Assessing the relationship between closing prices and trading volume in the US livestock futures markets

2020 ◽  
Vol 37 (3) ◽  
pp. 413-428
Author(s):  
Dimitrios Panagiotou ◽  
Alkistis Tseriki
Keyword(s):  
Trading Volume ◽  
Futures Markets ◽  
Quantile Regressions ◽  
Content Type ◽  
Feeder Cattle ◽  
Daily Data ◽  
The Us ◽  
Volume Relationship ◽  
Agricultural Futures ◽  
The Relationship

Purpose 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. Design/methodology/approach The parametric quantile regressions methodology is used. Daily data between January 1, 2010 and July 31, 2019 were used. Findings 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). Originality/value This is the first study that uses the parametric quantile regressions method in the livestock futures market, to examine the returns-volume dependence.

Volatility, trading volume and open interest in futures markets

2016 ◽  
Vol 12 (5) ◽  
pp. 629-653 ◽  
Author(s):  
Christos Floros ◽  
Enrique Salvador
Keyword(s):  
Interest Rates ◽  
Trading Volume ◽  
Futures Markets ◽  
Empirical Relation ◽  
Impulse Response Functions ◽  
Open Interest ◽  
Content Type ◽  
Daily Data ◽  
Relevant Role ◽  
Stage Estimation

Purpose The purpose of this paper is to examine the effect of trading volume and open interest on volatility of futures markets. The authors capture the size and change in speculative behaviour in futures markets by examining the role of liquidity variables (trading volume and open interest) in the behaviour of futures prices. Design/methodology/approach The sample includes daily data covering the period 1996-2014 from 36 international futures markets (including currencies, commodities, stock indices, interest rates and bonds). The authors employ a two-stage estimation methodology: first, the authors employ a E-GARCH model and consider the asymmetric response of volatility to shocks of different sign. Further, the authors consider a regression framework to examine the contemporaneous relationships between volatility, trading volume and open interest. To quantify the percentage of volatility that is caused by liquidity variables, the authors also regress the estimated volatilities on the measures of open interest and trading volume. Findings The authors find that: market depth has an effect on the volatility of futures markets but the direction of this effect depends on the type of contract, and there is evidence of a positive contemporaneous relationship between trading volume and futures volatility for all futures contracts. Impulse-response functions also show that trading volume has a more relevant role in explaining market volatility than open interest. Practical implications These results are recommended to financial managers and analysts dealing with futures markets. Originality/value To the best of the authors’ knowledge, no study has yet considered a complete database of futures markets to investigate the empirical relation between price changes (volatility), trading volume and open interest in futures markets.

Monotonicity, linearity and symmetry in the price volatility–volume relationship

2020 ◽  
Vol 37 (1) ◽  
pp. 110-133 ◽  
Author(s):  
Panos Fousekis ◽  
Dimitra Tzaferi
Keyword(s):  
Trading Volume ◽  
Futures Markets ◽  
Statistical Tests ◽  
Price Volatility ◽  
Local Linear Regression ◽  
Linear Regression Models ◽  
Content Type ◽  
Nonparametric Approach ◽  
Volume Relationship ◽  
The Usa

Purpose This paper aims to investigate the contemporaneous link between price volatility and trading volume in the futures markets of energy. Design/methodology/approach Non-parametric (local linear) regression models and formal statistical tests are used to assess monotonicity, linearity and symmetry. The data are daily price and volumes from five futures markets (West Texas Intermediate, Brent, gasoline, heating oil and natural gas) in the USA. Findings Trading volume and price volatility have, in all markets, a strong nonlinear relation to each other. There are violations of monotonicity locally but not globally. The qualitative nature of the price shocks may have implications for the trading activity locally. Originality/value To the authors’ best knowledge, this is the first manuscript that investigates simultaneously and formally all the three important issues (i.e. monotonicity, linearity and asymmetry) for the price volatility–volume relationship using a highly flexible nonparametric approach.

scholarly journals The Price-Trading Volume Relationship in the Brazilian Stock Market, the Impact of Stock Lending and a Role for Technical Analysis

