Measuring the cost of liquidity in agricultural futures markets: Conventional and Bayesian approaches
评估了传统和贝叶斯方法在农业期货市场中估计流动性成本的效果，发现贝叶斯绝对值估计器在高噪声和高相关条件下表现精确，对活牛和瘦猪合约数据有实际意义。
Abstract Estimating the cost of liquidity in agricultural futures markets is challenging because bid‐ask spreads are usually not observed. Based on an ability to reflect simulated data from Roll's spread model, we assess the effectiveness of conventional and Bayesian bid‐ask spread estimators under different market conditions. Conventional serial covariance and absolute price change spread estimators appear to be biased. Hasbrouck's Bayesian estimator generates small costs of liquidity whose values depend on the correlation and noise in the data. The absolute value Bayesian estimator is precise and works well under conditions of high levels of noise and correlation usually found in agricultural futures markets. Using data from live cattle (LC) and lean hog (LH) contracts, we find similar patterns of performance that produce economically meaningful cost of liquidity differences.