Eye in outer space: satellite imageries of container ports can predict world stock returns

Honghai Yu, Xianfeng Hao, Liangyu Wu, Yuqi Zhao and Yudong Wang
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Honghai Yu: Nanjing University
Xianfeng Hao: Nanjing University
Liangyu Wu: Nanjing University
Yuqi Zhao: Tongji University

Palgrave Communications, 2023, vol. 10, issue 1, 1-16

Abstract: Abstract Forecasting stock returns is challenging. Traditional economic data that are available to all investors are published with lags and suffer from the problem of frequent revisions. Consequently, they often fail to forecast stock returns. For this reason, investors are increasingly interested in seeking alternative data. This paper forecasts stock returns using satellite-based information on shipping containers, which can capture economic activity in real-time. The container coverage area in each port is identified from 83,672 satellite images via the U-Net method and used as a proxy for the number of containers. Forecast combination over univariate predictive regression is used to generate return forecasts. The results indicate that the number of containers in ports can significantly predict stock index returns in 27 out of 33 countries at a daily frequency for the 2019–2021 period. An investor making use of satellite data on marine ports can, on average, receive an annualized return of 16.38%. The predictability can be explained by the predictive relationship between port container numbers and economic activity. In future studies, satellite data can be applied to monitor and forecast other economic indicators.

Date: 2023
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DOI: 10.1057/s41599-023-01891-9

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