講座題目：Forecasting Option Returns with News

講座時間：2022年12月20日（星期二）上午11:00-12:00

講座方式：騰訊會議ID：958-999-529

密碼：221213

講座鏈接：https://meeting.tencent.com/dm/8lwPM6T9FWSS

主講人：

韓冰, 加拿大多倫多大學(xué)羅特曼管理學(xué)院金融學(xué)教授，多倫多證券交易所資本市場講座教授。韓冰教授的主要研究領(lǐng)域是資產(chǎn)定價，投資，行為金融學(xué)，房地產(chǎn)金融。他的多篇論文發(fā)表在頂級經(jīng)濟，金融和管理學(xué)學(xué)術(shù)雜志上，包括Journal of Finance, Journal of Financial Economics，Review of Financial Studies， Review of Economic Studies，International Economic Review, Journal of Economic Theory，Management Science等。他的研究成果受到《紐約時報》、《華爾街日報》、《華盛頓郵報》、《經(jīng)濟學(xué)人》等媒體的專訪和報導(dǎo)。韓冰教授獲得了眾多國際知名學(xué)術(shù)獎項，包括歐洲金融協(xié)會最佳論文獎，中國金融協(xié)會會議最佳論文獎，美國個人投資者協(xié)會在資產(chǎn)定價研究中獲優(yōu)秀論文獎，上海風(fēng)險論壇最佳論文獎, 中國國際金融與政策論壇杰出論文獎, 全球金融專業(yè)人士協(xié)會終身成就獎。韓冰教授現(xiàn)任Financial Management，Journal of Economic Dynamics and Control，Journal of Empirical Finance，International Review of Finance和Pacific-Basin Finance Journal主編和副主編。

講座簡介：

This paper investigates whether text data contains useful information about the cross-section of expected equity option returns. We apply both lexicon-based and machine learning approaches to extract qualitative signals from over six million news articles. The machine learning methods outperform lexicon-based approaches in predicting delta-hedged option returns and generate sizable profits. Our results are robust after controlling for known option return predictors including volatility-related variables and various underlying stock characteristics. An analysis of the keywords identified by machine learning methods suggests the option return predictability is largely related to firm-specific sentiment and option mispricing. Our work highlights the importance of analyzing unstructured data like texts for pricing derivatives.