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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳聖賢 | |
dc.contributor.author | Shang-Ching Li | en |
dc.contributor.author | 李尚璟 | zh_TW |
dc.date.accessioned | 2021-07-10T21:36:41Z | - |
dc.date.available | 2021-07-10T21:36:41Z | - |
dc.date.copyright | 2016-10-17 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-06-29 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/76774 | - |
dc.description.abstract | 我們認為不平衡關係似乎是為什麼我們經常會發現股票市場風險與報酬之間不具顯著關係的原因。由於這個因素,為了此不平衡回歸,我們提出新一類的估計方法(取名為GCO-AR)能讓回歸兩側為I(0),I(1)或I(d) 但不盡相同。此估計方法十分方便在於它不需要先行估計長期記憶的係數。我們的模擬結果證實了這新估計方法的有效性。接著,我們只使用此新估計方法與市場波動指數,而非條件變異數模型作為條件變異數的估計,重新檢視跨期風險報酬抵換關係。從GCO-AR的估計,我們發現在六大國際股票市場確實存在顯著的風險與報酬抵換關係,而這些相對風險趨避指數在經濟上合理。 | zh_TW |
dc.description.abstract | We argue that the imbalance issue seems to be the reason why we often find insignif- icant relation between risk and return in the equity market. In light of this problem, we propose a new class of estimation, named GCO-AR, for the imbalanced regression where we allow the orders of both sides of the regression to be I(0), I(1) or I(d) processes (long memory processes) but are not equal to each other. The implementation of our estimator is convenient since it does not necessitate the estimation of fraction integer. All simulations provide the evidence on the usefulness of our methodology. We then employ our new estimation to re-examine the intertemporal risk- return tradeoff with market volatility indices rather than conditional heteroskedasticity models as a proxy to the conditional variance. With GCO-AR estimation, we shed new lights on the relation between conditional risk premium and conditional variance, where we do find significantly positive and reasonable estimates of the coefficient of relative risk aversion across six major equity indices. | en |
dc.description.provenance | Made available in DSpace on 2021-07-10T21:36:41Z (GMT). No. of bitstreams: 1 ntu-105-R03723057-1.pdf: 1699645 bytes, checksum: e505dc490ca4584816a028417fbd98ac (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 口試委員會審定書………………………………………………………………….i
摘要…………………………………………………………………………….…….ii Abstract……………………………………………………………………………iii 1. Introduction……………………………………………………………………...1 2. Literature Review………………………………………………………………4 3. The Main Models and GCO-AR Class Estimation………………………7 3.1. GCO-AR(I) Estimator………………………….………………………...7 3.2. GCO-AR(II) Estimator…………………..………………………………9 4. Simulation Results……………………………………………………………11 4.1. Simulation Setup………………………………………………………11 4.2. Estimation Performance………………………………………………13 5. Empirical Applications……………………………………………………….16 5.1. Data and Summary statistics………………………………………..…16 5.2. The Intertemporal Risk-Return Tradeoff……………………………21 5.3. Robustness Checks………………………………………………………23 5.3.1. The Choice of k……………………………………………….23 5.3.2. The Volatility Risk Premium Bias…………………………..24 6. Concluding Remark…………………………………………………………...25 REFERENCES…………………………………………………………………….27 | |
dc.language.iso | en | |
dc.title | 跨期報酬風險抵換關係 | zh_TW |
dc.title | On the Intertemporal Risk-Return Tradeoff | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 王馨徽 | |
dc.contributor.oralexamcommittee | 蔡恆修 | |
dc.subject.keyword | 不平衡回歸,AR估計,長期記憶過程,跨期風險報酬抵換關係, | zh_TW |
dc.subject.keyword | Imbalanced regression,AR approximation,long memory processes,Intertemporal risk-return tradeoff, | en |
dc.relation.page | 57 | |
dc.identifier.doi | 10.6342/NTU201600427 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2016-06-30 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
顯示於系所單位: | 財務金融學系 |
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