47 citations · 97 across the 11 of their papers we have counts for
11 papers
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…
Optimal performance of a tontine overlay subject to withdrawal constraints
Peter A. Forsyth, Kenneth R. Vetzal, G. Westmacott
We consider the holder of an individual tontine retirement account, with maximum and minimum withdrawal amounts (per year) specified. The tontine account holder initiates the accou…
Optimal control of the decumulation of a retirement portfolio with variable spending and dynamic asset allocation
Peter A. Forsyth, Kenneth R. Vetzal, Graham Westmacott
We extend the Annually Recalculated Virtual Annuity (ARVA) spending rule for retirement savings decumulation to include a cap and a floor on withdrawals. With a minimum withdrawal…
A Stochastic Control Approach to Defined Contribution Plan Decumulation: "The Nastiest, Hardest Problem in Finance"
Peter A. Forsyth
We pose the decumulation strategy for a Defined Contribution (DC) pension plan as a problem in optimal stochastic control. The controls are the withdrawal amounts and the asset all…
Optimal Asset Allocation For Outperforming A Stochastic Benchmark Target
Chendi Ni, Yuying Li, Peter Forsyth +1
We propose a data-driven Neural Network (NN) optimization framework to determine the optimal multi-period dynamic asset allocation strategy for outperforming a general stochastic t…
Are target date funds dinosaurs? Failure to adapt can lead to extinction
Peter A. Forsyth, Yuying Li, Kenneth R. Vetzal
Investors in Target Date Funds are automatically switched from high risk to low risk assets as their retirements approach. Such funds have become very popular, but our analysis bri…
Weakly chained matrices, policy iteration, and impulse control
Parsiad Azimzadeh, Peter A. Forsyth
This work is motivated by numerical solutions to Hamilton-Jacobi-Bellman quasi-variational inequalities (HJBQVIs) associated with combined stochastic and impulse control problems.…
Piecewise Constant Policy Approximations to Hamilton-Jacobi-Bellman Equations
Christoph Reisinger, Peter Forsyth
An advantageous feature of piecewise constant policy timestepping for Hamilton-Jacobi-Bellman (HJB) equations is that different linear approximation schemes, and indeed different m…
The existence of optimal bang-bang controls for GMxB contracts
Parsiad Azimzadeh, Peter A. Forsyth
A large collection of financial contracts offering guaranteed minimum benefits are often posed as control problems, in which at any point in the solution domain, a control is able…