Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Essays in Finance and Behavioral Eco...
~
Wang, Shirui.
Linked to FindBook
Google Book
Amazon
博客來
Essays in Finance and Behavioral Economics.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Essays in Finance and Behavioral Economics./
Author:
Wang, Shirui.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:
104 p.
Notes:
Source: Dissertations Abstracts International, Volume: 82-07, Section: A.
Contained By:
Dissertations Abstracts International82-07A.
Subject:
Finance. -
Online resource:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28090994
ISBN:
9798557071468
Essays in Finance and Behavioral Economics.
Wang, Shirui.
Essays in Finance and Behavioral Economics.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 104 p.
Source: Dissertations Abstracts International, Volume: 82-07, Section: A.
Thesis (Ph.D.)--Iowa State University, 2020.
This item must not be sold to any third party vendors.
This dissertation consists of two chapters on finance and experimental economics.The first chapter studies the dynamic portfolio optimization problem with reinforcement learning. I evaluate several algorithms on simulated data to document their convergence properties and sample efficiencies. I also apply a state-of-the-art algorithm on two empirical problems and show that they outperform other traditional strategies.The second chapter studies alternating bargaining games, by proposing an ultimatum game with uncertainties. I model the two-stage game as a screening game that incorporates the social factor of fairness, and run experiments to analyze how participants behave in response to bargaining power shift.
ISBN: 9798557071468Subjects--Topical Terms:
542899
Finance.
Subjects--Index Terms:
Portfolio optimization
Essays in Finance and Behavioral Economics.
LDR
:01809nmm a2200349 4500
001
2277639
005
20210521102455.5
008
220723s2020 ||||||||||||||||| ||eng d
020
$a
9798557071468
035
$a
(MiAaPQ)AAI28090994
035
$a
AAI28090994
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Wang, Shirui.
$3
1678836
245
1 0
$a
Essays in Finance and Behavioral Economics.
260
1
$a
Ann Arbor :
$b
ProQuest Dissertations & Theses,
$c
2020
300
$a
104 p.
500
$a
Source: Dissertations Abstracts International, Volume: 82-07, Section: A.
500
$a
Advisor: Hoffman, Elizabeth;Wang, Zhengdao.
502
$a
Thesis (Ph.D.)--Iowa State University, 2020.
506
$a
This item must not be sold to any third party vendors.
520
$a
This dissertation consists of two chapters on finance and experimental economics.The first chapter studies the dynamic portfolio optimization problem with reinforcement learning. I evaluate several algorithms on simulated data to document their convergence properties and sample efficiencies. I also apply a state-of-the-art algorithm on two empirical problems and show that they outperform other traditional strategies.The second chapter studies alternating bargaining games, by proposing an ultimatum game with uncertainties. I model the two-stage game as a screening game that incorporates the social factor of fairness, and run experiments to analyze how participants behave in response to bargaining power shift.
590
$a
School code: 0097.
650
4
$a
Finance.
$3
542899
653
$a
Portfolio optimization
653
$a
Reinforcement learning
653
$a
Ultimatum game
690
$a
0501
690
$a
0511
690
$a
0508
710
2
$a
Iowa State University.
$b
Economics.
$3
1033976
773
0
$t
Dissertations Abstracts International
$g
82-07A.
790
$a
0097
791
$a
Ph.D.
792
$a
2020
793
$a
English
856
4 0
$u
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28090994
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9429373
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login