| 研究生: |
陳怡君 Yi Chun Chen |
|---|---|
| 論文名稱: |
最高價、最低價、開盤價及收盤價之買賣價差估計模型探討 Bid-ask spread estimator by daily high, low, open and close prices |
| 指導教授: |
黃泓人
Hong-jen Huang |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 財務金融學系 Department of Finance |
| 論文出版年: | 2014 |
| 畢業學年度: | 102 |
| 語文別: | 中文 |
| 論文頁數: | 74 |
| 中文關鍵詞: | 買賣價差估計 、波動度估計 、日內買賣價差U 型 、隔夜報酬 、最小報價單位 |
| 外文關鍵詞: | Bid-ask spread estimator, Range-based volatility, Intraday U shape, Overnight return, Tick size |
| 相關次數: | 點閱:9 下載:0 |
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Corwin and Schultz (2012)的高低價格比模型(High low spread estimator)是藉由Parkinson(1980)使用一日最高和最低價格的變幅波動度模型(Range-based volatility),再以真實價值、成交價格及買賣價差百分比之間的關係,以一日的買賣價差百分比。本研究模型沿用Corwin and Schultz (2012)的方法藉由Garman and Klass (1980) ,利用一日開盤價、收盤價、最高價及最低價,估計一日波動度的最佳尺度不變估計模型(Best scale invariant estimator)為基礎,使用真實價值、成交價格及買價差關係,並且透過日內買賣價差特性去推估一日買賣價差,來探討能否加以改善高低價格比模型(High low spread estimator)。先前實證研究結果發現股票在委託單驅動市場下,日內買賣價差在開盤及收盤期間會大於盤中,本研究在模型中加入了調整項,使其能應用於不同股票的日內買賣價差特性。此外本研究使用模擬的方式以及實證方法驗證,本研究模型相較於其他者是否能更準確的估計買賣價差百分比。模擬結果顯示當買賣價差百分比在3%以上時,本研究模型使用個別參數只取實數做調整,比起Corwin and Schultz (2012)的高低比估計模型存在更佳的準確性。實證結果顯示本研究模型調整開盤收盤對盤中買賣價差比率,使用個別參數所估計出的買賣價差百分比相較於高低價格比模型買賣價差百分比估計,更接近該股的有效買賣價差。
This study refers to Corwin and Schultz (2012) they develop a bid-ask spread estimator from daily high and low spread. Base on the Corwin and Schultz’s estimator model, a new estimator is built up by including three new variables, open price, close price and an adjustment variable. Adding in open and close price reduces the biased estimation due to ignorance of overnight Return. The adjustment variable takes the role of enhancing the flexibility of fitting in different intraday patterns in bid-ask spread. This study test the estimators by simulation and by seven major stocks in Taiwan. The findings are listed as below. This model performs higher accuracy compare to previous model especially when the percentage of bidask spread is over 3%. The accuracy of current model is highly improved by
considering the adjustment variable dealing with different intraday patterns.
參考文獻
[1] Roll, Richard. “A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficiency Market.” Journal of Finance, Vol 39, pp. 1127–1139, 1984.
[2] Goyenko, Ruslan Y., Craig W. Holden, and Charles A.Trzcinka. “Do Liquidity Measures Measure Liquidity?” Journal of Financial Economics, Vol 92, pp. 153–181, 2009.
[3] Corwin, Shane A., and Paul Schultz. “A Simple Way to Estimate Bid Ask Spread.”The Journal of Finance, Vol 67, pp. 719–760, 2012.
[4] French, Kenneth, and Richard Roll. “Stock Return Variances: The Arrival of Information and the Reaction of Traders.”Journal of Financial Economics, Vol 17, pp. 5–26, 1986.
[5] Parkinson, Michael.“The Extreme Value Method for Estimating the Variance of the Rate of Return.” Journal of Business, Vol 53, pp. 61–65, 1980.
[6] Garman, Mark B., and Michael J. Klass. “On the Estimation of Price Volatility from Historical Data,”Journal of Business, Vol 53, pp. 67-78. 1980.
[7] Chung, Kee H., Bonnie Van Ness, and Robert A Van Ness. “Limit 49 Orders and the Bid-Ask Spread.”Journal of Financial Economic, Vol 53, pp. 255–287, 1999.
[8] Ke, Mei-Chun, Ching-Hai Jiang, and Yen-Sheng Huang.“The Impact of Tick Size on Intraday Stock Price Behavior: Evidence from the Taiwan Stock Exchange” Pacific-Basin Finance Journal, Vol 12, pp. 19–39, 2004.
[9] Lesmond, David, Joseph Ogden, and Charles Trzcinka.“A New Estimate of Transaction Costs.”Review of Financial Studies, Vol 12, pp. 1113–1141, 1999.
[10] Amihud, Yakov. “Illiquidity and Stock Returns: Cross-Section and Time-Series Effects.” Journal of Financial Markets, Vol 5, pp. 31–56, 2002.
[11]Chung, Kee H., and Hao Zhang. “A Simple Approximation of Intraday Spreads Using Daily Data.”Journal of Financial Markets, vol 17, pp.94-120, 2013.