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A Volatility Market with Heterogeneo...

Yang, Yuanyuan.

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A Volatility Market with Heterogeneous Forecasts.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Volatility Market with Heterogeneous Forecasts./
作者:	Yang, Yuanyuan.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	165 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-04, Section: A.
Contained By:	Dissertations Abstracts International80-04A.
標題:	Finance. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10843819
ISBN:	9780438461116

A Volatility Market with Heterogeneous Forecasts.
Yang, Yuanyuan.

A Volatility Market with Heterogeneous Forecasts. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 165 p.

Source: Dissertations Abstracts International, Volume: 80-04, Section: A.

Thesis (Ph.D.)--Illinois Institute of Technology, 2018.

This item must not be sold to any third party vendors.

This research includes four main aspects. First, a small universe trading game methodology is introduced as an evaluation methodology to assess the out-of-sample performance of competing volatility forecasting models. Second, this new methodology is compared with one of the classic evaluation measures of RMSE in terms of the speed of identifying the best performance model. Third, the Generalized Lambda Distribution is applied in the field of volatility forecasting. Finally, the daily absolute return contract is proposed, which can be used to better hedge the VaR exposure during the next trading day, and used as the trading subject in the small universe. Evidences show that the trading game methodology works faster, and with higher confidence level than RMSE to find out the best models.

ISBN: 9780438461116Subjects--Topical Terms:

542899
Finance.
Subjects--Index Terms:

Asymmetric variance mixture of normal distributions

A Volatility Market with Heterogeneous Forecasts.
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500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Cooper, Ricky A.;Bilson, John F. O.
502 $a Thesis (Ph.D.)--Illinois Institute of Technology, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a This research includes four main aspects. First, a small universe trading game methodology is introduced as an evaluation methodology to assess the out-of-sample performance of competing volatility forecasting models. Second, this new methodology is compared with one of the classic evaluation measures of RMSE in terms of the speed of identifying the best performance model. Third, the Generalized Lambda Distribution is applied in the field of volatility forecasting. Finally, the daily absolute return contract is proposed, which can be used to better hedge the VaR exposure during the next trading day, and used as the trading subject in the small universe. Evidences show that the trading game methodology works faster, and with higher confidence level than RMSE to find out the best models.
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653 $a Daily absolute return contract
653 $a Generalized lambda distribution
653 $a Trading game methodology
653 $a Volatility forecasting models
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