本研究以台灣市場為對象，利用高頻率的日內資料，進行波動度外溢假說的驗證，並藉投資人行為觀察其成因。本研究參考Kim and Yang (2008)的做法，將漲跌停板狀況分為單點觸碰、鎖死及有打開三種類型，再加上漲停與跌停兩種市場方向共計六種漲跌停型態，進行波動度外溢假說之實證研究。並將股票市場中的參與者區分為外資、散戶、自營商及其它國內法人四類，以流動性及委託單不平衡做為投資人下單行為的代理變數，以分析其中行為對漲跌停板後之股票市場波動度之影響。並進一步分析該行為是否具有資訊性。
研究結果顯示波動度外溢只存在於跌停板狀態，漲停板之狀態皆如漲跌停限制制度設立原意可降低市場波動度，而使波動度降低的原因主要來自於散戶。且波動度的降低並非雜訊性的波動。隱含漲跌停板確實為散戶帶來訊號致使散戶行為做出改變，緩和了市場波動，此結果亦支持了機構投資人於平常時較散戶更具有資訊性的觀點。

The purpose of this paper is to test the volatility spillover hypothesis by analyzing high-frequency intraday data from Taiwan. To investigate the effects of the price limits on volatility spillover, we consider three types of price limits according to Kim and Yang (2008): hits-single, locked, and opened. Each type has upper and lower limits. Investors are also separated into four categories: foreign institutional investors, individual investors, dealers and domestic institutional investors. Both liquidity and order imbalance are employed of analyze investors’ behavior with report to factors influencing volatility change.
Our evidence indicates that only lower price limits causes volatility spillover. While behaviors of individual investors cause the price limits system to stabilize market fluctuations when upper price limits is reached. However, the volatility changes at price limits is the actual volatility without noise, which implies that price limits send significant signals to individual investors to change their behavior. This is consisted with the view that institutional investors have information advantage over other investors in general.

目錄

第一章 前言	1
第一節 研究動機與背景	1
第二節 研究目的	3
第三節 研究架構	4
第四節 研究流程	5
第二章 文獻回顧	6
第一節 漲跌停限制	6
第二節 報酬波動度與交易量	9
第三節 雜訊	12
第四節 流動性	15
第五節 買賣不平衡	19
第三章 研究方法	21
第一節 研究期間與樣本篩選	21
第二節 資料處理	26
第三節 變數計算	34
第四節 理論驗證方法及迴歸模型設定	41
第四章 實證結果與分析	44
第一節 波動度外溢假說	44
第二節 敘述統計分析	48
第三節 相關係數及共線性分析	51
第四節 迴歸實證模型之全市場分析	54
第五節 迴歸實證模型之各類投資人分析	59
第六節 開盤觸碰漲跌停限制之驗證	65
第五章 結論	69
參考文獻	72
 
表目錄

表3-1投資人類別成交值比重	23
表3-2委託檔資料格式	24
表3-3成交檔檔資料格式	25
表3-4揭示檔資料格式	25
表3-5漲跌停板次數統計	32
表3-5每檔股票發生漲跌停次數敘述統計	33
表4-1漲跌停板前後波動度敘述統計	45
表4-2波動度外溢檢定	47
表4-3市場波動度與雜訊敘述統計	49
表4-4全市場限價委託簿變數敘述統計	50
表4-5皮爾森相關係數	52
表4-6共線性檢定-VIF值	53
表4-7全市場委託簿變數變動對波動度變動之影響	57
表4-8全市場委託簿變數變動對雜訊變動之影響	58
表4-9投資人分群限價委託簿變數敘述統計	60
表4-10各類投資人委託簿變數變動對波動度變動之影響	63
表4-11各類投資人委託簿變數變動對雜訊變動之影響	64
表4-12開盤後15分鐘觸碰漲跌停板次數統計	66
表4-13開盤觸碰漲跌停限制下委託簿變數變動對波動度變動之影響	67
表4-14開盤觸碰漲跌停限制下委託簿變數變動對雜訊變動之影響	68
 
圖目錄

圖1-1論文架構圖	5
圖3-1單點觸碰(single)狀態示意圖	30
圖3-2鎖死(locked)狀態示意圖	30
圖3-3有打開(opened)狀態示意圖	30

