COVID-19 Forecasts via Stock Market Indicators

TL;DR

This paper introduces a novel approach using stock market technical indicators applied to COVID-19 data, enabling short-term forecasts of pandemic waves and assessing policy impacts with statistical significance.

Contribution

It reinterprets COVID-19 cases as stock market candlesticks and applies technical indicators like MACD and RSI for pandemic prediction, a novel cross-domain methodology.

Findings

Technical indicators significantly predict COVID-19 case trends.

Candlestick analysis helps identify pandemic wave onsets.

Method assesses impact of health policies on case growth.

Abstract

Reliable short term forecasting can provide potentially lifesaving insights into logistical planning, and in particular, into the optimal allocation of resources such as hospital staff and equipment. By reinterpreting COVID-19 daily cases in terms of candlesticks, we are able to apply some of the most popular stock market technical indicators to obtain predictive power over the course of the pandemics. By providing a quantitative assessment of MACD, RSI, and candlestick analyses, we show their statistical significance in making predictions for both stock market data and WHO COVID-19 data. In particular, we show the utility of this novel approach by considering the identification of the beginnings of subsequent waves of the pandemic. Finally, our new methods are used to assess whether current health policies are impacting the growth in new COVID-19 cases.