Papers · 论文
Research in plain language
Two papers from my PhD years, written for readers who do not live inside quantitative finance.
Quantitative Finance
Deep learning for enhanced index tracking
This paper formulates enhanced index tracking as a dynamic rebalancing problem: select large index constituents, then let a structured neural network allocate weights under tracking-error, excess-return, CVaR, and transaction-cost considerations.
The Journal of Derivatives
Which neural network works best for quadratic hedging?
This is a benchmark paper rather than a new hedging trick: it compares Multi-net, Single-net, and RNN architectures for dynamic hedging across high-dimensional and long-horizon settings.