報告題目：Empirical asset pricing via the conditional quantile variational autoencoder
報 告 人：朱柯 副教授
所在單位：香港大學
報告時間：2022年7月8日 星期五 14:00-15:00
報告地點：騰訊會議 ID：345-417-089， 會議密碼：0708
校内聯系人：朱複康 fzhu@jlu.edu.cn
報告摘要：We propose a new asset pricing model that is applicable to the big panel of return data. Our model aims to explain the conditional mean of the return from the conditional distribution of the return, which is approximated by a step distribution function constructed from conditional quantiles of the return. To study conditional quantiles of the return, we propose a new conditional quantile variational autoencoder (CQVAE) network. The CQVAE network specifies a factor structure for conditional quantiles with latent factors learned from a VAE network and nonlinear factor loadings learned from a "multi-head" network. Under the CQVAE network, we allow the observed covariates such as asset characteristics to guide the structure of latent factors and factor loadings. Furthermore, we provide a two-step estimation procedure for the CQVAE network. Finally, we apply our CQVAE asset pricing model to analyze a 60-year US equity return data set. Compared with the benchmark conditional autoencoder model, the CQVAE model not only delivers much larger values of out-of-sample total and predictive R^2s, but also earns at least 30.9% higher values of Sharpe ratios for both long-short and long-only portfolios.
報告人簡介： 朱柯博士2011年獲得香港科技大學統計學博士學位，同年進入中國科學院數學與系統科學研究院從事研究工作，曆任助理研究員、副研究員。2016年加入香港大學任助理教授、副教授。朱柯博士的研究興趣包括統計建模、金融時間序列分析、計量經濟、金融大數據、因果推斷等領域。朱柯博士2015年獲得中國科學院數學與系統科學研究院的 “陳景潤未來之星獎”，他的一系列論文發表在國際統計學和計量經濟學頂級雜志 Annals of Statistics, Journal of the Royal Statistical Society (Series B), Journal of American Statistics Association, Journal of Econometrics 和 Journal of Business & Economic Statistics。