1.	胡星陽、梁敏芳（1995），「漲跌幅限制與台灣證券市場波動性」，證券市場發展季刊，第7 卷第1 期，p1-24。
2.	Anderson, T., 1996, “ Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility”, Journal of Finance 51, 169-204.
3.	Bagchi, D., 2006, “ Noise Trading in an Emerging Market: Evidence and Analysis”, New Economic Windows 1, 77-84.
4.	Barber, B., T. Odean and N. Zhu, 2006, “ Do Noise Trader Move Markets”, Working Paper.
5.	Bildik, R., and Elekdag, S., 2004, “Effects of price limits on volatility: Evidence from the Istanbul stock exchange”, Emerging Markets Finance and Trade, 40(1), 5-34.
6.	Bildik, R., and Gulay, G., 2006. “Are price limits effective? evidence from the Istanbul stock exchange”, Journal of Financial Research, 29(3), 383-403.
7.	Black, F., 1986, “ Noise” Journal of Finance 41, 529-543.
8.	Brennan, M. J., 1986,”Report of the Presidential Task Forceon Market Mechanism”.
9.	Brown, P., D. Walsh and A. Yuen, 1997, “ The Interaction between Order Imbalance and Stock Price” , Pacific-Basin Finance Journal 5, 539-557.
10.	Chan, K and W. M. Fong, 2000, “ Trade Size, Order Imbalance, and the Volatility-Volume Relation”, Journal of Financial Economics 57, 247-273.
11.	Chan, S. H., Kim, K. A., and Rhee, S. G., 2005, “Price limit performance: Evidence from transactions data and the limit order book”, Journal of Empirical Finance, 12(2), 269-290.
12.	Chordia, T and A. Subrahmanyam, 2004, “ Order Imbalance and Individual Stock Returns: Theory and Evidence”, Journal of Financial Economics 72, 485-518.
13.	Chordia, T., R. Roll and A. Subrahmanyam, 2008, “ Liquidity and Market Efficiency”, Journal of Financial Economics 87, 249-268.
14.	Chordia, T., R. Roll and A. Subrahmanyam, 2002, “Order Imbalance, Liquidity, and Market Returns”, Journal of Financial Economics 65, 111-130.
15.	Christopher K. Ma, Ramesh P. Rao, and R. Stephen Sears, 1989,”Limit Moves and Price Resolution: The Case of The Treasure Bond Futures Market”, Journal of Futures Markets, p321-335.
16.	Clark, P., 1973, “A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices” Econometrica 41, 135-155.
 
17.	Copeland TE., 1976, “A Model of Asset Trading under The Assumption of Sequential Information Arrival”, Journal of Finance 31: 1149–1168
18.	De Long, J., A. Shleifer, L. Summer and R. Waldmann, 1990, “ The Survival of Noise Traders in Financial Markets”, Working Paper.
19.	Easley, D and M. O’Hara, 1987, “ Price, Trade Size, and Information in Securities Markets,” Journal of Financial Economics 19, 69-90.
20.	Fama, E. F., Kamphuis, R., Kormendi, R., and Watson, J., 1989, “Black Monday and the future of financial markets”, Perspectives on October 1987, 155–179.
21.	Fan, Y. J and H. N. Lai, 2006, “The Intraday Effect and the Extension of Trading Hours for Taiwanese Securities”, International Review of Financial Analysis 15, 328-347.
22.	France, V. G., Kodres, L., and Moser, J. T., 1994, “A review of regulatory mechanisms to control the volatility of prices”, Economic Perspectives, 18(6).
23.	French, K and R. Roll, 1986, “Stock Return Variances the Arrival of Information and the Reaction of Traders”, Journal of Financial Economics 17, 5-26.
24.	Garbade, K and W. Silber, 1979, “Structural Organization of Secondary Market: Clearing Frequency, Dealer Activity and Liquidity Risk”, Journal of Finance 34, 577-593.
25.	Glosten, L and L. Harris, 1988, “Estimating the Components of the Bid/Ask Spread”, Journal of Financial Economics 21, 123-142.
26.	Harris, L., 1987, “Transaction Data Test of the Mixture of distribution Hypothesis”, Journal of Financial and Quantitative Analysis 22, 127-141.
27.	Stoll, H., 1978, “The pricing of dealer services: an empirical study of NASDAQ stocks”, Journal of Finance 33, 1152-1173.
28.	Hu, S. Y., 2006, “A Simple Estimate of Noise and it’s Determinant in a Call Auction Market”, International Review of Financial Analysis, 15, 348-362.
29.	Jain, P and G. H. Joh, 1988, “The Dependence between Hourly Prices and Trading Volume”, Journal of Financial and Quantitative Analysis, 23, 269-283.
30.	Jennings R, Starks L, Fellingham J., 1981, “An equilibrium model of asset trading with sequential information arrival”, Journal of Finance, 36, 143–161.
31.	Jie-Haun Lee, and Robin K. Chou, (2004), “The intraday stock return characteristics surrounding price limit hit”, Journal of Multinational Financial Management, 14, 485-501.


