The Economic Value of Intraday Data in Hedging Commodity Spot Prices

Shujie Wu, Joshua Huang and Teresa Serra

No 379012, 2024 Conference, April 22-23, 2024, St. Louis, Missouri from NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management

Abstract: This article shows how high-frequency market data relates to low frequency events by examining the economic value of using intraday data to hedge commodity spot prices in the futures market. We use the realized minimum-variance hedging ratio (RMVHR) framework, which depends on the realized futures-cash covariance matrix forecast. We focus on the crude oil crack and soybean crush industries and consider both multiple and single-commodity portfolios, as well as different forecast strategies based on intraday data. We use the Naïve hedging ratio as the benchmark to investigate the performance of intraday data-based hedging models. Our results suggest that for each portfolio considered, there is usually one intraday data-based hedging strategy that outperforms the Naïve. Superior performance, however, is not always statistically significant, for the crack industry. Our estimates place the advantage of using intraday data between $7,155.00 and $287.50 per contract and year on average, with these values representing the decline in the portfolio’s standard deviation achieved through hedging. This points at a promising path to improving the performance of hedging in the commodity space based on intraday data.

Keywords: Agricultural and Food Policy; Demand and Price Analysis (search for similar items in EconPapers)
Pages: 57
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ags:nccc24:379012

DOI: 10.22004/ag.econ.379012

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