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The effect of basis functions on QLBS : QLBS 에서 기저 함수의 영향
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 이기암 | - |
dc.contributor.author | 문상필 | - |
dc.date.accessioned | 2023-06-29T02:35:59Z | - |
dc.date.available | 2023-06-29T02:35:59Z | - |
dc.date.issued | 2023 | - |
dc.identifier.other | 000000176945 | - |
dc.identifier.uri | https://hdl.handle.net/10371/194362 | - |
dc.identifier.uri | https://dcollection.snu.ac.kr/common/orgView/000000176945 | ko_KR |
dc.description | 학위논문(석사) -- 서울대학교대학원 : 자연과학대학 수학과, 2023. 2. 이기암. | - |
dc.description.abstract | The question of whether it is suitable to select a set of basis functions in a QLBS model without any restrictions is discussed in this research.
In his paper titled QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds, Igor Halperin proposed a discrete-time option hedging and pricing model known as QLBS. In the study, he proved that the QLBS model converges to the Black-Scholes-Merton model as the discrete-time interval converges to 0 under some circumstances, but he left the phenomenon where the discretetime interval is a specific positive number for future work. In this work, I will demonstrate that, depending on the choice of a set of basis functions, the reward setting in the QLBS model can result in option pricing that is different from the initial outcome expected. | - |
dc.description.abstract | 이 논문은 QLBS model 에서 a set of basis functions 가 제약 없이 선택되는 것이 적절한가에 대해 논의한다.
Igor Halperin 은 그의 논문 QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds 에서 QLBS 라는 discrete-time option hedging and pricing model 을 소개했다. 그는 그 논문에서 특정한 조건 하에 discrete-time 간의 간격이 0 으로 수렴할수록 QLBS model 이 Black-Scholes-Merton model 에 수렴함을 증명하였지만 그 간격이 구체적인 양수일 때의 현상은 future work 로 남겨두었다. 이 논문에서는 QLBS model 에서 설정한 reward 가 a set of basis functions 의 선택에 따라 애초에 기대했던 결과와 다른 option pricing 을 유도할 수 있다는 것을 보일 것이다. | - |
dc.description.tableofcontents | 1 Introduction 1
2 QLBS model 3 2.1 Discrete portfolio 3 2.2 Hedging and pricing at ∆t → 0 5 2.3 Transformation to stationary state variables 9 2.4 Bellman Equations 9 2.5 Optimal Policy 13 3 The optimal action and Q-function in QLBS 19 3.1 The optimal action 19 3.2 The optimal Q-function 27 4 Experiment : The optimal is not optimal 34 4.1 Experimental Design 34 4.2 Experimental results and analysis 35 Bibliography 38 Abstract (in Korean) 39 Acknowledgement (in Korean) 40 | - |
dc.format.extent | ii, 38 | - |
dc.language.iso | eng | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | QLBS | - |
dc.subject | 다이나믹 프로그래밍 | - |
dc.subject | 옵션 헷징 | - |
dc.subject | 옵션 가격결정 | - |
dc.subject | 마르코프 결정 과정 | - |
dc.subject.ddc | 510 | - |
dc.title | The effect of basis functions on QLBS | - |
dc.title.alternative | QLBS 에서 기저 함수의 영향 | - |
dc.type | Thesis | - |
dc.type | Dissertation | - |
dc.contributor.AlternativeAuthor | moon sangpil | - |
dc.contributor.department | 자연과학대학 수학과 | - |
dc.description.degree | 석사 | - |
dc.date.awarded | 2023-02 | - |
dc.identifier.uci | I804:11032-000000176945 | - |
dc.identifier.holdings | 000000000049▲000000000056▲000000176945▲ | - |
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