Embracing advanced AI/ML to help investors achieve success: Vanguard Reinforcement Learning for Financial Goal Planning

10/18/2021
by   Shareefuddin Mohammed, et al.
0

In the world of advice and financial planning, there is seldom one right answer. While traditional algorithms have been successful in solving linear problems, its success often depends on choosing the right features from a dataset, which can be a challenge for nuanced financial planning scenarios. Reinforcement learning is a machine learning approach that can be employed with complex data sets where picking the right features can be nearly impossible. In this paper, we will explore the use of machine learning for financial forecasting, predicting economic indicators, and creating a savings strategy. Vanguard ML algorithm for goals-based financial planning is based on deep reinforcement learning that identifies optimal savings rates across multiple goals and sources of income to help clients achieve financial success. Vanguard learning algorithms are trained to identify market indicators and behaviors too complex to capture with formulas and rules, instead, it works to model the financial success trajectory of investors and their investment outcomes as a Markov decision process. We believe that reinforcement learning can be used to create value for advisors and end-investors, creating efficiency, more personalized plans, and data to enable customized solutions.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 8

page 9

07/09/2019

Deep Reinforcement Learning in Financial Markets

In this paper we explore the usage of deep reinforcement learning algori...
07/08/2018

Financial Trading as a Game: A Deep Reinforcement Learning Approach

An automatic program that generates constant profit from the financial m...
11/23/2019

From Persistent Homology to Reinforcement Learning with Applications for Retail Banking

The retail banking services are one of the pillars of the modern economi...
07/09/2019

Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets

We develop a new topological structure for the construction of a reinfor...
09/30/2020

Bridging the gap between Markowitz planning and deep reinforcement learning

While researchers in the asset management industry have mostly focused o...
05/07/2020

Know Your Clients' behaviours: a cluster analysis of financial transactions

In Canada, financial advisors and dealers by provincial securities commi...
08/05/2021

Responding to Illegal Activities Along the Canadian Coastlines Using Reinforcement Learning

This article elaborates on how machine learning (ML) can leverage the so...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.