Machine Learning in Asset Management

65 Pages Posted: 18 Jul 2019 Last revised: 26 Mar 2020

Date Written: July 16, 2019

Abstract

This paper investigates various machine learning trading and portfolio optimisation models and techniques. The notebooks to this paper are Python based. By last count there are about 15 distinct trading varieties and around 100 trading strategies. Code and data are made available where appropriate. The hope is that this informal paper will organically grow with future developments in machine learning and data processing techniques. Changes can be tracked on the GitHub repository.

Keywords: asset management, portfolio, machine learning, trading strategies

JEL Classification: G11, G10, C15, C11, C22, C61, C63, C53, C52

Suggested Citation

Snow, Derek, Machine Learning in Asset Management (July 16, 2019). Available at SSRN: https://ssrn.com/abstract=3420952 or http://dx.doi.org/10.2139/ssrn.3420952

Derek Snow (Contact Author)

FirmAI, NYU FRE ( email )

NYC, Cambridge, Auckland

HOME PAGE: http://www.firmai.org

UoA ( email )

Auckland
New Zealand

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