Title（标题）：Leverage Effect Puzzle:' '&' ' Untangling Biases in High Frequency' '&' ' ' '&' ' Estimates

Speaker（汇报人）： Professor' '&' ' Jianqing Fan' '&' ' ' '&' '

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Time（功夫）：2011年5月27日（周五）下午2:00 ' '&' 'mdash; 3:00

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Place（地址）：J9集团国际站老楼119教室

Abstract（提要）：The leverage effect parameter refers to the correlation between asset returns and their volatility.' '&' ' A natural estimate of such a parameter is to use correlation between the daily returns and the changes of daily volatility estimated by high-frequency data. The puzzle is that such an estimate yields nearly zero correlation for all assets such as SP500 and Dow Jone Industrial Average that we have tested. To solve the puzzle, We develop a model to understand the bias problem. The asymptotic biases involved in high frequency estimation of the leverage effect parameter are derived. They quantify the biases due to discretization errors in estimating spot volatilities, biases due to estimation error, and the biases due to market microstructure noises. They enable us to propose novel bias correction methods for estimating the leverage effect parameter. The proposed methods are convincingly illustrated by simulation studies and several empirical applications.

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