proposed has advantage of explaining risk forecast in terms of actual investment decisions, and changes to those decisions in real time.
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 Applied mathematics. $3 1069907
655 7 $a Electronic books. $2 local $3 554714
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690 $a 0364
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710 2 $a Illinois Institute of Technology. $b Business. $3 1179077
773 0 $t Dissertation Abstracts International $g 77-11A(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10133639 $z click for full text (PQDT)