台灣股票市場當沖因素之探討

Discussion on Factor of Day Trading for Taiwan Stock Markets

張仕琦(Shih-Chi Chang)

指導教授 ： 段昌文

淡江大學/商管學院/財務金融學系碩士班/碩士(2021年)

https://doi.org/10.6846/TKU.2021.00411

摘要

本研究主要依據Chung, Choe and Kho (2009) 的研究方法，分別採用VAR模型及縱橫分析，來探討在台灣當日沖銷對投資者是否有影響，採用台灣證券交易所上市、上櫃的股市資料作為研究樣本，研究期間為2017年4月28日至2020年12月31日之日資料，目的在觀察當沖客是否會影響股票市場上波動加劇。
實證結果發現，現股當沖報酬率不管在疫情前後，大多呈現負的報酬率。透過VAR模型得出當沖大盤會造成波動性與流動性 有顯著負相關，說明波動率高低會影響流動性。疫情前的當沖比率與delay值呈負相關，疫情後成正相關，代表在疫情前的當沖投資人的隱藏資訊會比疫情之後來的多，且當沖投資人偏好股價淨值比、成交值高的熱門股以及高風險高波動性的個股。

關鍵字

當日沖銷 ； 現股報酬 ； 向量自回歸 ； 縱橫分析 ； 波動率 ； 流動性

並列摘要

Based on the research method of Chung, Choe and Kho (2009), this study uses VAR model and vertical and horizontal analysis to explore whether the day-trading in Taiwan has an impact on investors. The data of listed and OTC stock markets in Taiwan stock exchange is used as the research sample, and the research period is from April 28, 2017 to December 31, 2020. The purpose of this paper is to observe whether the impact of the impulse customers on the stock market volatility.
The empirical results show that the current stock when the rate of return regardless of before and after the epidemic, most of the negative rate of return. Through the VAR model, it is concluded that when the market is attacked, there will be a significant negative correlation between volatility and liquidity, indicating that volatility will affect liquidity. There is a negative correlation between the day trade ratio before the epidemic and the delay value, and a positive correlation after the epidemic, which means that the investors before the epidemic will have more hidden information than after the epidemic, and they prefer the stocks with high price-book ratio, high transaction value and high risk and high volatility.

並列關鍵字

Day-Trading ； Stock Return ； VAR ； Vertical and horizontal analysis ； Volatility ； Liquidity

參考文獻

一、中文文獻

徐子舜（2015），「現股當沖新制對市場及個股報酬率、週轉率與成交量影響效果之研究」國立臺北大學國際財務金融碩士在職專班碩士論文。

二、英文文獻

1. Alizadeh S., Brandt M.W., Diebold F.X. (2002), “Range-based estimation of stochastic volatility models.” Journal of Financial 57, 1047–1091.

2. Amilhud, Yakov, and Haim Mendelson (1987), “Trading mechanisms and stock returns : An empirical investigation” Journal of Finance, Vol. 42, 533-553.