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博碩士論文 etd-0729103-171101 詳細資訊
Title page for etd-0729103-171101
論文名稱
Title
漲跌停限制與新上市股票長期績效:異象或模型設定不當
Long-run Stock Performance of Initial Public Offerings with Price Limits: Anomaly or Misspecification
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
97
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2003-07-29
繳交日期
Date of Submission
2003-07-29
關鍵字
Keywords
新上市股票、長期績效、漲跌停限制
long-run performance, IPO, price limits
統計
Statistics
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中文摘要
摘要
本文採用1991年至1998 年間在台灣股票市場新上市的普通股做為樣本,分析新上市股票市場的理性行為。採用兩種市場效率假說: 效率市場假說(efficient markets hypothesis)及有效學習市場(efficiently learning market )假說。風險評價分別採用市場投資組合報酬,市場模型(market model),及三因子模型。當收盤價遇到漲停或跌停時,採用 Tobit model 估計沒有漲跌停限制下的均衡價格。
除了檢驗市場效率性假說外,本文亦分析新上市股票在橫斷面及縱斷面的報酬型態。 包括引入競價拍賣對市場效率的影響、現金增資在新上市股票長期績效中扮演的角色、在發行旺季上市的股票報酬型態所代表的意涵、及檢驗是否存在momentum和mean reversion的現象。
研究結果顯示,當採用市場模型或三因子模型評價風險時,新上市股票樣本符合有效學習市場假說的理性學習要求。橫斷面與時間數列的報酬型態顯示市場並沒有過度反應,而是循序漸進且保守的學習。因此,當模型定義恰當時,新上市股票並沒有異常現象。

Abstract
Abstract
By using Tobit model to remove price limit regulation from the limited price data, this study analyzes the IPO aftermarket’s rationality using a sample of 362 stocks which conducted IPO between 1991 and 1998 in Taiwan stock markets. Two market efficiency hypotheses were examined: the efficient markets hypothesis (EMH) and the hypothesis of efficiently learning market (ELM). The later relaxed EMH by letting prior beliefs to be unspecified. Risk was valued by market portfolio return, market model, and an alteration of Fama-French three-factor model. Tobit model is used to remove price limits in case of limit-move day. In addition to examining the hypotheses of market efficiency, this study also explores cross-section and time-series return patterns. We are interested in the effect of competitive bidding on market efficiency, the role of SEO on IPOs long-run performance, the implication of heavy issuance return pattern, and momentum and mean reversion. The results show that our IPO sample does learn rationally from information in the sense of ELM in conjunction with market model or thee-factor model. The cross-section and time-series results indicate that market is not ‘overreaction’ or ‘fad’, but learning sequentially and cautiously. Thus, the IPOs long-run anomalies disappear in our sample if model is properly defined.

目次 Table of Contents
Table of Contents
Chapter 1. Introduction 1
1.1 Rationale 1
1.2 Purpose 4
1.3 Overview of the Research methodology 5
1.4 The structure of this Study 6
Chapter 2. Literature Review 8
2.1. Asset Pricing Theory 8
2.2 Rationality 10
2.3 Market efficiency 12
2.4 Price limits and market efficiency 15
2.5 Evidence on IPO long-run performance and competing explanations 19
2.6 Other issues 22
2.7 Empirical evidences of IPO long-run Performance in Taiwan 27
Chapter 3. History and Structure of Taiwan Primary Stock Market 31
Chapter 4. Data and Methodology 38
4.1 Data 38
4.2 Methodology 42
Chapter 5. Empirical Results 52
5.1 Evidence on EMH 52
5.2 Evidence on ELM 57
5.3 Cross-sectional and time-series patterns 64
Chapter 6. Conclusions and Suggestions 85
6.1 Conclusions 85
6.2 Suggestions for further research 87
References 88


List of Tables
Table 1 Summary of Empirical results of Taiwan IPO Stock Long-run Performance 30
Table 2 Criteria for Securities Listings 32
Table 3 Criteria for Public offering proportion 35
Table 4 Allocation of IPO 36
Table 5 Price Limits for TES and GTSM 37
Table 6 Limited Price Distribution of IPO Firms and All Listed Firms 40
Table 7 Distribution of Initial Public Offerings by Year, 1991-1998 41
Table 8 Distribution of the Overnight Returns 56
Table 9 Aftermarket Performance Categorized by Allocating Methods 68
Table 10 Aftermarket Performance Categorized by Offering Time and Proportion of Subscribing Orders Receiving an Allocation of IPO Shares 70
Table 11 Aftermarket Performance Categorized by SEO 73
Table 12 Aftermarket Performance Categorized by Initial Return Size and Waiting Time Between IPO and SEO 74
Table 13 Aftermarket Performance Categorized by IPO Volume and Industry 78
Table 14 Aftermarket Performance Categorized by Offering Year and industry 80


List of Figures
Figure 1 Time Series of IPO Issuance and Market Index 42
Figure 2 Event-time Risk Adjusted Returns under Efficient Markets Hypothesis 53
Figure 3 Event-time Risk Adjusted Return under Efficient Markets Hypothesis with Limited Price Was Replaced by Estimate of ‘True’ Equilibrium Price. 55
Figure 4 Event-time Risk Adjusted Return under Efficiently Learning Market Hypothesis with Risk Adjusted by Market Index Return. 58
Figure 5 Event-time Risk Adjusted Return under Efficiently Learning Market Hypothesis with Risk Adjusted by Market Return and Limited Price was Replaced by Estimate of ‘True’ Equilibrium Price. 59
Figure 6 Event-Time Risk Adjusted Return under Efficiently Learning Market Hypothesis with Risk Adjusted by Market Model and Limited Price Was Replaced by Estimate of ‘True’ Equilibrium Price 62
Figure 7 Event-time Risk Adjusted Return under Efficiently Learning Market Hypothesis with Risk Adjusted by Three-factor Model and Limited Price Was Replaced by Estimate of ‘True’ Equilibrium Price 63
Figure 8 Aftermarket Performance of IPOs Allocating by Competitive Bidding Combining with Public Subscription: Categorized by Offering Date 69
Figure 9 IPO Aftermarket Performance Categorized by Offering Quarter 81
Figure 10 Aftermarket Performance Categorized by Initial Return 83

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