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Predicting Federal Funds Rate Using Extreme Value Theory.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Predicting Federal Funds Rate Using Extreme Value Theory./
作者:	Kumar Dey, Ashim.
面頁冊數:	1 online resource (66 pages)
附註:	Source: Masters Abstracts International, Volume: 81-05.
Contained By:	Masters Abstracts International81-05.
標題:	Statistics. -
電子資源:	click for full text (PQDT)
ISBN:	9781088395004

Predicting Federal Funds Rate Using Extreme Value Theory.
Kumar Dey, Ashim.

Predicting Federal Funds Rate Using Extreme Value Theory. - 1 online resource (66 pages)

Source: Masters Abstracts International, Volume: 81-05.

Thesis (M.S.)--Lamar University - Beaumont, 2019.

Includes bibliographical references

The extreme value theory (EVT) is a very vital aspect of statistics to assess the risk of extreme events caused by natural calamities or untoward circumstances in the social and economic sectors. In probability theory, and statistics, Leonard Tippett developed this theory to study the frequency of rare events and to build up a predictive model so that one can attempt to forecast the frequency of a financial collapse and the amount of damage from such an event. In this study, the Federal Funds Rate in the United States from 1954-2019 has been analyzed. The study has the following objectives. First, normalizing Federal Funds Rate data and fitting an appropriate model for the normalized Federal Funds Rate data. Secondly, predicting the maximum economic return rate from a Federal Funds Rate in the future by using the concept of the return period. Thirdly, applying both generalized extreme value (GEV) distribution and generalized Pareto distribution (GPD) to investigate and compare several estimation methods and their implications. Finally, we investigate the bias of estimated parameters applying a simulation study. Simulated data and real financial data are considered for our research, and the outcome satisfies the efficiency of its application.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9781088395004Subjects--Topical Terms:

556824
Statistics.
Subjects--Index Terms:

Extreme value theoryIndex Terms--Genre/Form:

554714
Electronic books.

Predicting Federal Funds Rate Using Extreme Value Theory.
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500 $a Advisor: Das, Kumer Pial.
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520 $a The extreme value theory (EVT) is a very vital aspect of statistics to assess the risk of extreme events caused by natural calamities or untoward circumstances in the social and economic sectors. In probability theory, and statistics, Leonard Tippett developed this theory to study the frequency of rare events and to build up a predictive model so that one can attempt to forecast the frequency of a financial collapse and the amount of damage from such an event. In this study, the Federal Funds Rate in the United States from 1954-2019 has been analyzed. The study has the following objectives. First, normalizing Federal Funds Rate data and fitting an appropriate model for the normalized Federal Funds Rate data. Secondly, predicting the maximum economic return rate from a Federal Funds Rate in the future by using the concept of the return period. Thirdly, applying both generalized extreme value (GEV) distribution and generalized Pareto distribution (GPD) to investigate and compare several estimation methods and their implications. Finally, we investigate the bias of estimated parameters applying a simulation study. Simulated data and real financial data are considered for our research, and the outcome satisfies the efficiency of its application.
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653 $a Generalized extreme value distribution
653 $a Generalized pareto distribution
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