The historic oil price fluctuation during the Covid-19 pandemic: What are the causes?

This work examines the price-volume relationship in six agricultural futures markets using quantile regressions and daily data from 2010 to 2018. The results suggest that the association between the two variables is highly non-linear (convex). In particular, the association is positive (negative) under positive (negative) returns in line with the theoretical proposition of Blume et al. (1995) for stock markets. The existence of non-linearity explains why earlier empirical studies, that assumed a priori a linear association, ended up with conflicting and often counterintuitive findings.

Price returns and trading volume changes in agricultural futures markets: An empirical analysis with quantile regressions

Uncovering the complex asymmetric relationship between trading activity and commodity futures price: Evidenced from QNARDL study

PurposeThe 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.Design/methodology/approachThe 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.FindingsThe 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.Research limitations/implicationsAgricultural 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.Originality/valueThis 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.

Directional predictability between trading volume and price returns in the agricultural futures markets: risk implications for traders

The relationship between returns and trading volume is central in financial economics because it has both a theoretical interest and important practical implications with regard to the structure of financial markets and the level of speculation activity. The aim of this study is to provide new insights into the association between returns and trading volume by investigating their kernel (instantaneous) causality. The empirical analysis relies on time series data from 22 commodities futures markets (agricultural, energy and metals) in the USA.,Non-parametric (local linear) regressions are applied to daily data on returns and on trading activity; generalized correlation measures are computed and their differences are subjected to formal statistical testing.,The results suggest that raw returns are likely to kernel-cause volume and volume is likely to kernel-cause price volatility. The patterns of causal order are generally in line with what is stipulated by the relevant theory, they provide guidance for model specification and they appear to explain the empirical evidence on temporal (lag-lead) causality between the same pairs of variables obtained in earlier works.,The concept of kernel causality has very recently become a part of the toolkit for econometric/statistical analysis. To the best of the author’s knowledge, this is the first study that relies on the notion of kernel (instantaneous) causality to provide new evidence on a relationship that is of keen interest to investors, professional economists and policymakers.

Returns and volume: Kernel causality in the US futures markets for agricultural, energy and metal commodities

This paper applies a quantile regression model to examine the relationship between the contract prices and trading volumes of light sweet crude oil contracts on the New York Mercantile Exchange (NYMEX) and Brent crude oil contracts on the Intercontinental Exchange (ICE). The results show a tandem rise in prices and volumes for light sweet crude oil contracts but a deviation between prices and volumes for Brent crude oil contracts. These two crude oil contracts exhibit significantly different relationships between prices and volumes when prices fluctuate. This finding can help analysts and investors in their investment decisions.

On the Price–Volume Relationship in Crude Oil Futures Markets

Abstract Residual stress negatively affects the quality of optical products and is a difficult problem to solve. Regulating process parameters is a critical element in quality control. Therefore, the online monitoring of critical process variables is necessary for stabilizing product quality and reducing manufacturing cost. This study proposes a method for the online monitoring of residual stress near the gate of a mold using multiple pressure sensors to measure process variables and verifies the feasibility of online monitoring. The study found that residual stress near the gate could not be accurately measured with only a single sensor because measurements were susceptible to interference with process parameters. When a single sensor was used to measure process variables, correlation coefficients of between 0.48 and 0.59 were obtained, and when multiple sensors were used, correlation coefficients of between 0.80 and 0.92 were obtained, which indicated strong correlation. Therefore, the online monitoring of residual stress near the gate is feasible. This monitoring method can provide a new concept of online monitoring technology for the injection molding of optical products.

https://www.degruyter.com/document/doi/10.1515/polyeng-2022-0113/pdf

Yi-Cheng Chen

Papers

On the Price–Volume Relationship in Crude Oil Futures Markets

Online detection of residual stress near the gate using cavity pressure for injection molding