請用此 Handle URI 來引用此文件：
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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林修葳(Hsiou-Wei Lin) | |
| dc.contributor.author | Kendro Vincent | en |
| dc.contributor.author | 羅秉政 | zh_TW |
| dc.date.accessioned | 2021-06-17T02:12:47Z | - |
| dc.date.available | 2020-01-04 | |
| dc.date.copyright | 2018-01-04 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-12-19 | |
| dc.identifier.citation | Acharya, V. V. and Pedersen, L. H. (2005). Asset pricing with liquidity risk. Journal of Financial Economics, 77:375–410.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68109 | - |
| dc.description.abstract | 本論文使用多重檢定方法探討實證金融文獻裡的股市異常報酬現象。為了尋找可獲得異常報酬之選股策略，投資領域專家已不斷的檢定許多模型。若使用傳統假設檢定方法，所發現的優異選股策略可能為統計推論上偏誤所造成。在第一章，我們探討多因子投資策略是否真的提供投資人附加價值。由於投資人可使用不同排列組合建構多因子投資策略，我們必須使用多重檢定方法測試該選股策略之有效性。第二章探索股市橫斷面報酬率是否存在異常現象。該章節討論當我們可以針對異常現象進行分類時，是否影響多重檢定結果。 | zh_TW |
| dc.description.abstract | This dissertation joins the vibrant debate in the empirical finance literature about the cross-sectional stock return anomalies. The endless effort by the finance community to find profitable stock-picking rules has raised questions of data-snooping bias in the empirical findings. The two main chapters of this dissertation investigate the cross-section of stock returns with multiple testing method to eliminate the data-snooping bias concern. The first one examines the efficiency of multi-factor investment strategies prevalent in the equity ETF market. The second one explores the relevance of group information in testing the stock market anomalies. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T02:12:47Z (GMT). No. of bitstreams: 1 ntu-106-D01724008-1.pdf: 2645656 bytes, checksum: fda5f81315456bf19cee89d12e464c3d (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | List of Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Analyzing the Performance of Multi-Factor Investment Strategies under Multiple Testing Framework. . . . . . 3 2.1 Error Control in Multiple Testing . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . 4 2.2 Measuring Portfolio Performance . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . 7 2.3 Data and Portfolio Construction . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . 8 2.4 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3 Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?. . . . . . . . . . . . 24 3.1 Multiple Testing Methodology . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 26 3.1.1 Pooled multiple testing with FWER(k) control . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . 28 3.1.2 Grouped multiple testing with average FWER over the selected families . . . . . . . . . . . . . . . . . 29 3.2 Data and Portfolio Construction . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 31 3.3 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.3.1 Pooled vs grouped multiple testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.3.2 Analysis with risk-adjusted returns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . 38 3.3.3 Anomalies in the period of increased liquidity . . . . . . .. . . . . . . . . . . . . . . . . . .. . . 41 3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . 43 3.5 Definition of Predictors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 A Step-SPA(k) algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 | |
| dc.language.iso | en | |
| dc.title | 多重檢定與股票報酬率橫斷面分析 | zh_TW |
| dc.title | Multiple Testing and the Cross-Section of Stock Returns | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-1 | |
| dc.description.degree | 博士 | |
| dc.contributor.coadvisor | 許育進(Yu-Chin Hsu) | |
| dc.contributor.oralexamcommittee | 陳宜廷(Yi-Ting Chen),江彌修(Mi-Hsiu Chiang),黃瑞卿(Ruey-Ching Hwang) | |
| dc.subject.keyword | 股票報酬率橫斷面分析,資料竊探偏誤,市場效率,多因子投資,多重檢定,智能選股,股市異常報酬, | zh_TW |
| dc.subject.keyword | cross-section of stock returns,data-snooping bias,market efficiency,multi-factor investing,multiple testing,smart beta,stock market anomalies., | en |
| dc.relation.page | 61 | |
| dc.identifier.doi | 10.6342/NTU201704469 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-12-19 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 國際企業學研究所 | zh_TW |
| 顯示於系所單位： | 國際企業學系 | |
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