Optimal Tactical Asset Allocation – Using Recommender Systems in Portfolio Management

17 Pages Posted: 5 Mar 2019

Date Written: Janauray 2019

Abstract

Here we present a novel approach to how the Chief Investment Office (CIO) can select investment strategies to allocate to and to decide the percentage allocation to them. The method that we outline here is a continuation of our previous research on recommender systems science[13]. The aim of this project is to improve upon an objective measure of the CIO’s efficiency. The CIO office is tasked with allocating to the available investment strategies and altering the allocation based on changes in financial markets.

The allocation algorithm outlined here tries to adapt to new market regimes while simultaneously responding to observations of the relative performance of investment strategies. It turns out that a solution to the strategy selection problem faced by CIOs is very similar to the science behind movie or music recommendation.

The algorithm learns from historical observations about strategies. It tries to figure out a relationship between different dates and months in the past, and between strategies to which we are possibly allocating. This process of detecting a two-dimensional neighborhood is what is superior to methods adopted by CIO offices in the past.

Keywords: Portfolio Construction, Tactical Allocation, Recommender Systems, Matrix Factorization, Global Macro Trading

JEL Classification: C00, C10, C50, G00, G11

Suggested Citation

Chakravorty, Gaurav and Awasthi, Ankit and Sirohiya, Anshul and Singhal, Mansi, Optimal Tactical Asset Allocation – Using Recommender Systems in Portfolio Management (Janauray 2019). Available at SSRN: https://ssrn.com/abstract=3334021 or http://dx.doi.org/10.2139/ssrn.3334021

Gaurav Chakravorty (Contact Author)

Qplum ( email )

Harborside 5, 185 Hudson St, Suite 1620
Jersey City, NJ 07311
United States
2013772302 (Phone)

HOME PAGE: http://https://www.qplum.co

Ankit Awasthi

affiliation not provided to SSRN

Anshul Sirohiya

Qplum ( email )

Harborside 5, 185 Hudson St, Suite 1620
Jersey City, NJ 07311
United States

HOME PAGE: http://https://www.qplum.co

Mansi Singhal

Qplum ( email )

Harborside 5, 185 Hudson St, Suite 1620
Jersey City, NJ 07311
United States
2013772302 (Phone)

HOME PAGE: http://www.qplum.co

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