13 citations · 17 across the 5 of their papers we have counts for
5 papers
The New Quant: A Survey of Large Language Models in Financial Prediction and Trading
Weilong Fu
Large language models are reshaping quantitative investing by turning unstructured financial information into evidence-grounded signals and executable decisions. This survey synthe…
Solving barrier options under stochastic volatility using deep learning
Weilong Fu, Ali Hirsa
We develop an unsupervised deep learning method to solve the barrier options under the Bergomi model. The neural networks serve as the approximate option surfaces and are trained t…
Simulating financial time series using attention
Weilong Fu, Ali Hirsa, Jörg Osterrieder
Financial time series simulation is a central topic since it extends the limited real data for training and evaluation of trading strategies. It is also challenging because of the…
An unsupervised deep learning approach in solving partial integro-differential equations
Ali Hirsa, Weilong Fu
We investigate solving partial integro-differential equations (PIDEs) using unsupervised deep learning in this paper. To price options, assuming underlying processes follow Levy pr…
A fast method for pricing American options under the variance gamma model
Weilong Fu, Ali Hirsa
We investigate methods for pricing American options under the variance gamma model. The variance gamma process is a pure jump process which is constructed by replacing the calendar…