Duality in optimal consumption--investment problems with alternative data

TL;DR

This paper develops a duality theory for optimal consumption-investment problems incorporating alternative data sources like social media and GPS, providing explicit strategies under certain distribution conditions.

Contribution

It introduces a novel duality framework for models with alternative data and jump-diffusion processes, enabling explicit solutions for consumption-investment strategies.

Findings

Established conditions for unique smooth solutions with alternative data

Derived explicit consumption-investment strategies using duality theory

Extended classical models to include non-standard data sources

Abstract

This study investigates an optimal consumption--investment problem in which the unobserved stock trend is modulated by a hidden Markov chain that represents different economic regimes. In the classical approach, the hidden state is estimated from historical asset prices, but recent advancements in technology enable investors to consider alternative data in their decision-making. These include social media commentary, expert opinions, COVID-19 pandemic data, and GPS data, which originate outside of the standard sources of market data but are considered useful for predicting stock trends. We develop a novel duality theory for this problem and consider a jump-diffusion process for the alternative data series. This theory helps investors in identifying ``useful'' alternative data for dynamic decision-making by offering conditions to the filter equation that permit the use of a control approach based on the dynamic programming principle. We demonstrate an application for proving a unique smooth solution for a constant relative risk-averse agent once the distributions of the signals generated from alternative data satisfy a bounded likelihood ratio condition. In doing so, we obtain an explicit consumption--investment strategy that takes advantage of different types of alternative data that have not been addressed in the literature.