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主讲人 |
Oliver Linton |
简介 |
<p>We introduce a new class of semiparametric dynamic autoregressive models for the Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a GMM estimator based on conditional moment restrictions and an efficient semiparametric ML estimator based on an i.i.d. assumption. We derive large sample properties for our estimators. We further develop a methodology to detect the occurrence of permanent and transitory breaks in the illiquidity process. Finally, we demonstrate the model performance and its empirical relevance on two applications. First, we study the impact of stock splits on the illiquidity dynamics of the five largest US technology company stocks. Second, we investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index.</p> |
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主讲人简介 |
<p class="MsoNormal">Oliver Linton is a Professor of Political Economy and Econometrics at Cambridge University and a Fellow of Trinity College. He has served as an Associate Editor with Econometrica, a co-editor at Journal of Econometrics, Econometric Theory, and Econometrics Journal. Linton is a Fellow of the British Academy, a Fellow of the Econometric Society, and a Fellow of the Institute of Mathematical Statistics. His research contribution has mostly been to do with nonparametric and semiparametric methods. He is also interested in Financial Econometrics. He is now the president of the Society for Financial Econometrics.</p> |
期数 |
厦门大学群贤学科学术讲座 |
