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The cross-quantilogram analysis is employed. The latter can assess the temporal association between two stationary time series at different parts of their joint distribution. Data are daily prices and trading volumes from the futures markets of five agricultural commodities, namely, corn, hard red wheat, oats, rice and soybeans.

The objective to the present work is to investigate for directional predictability between returns and volume (and vice versa) in the futures markets of agricultural commodities.

The empirical results reveal evidence, weak as well as strong, that extreme low values of returns are likely to lead high levels of volume. There is also weak evidence that extreme low values of volume are likely to precede high values of returns, except for the futures markets of oats where there is very strong evidence that low values of volume are likely to lead high values of returns. For the commodity of soybeans, there is very strong evidence that extreme high levels of volume are likely to lead high values of returns, but they are very short lived.

Agricultural futures have been recently characterized by increased volatility leading hedgers to be looking for diversification. The present findings suggest that when price crashes occur, investors who suffer losses wish to sell, increasing this way the trading activity. Concurrently, the results reveal that extreme low levels of trading volume might signal a possible price turn around for traders.

This is the first study that employs the quantilogram approach in order to investigate for potential predictability from returns to volume and from volume to returns, in the futures markets of agricultural commodities.

The purpose of this paper is to examine the relationship between closing prices and trading volume in the livestock futures markets of lean hogs, live cattle and feeder cattle.

The parametric quantile regressions methodology is used. Daily data between January 1, 2010 and July 31, 2019 were used.

Findings suggest that the relationship between the two variables is non-linear. Price-volume relationship is positive (negative) under positive (negative) returns. Furthermore, co-movement is weaker at the lower quantiles and stronger at the higher quantiles. Results are in line with the empirical findings of the price-volume relationship in six agricultural futures markets from the study by Fousekis and Tzaferi (2019).

This is the first study that uses the parametric quantile regressions method in the livestock futures market, to examine the returns-volume dependence.