內部人可能擁有操弄資訊揭露品質的空間，讓部分交易在不公平的情況發生，進而影響股票市場的波動，本文篩選出300間台灣上市公司在確保一定的流動性與市值下進行研究，以兩種不同的知情交易機率與波動度間的關係來代表資訊不對稱，並透過不同的董事股權集中的程度來進行分群實證，探討董事是否為造成資訊不對稱的原因之一，本文發現董事股權集中的中小型公司以及董事股權分散的大型公司有較嚴重的資訊不對稱。

Insiders may have the opportunity to manipulate the quality of information disclosure, leading to unfair situations in certain transactions and subsequently affecting stock market volatility. This study focuses on 300 listed companies in Taiwan, controlling for a certain level of liquidity and market capitalization for research purposes. The relationship between two different probabilities of informed trading and volatility is used to represent information asymmetry. The study also conducts empirical analysis by grouping companies based on the degree of director ownership concentration, exploring whether director ownership is one of the causes of information asymmetry. Our findings indicate that small and medium-sized companies with concentrated director ownership, as well as larger companies with dispersed director ownership, exhibit more severe information asymmetry.

Contents
論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
Content v
Tables vi
Chapter 1: Introduction: - 1 -
Chapter 2: Literature Review - 5 -
2-1 Equity Concentration and Information Asymmetry - 5 -
2-2 Measurement of Informed Trading - 7 -
Chapter 3: Data and Research Methodology - 11 -
3-1 Database - 12 -
3-2 Calculation of DPIN (Dynamic Probabilities of Informed Trading) - 14 -
3-3 Shareholding Concentration - 15 -
3-4 Calculation of MPIN (Markov Probabilities of Informed Trading) - 16 -
3-5 Research Model Setup - 17 -
Chapter 4: Empirical Results - 20 -
4-1 Association between Ownership Concentration and Information Asymmetry - 20 -
4-2 Indirect Relationship between Ownership and Information Asymmetry - 20 -
4-3 Relationship between Insider Trading Probability and Returns - 22 -
4-4 Empirical Results of MPIN - 23 -
Chapter 5: Robustness Analysis - 24 -
Chapter 6: Conclusion - 25 -
References - 28 -
Tables
Table (1) descriptive statistics - 31 -
Table (2) Regression analysis of equity concentration and DPIN - 32 -
Table (3) The impact on informed trading for SMEs (based on DPIN) - 33 -
Table (4) The impact on informed trading for SMEs (trend- DPIN) - 34 -
Table (5) The impact on informed trading for SMEs (T & D- DPIN) - 35 -
Table (6) The impact on informed trading for large enterprises (based on DPIN) - 36 -
Table (7) The impact on informed trading for large enterprises (trend- DPIN) - 37 -
Table (8) The impact on informed trading for large enterprises (T & D- DPIN) - 38 -
Table (9) The effectiveness of DPIN measurement. - 39 -
Table (10) The impact on informed trading for SMEs (MPIN) - 40 -
Table (11) The impact on informed trading for large enterprises (MPIN) - 41 -
Table (12): Interrelationships and Autocorrelation Coefficients of Informed Trading Probability. 42
Table (13) The impact of equity concentration on informed trading for SMEs (trend- DPIN&MPIN) 43
Table (14) The impact of equity concentration on informed trading for large enterprises (trend- DPIN&MPIN) 44
Table (15): Relationship between DPIN and unexpected volatility (SMEs) 45
Table (16): Relationship between DPIN and unexpected volatility (large enterprises) 46
Table (17): Relationship between MPIN and unexpected volatility (SMEs) 47
Table (18): Relationship between DPIN and unexpected volatility (large enterprises) 48
Table (19): Relationship between PINs and unexpected volatility (SMEs) 49
Table (20): Relationship between PINs and unexpected volatility (large enterprises) 50
APPENDIX A: Four-state Markov-Chain Switching Model 51
APPENDIX B: Classification of Order Initiation in Intraday 53
APPENDIX C: Variable Table 54

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