Internet Search and Market Efficiency

• Main Authors: LIN, FANG-CHUN, 林芳群
• Other Authors: WANG, MING-CHUN
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/rt34ng

碩士 === 國立高雄第一科技大學 === 金融系碩士班 === 105 === This study demonstrates the impact on price discovery between stock futures and spots, resulting from internet searching. I first utilize the vector auto-regression model and the vector error correlation model to explore price discovery between stock futures and spots. In my experiment, from September 1, 2010 to December 31, 2015, I focus on the thirty stock futures and spots with the highest daily trading values and the lead-lag relationship between spot and futures prices. I even add the Google search volume index, with dummy variables, D1, D2, and D3, denoting high to low search volume, to my model that explore the effect on spot and futures price. The empirical result shows that spot prices always leads futures prices whether adding dummy variable D3 or not. Then, after adding dummy variables, D1 and D2 (high search volume), the rate of price discovery is dramatically reduced to 50%. Since this is due to outlier within high search volume index, I may say that the search volume has little influence on market price. Furthermore, I conclude that search volume has low correlation with market efficiency.