4 citations · 8 across the 9 of their papers we have counts for
3 papers · 1 filter
Machine Learning and Hamilton-Jacobi-Bellman Equation for Optimal Decumulation: a Comparison Study
Marc Chen, Mohammad Shirazi, Peter A. Forsyth +1
We propose a novel data-driven neural network (NN) optimization framework for solving an optimal stochastic control problem under stochastic constraints. Customized activation func…
Neural Network Approach to Portfolio Optimization with Leverage Constraints:a Case Study on High Inflation Investment
Chendi Ni, Yuying Li, Peter A. Forsyth
Motivated by the current global high inflation scenario, we aim to discover a dynamic multi-period allocation strategy to optimally outperform a passive benchmark while adhering to…
A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming
Pieter M. van Staden, Peter A. Forsyth, Yuying Li
We present a parsimonious neural network approach, which does not rely on dynamic programming techniques, to solve dynamic portfolio optimization problems subject to multiple inves…