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Using a proposed quantile-based hedging analysis framework, this paper analyzes the hedging properties and portfolio performance of 15 commodities futures in China, especially under extreme market conditions. Quantile-onquantile regression results show that the dependency structures of most spot and futures prices exhibit an almost similar shape with positive coefficients, which indicates that most futures products are good hedges and safe havens for the corresponding spot prices. Quantile hedge ratios vary with the quantiles, displaying a U-shape, so the hedge ratios of most commodities should increase moderately in both bearish and bullish markets. As for portfolio performance, metal commodities perform best; agricultural commodities second best, and energy commodities relatively poorly. Out-of-sample quantile hedging results are consistent with in-sample results. Therefore, participating in the futures market can effectively manage risk. The premise is that investors pay attention to market dynamics and adjust their portfolios promptly.commodity futures, extreme market, quantile hedging, quantile-on-quantile regression, safe haven | INTRODUCTIONIn recent years, uncertainties such as COVID-19, the Russia-Ukraine war, and African Swine fever have led to dramatic volatility in international commodity prices (Ji et al., 2020;Panagiotou, 2021) and extreme market conditions occur frequently. The price of a barrel of West Texas Intermediate (WTI), the benchmark for US oil, fell as low as −

Contracts that expire in January, May, and September attract the most trading activity for corn futures in China. Contracts that mature in other months are thinly traded, even when they are the closest to maturity. In this paper, we examine and compare the behavior and determinants of the bid-ask spreads (BASs) of active and inactive contracts using the best bid offer data set. We show that both the magnitude and volatility of BAS for inactive contracts exhibit U-shaped patterns, whereas active contracts' BAS increase only near their expiration. Inactive contracts are also of low liquidity risk after introducing market makers. On the basis of the simultaneous equation model, we find that BAS responds negatively to volume and positively to volatility and order imbalance. The impacts are larger in inactive contracts. Moreover, introducing market makers to inactive contracts is conducive to attracting trading and lowering trading costs.