财务与金融系学术讲座系列2023年第2讲

来源：财务与金融系

主题：Forecasting and Managing Correlation Risks

主讲人：Sophia Zhengzi Li（罗格斯商学院金融系助理教授）

协调人：李晨煦、竺圣波

时间：2023年3月3日（周五）上午 10:00-11:30

地点：线上会议室

语言：中英文

讲座摘要：

We propose a novel and easy-to-implement framework for forecasting correlation risks based on a large set of salient realized correlation features and the sparsity-encouraging LASSO technique. Considering the universe of S&P 500 stocks, we find that the new approach manifests in statistically superior out-of-sample forecasts compared to commonly used procedures. We further demonstrate how the forecasts translate into significant economic gains in the form of higher pairs trading profits, better equity premium predictions, more accurate portfolio risk targeting, and superior overall risk control and minimization.

主讲人简介：

Sophia Zhengzi Li is an assistant professor of finance at Rutgers Business School. She previously taught at Michigan State University from 2013 to 2017. Her main research areas are empirical asset pricing, financial econometrics, big data, and machine learning, and her research interests include volatility, intraday analysis, return prediction, tail risk, news, disagreement, and shareholder voting. She received the First Prize of 2012 Morgan Stanley Prize for Excellence in Financial Markets and the Best Paper Award at the Triple Crown Conference. Her work has been published in leading academic journals, including the Review of Financial Studies, Journal of Financial Economics, Journal of Finance and Quantitative Analysis, and Journal of Econometrics. Her work has been presented at NBER Summer Institute, NBER-NSF Time Series Conference, American Finance Association, European Finance Association, and SFS Cavalcade North America.

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