Peter Forsyth

Peter Forsyth

University of Waterloo

H-index: 59

North America-Canada

About Peter Forsyth

Peter Forsyth, With an exceptional h-index of 59 and a recent h-index of 29 (since 2020), a distinguished researcher at University of Waterloo, specializes in the field of Scientific Computing, Computational Finance, Numerical solution of PDEs.

His recent articles reflect a diverse array of research interests and contributions to the field:

A Buy and Hold Portfolio Loses Diversification

Across-time risk-aware strategies for outperforming a benchmark

Optimal performance of a tontine overlay subject to withdrawal constraints

A parsimonious neural network approach portfolio optimization

Target Date Funds: a bad idea whose time has come

Beating a benchmark: dynamic programming may not be the right numerical approach

Machine Learning and Hamilton-Jacobi-Bellman Equation for Optimal Decumulation: a Comparison Study

Neural Network Approach to Portfolio Optimization with Leverage Constraints: A Case Study on High Inflation Investment

Peter Forsyth Information

University

Position

Distinguished Professor Emeritus of Computer Science

Citations(all)

10987

Citations(since 2020)

2428

Cited By

9617

hIndex(all)

59

hIndex(since 2020)

29

i10Index(all)

146

i10Index(since 2020)

75

Email

University Profile Page

Google Scholar

Peter Forsyth Skills & Research Interests

Scientific Computing

Computational Finance

Numerical solution of PDEs

Top articles of Peter Forsyth

A Buy and Hold Portfolio Loses Diversification

2023/12/12

Across-time risk-aware strategies for outperforming a benchmark

European Journal of Operational Research

2024/3/1

Optimal performance of a tontine overlay subject to withdrawal constraints

ASTIN Bulletin: The Journal of the IAA

2024/1

A parsimonious neural network approach portfolio optimization

2023/12/6

Target Date Funds: a bad idea whose time has come

2023/12/2

Beating a benchmark: dynamic programming may not be the right numerical approach

SIAM Journal on Financial Mathematics

2023/6/30

Machine Learning and Hamilton-Jacobi-Bellman Equation for Optimal Decumulation: a Comparison Study

arXiv preprint arXiv:2306.10582

2023/6/18

Neural Network Approach to Portfolio Optimization with Leverage Constraints: A Case Study on High Inflation Investment

arXiv preprint arXiv:2304.05297

2023/5/26

Yuying Li
Yuying Li

H-Index: 1

Peter Forsyth
Peter Forsyth

H-Index: 30

Beating a constant weight benchmark: easier done than said

International Journal of Theoretical and Applied Finance (IJTAF)

2023/5/21

Optimal Asset Allocation in a High Inflation Regime: a Leverage-feasible Neural Network Approach

arXiv preprint arXiv:2304.05297

2023/4/11

A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming

arXiv preprint arXiv:2303.08968

2023/3/15

What’s LDI got to do with it?

2023/1/18

Multi-Period Mean Expected-Shortfall Strategies:‘Cut Your Losses and Ride Your Gains’

Applied Mathematical Finance

2022/9/3

Optimal asset allocation for outperforming a stochastic benchmark target

Quantitative Finance

2022/9/2

Yuying Li
Yuying Li

H-Index: 1

Peter Forsyth
Peter Forsyth

H-Index: 30

Asset allocation during high inflation periods: A stress test

2022/6/16

Decumulation of Defined Contribution Pension Plans: The Canasta Strategy

2022/4/29

Dynamic optimal investment strategies for benchmark

2022/4/28

Optimal Asset Allocation

2022/4/26

Yuying Li
Yuying Li

H-Index: 1

Peter Forsyth
Peter Forsyth

H-Index: 30

A Stochastic Control Approach to Defined Contribution Plan Decumulation: “The Nastiest, Hardest Problem in Finance”

North American Actuarial Journal

2022/4/3

Equal weight vs capitalization weight indexes

White paper, Cheriton School

2022/3/2

See List of Professors in Peter Forsyth University(University of Waterloo)

Co-Authors

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