4 citations · 8 across the 7 of their papers we have counts for
5 papers · 1 filter
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…