Research

Working Papers

Carbon emission and asset prices: new evidence from machine learning (with Feng Li)

We predict the carbon emissions of US-listed firms with XGBoost and find a reversed carbon premium after 2016. (This is my second-year summer paper.)

Clustered by images: Convolutional neural networks, investor heterogeneity, and Chinese stock market predictability (《图以类聚：卷积神经网络，投资者异质性与中国股市可预测性》 in Chinese, with Yuqiao Fang and Feng Li)

We propose a simple but effective method to improve the predictability power of CNN in the Chinese Stock market.

How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs (with Shumiao Ouyang and Hayong yun)

Large language models do exhibit consistent risk preferences and ethical fine-tuning has unintended consequences on their risk preferences.

Work in Progress

Multimodal deep learning and asset prices (with Yuqiao Fang)

We use a transformer-based architecture that combines images and text data (as well as numerical data) to predict stock returns.