32.	Kang, W. and W.Y. Yeo ,(2008), "Liquidity Beyond the Best Quote: A Study of the NYSE Limit Order Book", National University of Singapore working paper.
33.	Karpoff, J., 1986, “A Theory of Trading Volume”, Journal of Finance 41, 1069-1087.
34.	Kim, Y. H., and Yang, J. J., 2008, “The effect of price limits on intraday volatility and information asymmetry”, Pacific-Basin Finance Journal, 16(5), 522-538.
35.	Kim, K. A., and Rhee, S. G., 1997, “Price limit performance: Evidence from the Tokyo stock exchange”, Journal of Finance, 52(2), 885-901.
36.	Kodres, L. E. and D. P. O’Brien, 1994, “The Existence of Pareto-Superior Price Limits”, American Economic Review 74, 919-932.
37.	Kyle, A., 1985, “Continuous Auctions and Insider Trading”, Econometrica 53, 1315-1335.
38.	Lee, S. B. and J. S. Chung, 1996, “Price Limits and Stock Market Efficiency”, Journal of Business Finance & Accounting 23, 585-601.
39.	Lee, S. B. and K. J. Kim, 1995, “The Effect of Price Limits on Stock Prie Volatility: Empirical Evidence in Korea”, Journal of Business Finance & Accounting 22, 257-267.
40.	Lee, Y. T., Y. J. Liu, R. Roll and A. Subrahmanyam, 2004, “Order Imbalance and Market Efficiency: Evidence from the Taiwan Stock Exchange,” Journal of Financial and Quantitative Analysis 39, 327-341.
41.	Lin ,William T., S.C. Tsai and D. S. Sun, 2012,” Search Costs and Investor Trading Activity: Evidences from limit order book”, Forthcoming on Emerging Markets Finance & Trade.
42.	Lo, A and A. Mackinlay, 1988, “Stock Market Price do not Follow Random Walks: Evidence from a Simple Specification Test”, Review of Financial Studies 1, 41-66.
43.	Ma, C. K., Rao, R. P., and Sears, R. S., 1989, “Volatility, price resolution, and the effectiveness of price limits”, Journal of Financial Services Research, 3(2), 165-199.
44.	Madhavan, A., 1992, “Trading Mechanisms in Securities Markets”, Journal of Finance 47, 607-641.
45.	Mendelson, H., 1982, “Market Behavior in a Clearing House,” Econometrica 50, 1505-1524.
46.	Phylaktis, K., Kavussanos, M., and Manalis, G., 1999, ”Price limits and stock market volatility in the Athens stock exchange”, European Financial Management, 5(1), 69-84.
47.	Smirlock M and Starks L., 1985, “A further examination of stock price changes and transaction volume”, Journal of Financial Research 8: 217–225.

48.	Thomas C. Chiang, Zhuo Qiao, and Wing-Keung Wong, 2010, “New Evidence on the Relation between Return Volatility and Trading Volume”, Journal of Forecasting 29, 502-515.
49.	Wood, R., T. Mclnish and J. Ord, 1985, “An Investigation of Transaction Data for NYSE Stocks”, Journal of Finance 40, 723-739.
50.	Wu, C and X. Xu, 2000, “Return Volatility, Trading Volume and the Information Content of Volume”, Review of Quantitative Finance and Accounting 14, 131-153.
51.	Xu, X., P. Chen and C. Wu, 2006, “ Time and Dynamic Volume-Volatility Relation,” Journal of Banking & Finance 30, 1535-1588.