2015 ◽  
Vol 13 (4) ◽  
pp. 631
Author(s):  
Antonio Zoratto Sanvicente ◽  
Antonio Zoratto Sanvicente ◽  
Antonio Zoratto Sanvicente
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Price Change ◽  
Absolute Value ◽  
Daily Data ◽  
Volume Relationship ◽  
Current Price ◽  
The Impact ◽  
The Relationship ◽  
Positive Covariance

We examine the relationship between price and volume in the Brazilian stock market. It tests the “V-shaped relationship” developed by Karpoff (1987), identified in several empirical papers for the U.S. market. This is expressed by positive covariance between a stock’s market turnover and the absolute value of that stock’s price change in the same period. This would contradict the implication from weak market efficiency that current price would impound all information. We analyze daily data for 47 stocks covering the period from January 04, 2010 to June 28, 2013. The results indicate that the V-shaped relationship is significant.

Exploring the inflationary effect of oil price in the US

2019 ◽  
Vol 13 (1) ◽  
pp. 60-76 ◽  
Author(s):  
Amine Lahiani
Keyword(s):  
Growth Rate ◽  
Structural Breaks ◽  
Oil Prices ◽  
Oil Price ◽  
Inflation Expectations ◽  
Oil Price Shocks ◽  
Price Shocks ◽  
Content Type ◽  
The Us ◽  
The Relationship

PurposeThe purpose of this paper is to explore the effect of oil price shocks on the US Consumer Price Index over the monthly period from 1876:01 to 2014:04.Design/methodology/approachThe author uses the Bai and Perron (2003) structural break test to split the data sample into sub-periods delimited by the computed break dates. Afterwards, the author uses the quantile treatment effects over the full sample and then, by including sub-periods dummies to accommodate the selected structural breaks that drive the relationship between inflation and oil price growth.FindingsThe findings include a decreased transmission effect of oil price changes on inflation in recent years; a varied elasticity of inflation to the growth rate of oil prices across the distribution; and, finally, evidence of asymmetry in the relationship between the growth rate of oil prices and inflation, with a higher transmission mechanism for decreasing rather than increasing oil prices.Practical implicationsPolicymakers should remain alert to monitoring potential inflation increases and should take precautionary measures to anchor inflation expectations, because inflation reacts differently to positive and negative oil price shocks. Moreover, authorities should consider the asymmetric reaction of inflation to oil price shocks to adopt an appropriate monetary policy strategy to achieve the price stability target.Originality/valueThe paper used a quantile regression model with structural breaks, which has not yet been used in the literature.

scholarly journals Study of efficiency and information transmission for agricultural futures markets: a comparative analysis between Buenos Aires and Chicago using monthly and daily data

2017 ◽  
Vol 34 (69) ◽  
pp. 3-23
Author(s):  
Jeremías Lachman ◽  
Pablo Jack
Keyword(s):  
Comparative Analysis ◽  
Information Transmission ◽  
Market Efficiency ◽  
Futures Markets ◽  
Buenos Aires ◽  
Relevant Information ◽  
Futures Market ◽  
Daily Data ◽  
Agricultural Futures ◽  
The One

This paper aims to study and compare the efficiency in futures markets for soybean crop between Buenos Aires (MATBA) and Chicago (CME–CBOT) for the years 1994 through 2015. There are numerous studies that analyze this phenomenon independently, but few of them have done a comparative analysis between marke- ts. Therefore, the main objective of this research — in addition to individually analyzing the efficiency in futures market in each country — is to be able to detect the existence of a relationship between the two markets. In this article we show that, in addition for market efficiency in all cases, market efficiency in MatBa was derived from the efficiency in CME–CBOT. This means that relevant information is transmitted from the Chicago market to the one in Buenos Aires. By using a cointegration approach based on Johansen (1995) we estimated the models with monthly and daily data.

Investors overconfidence behaviour at Bombay Stock Exchange

2018 ◽  
Vol 14 (5) ◽  
pp. 613-632 ◽  
Author(s):  
Venkata Narasimha Chary Mushinada ◽  
Venkata Subrahmanya Sarma Veluri
Keyword(s):  
Private Information ◽  
Trading Volume ◽  
Negative Impact ◽  
Stock Exchange ◽  
Public Information ◽  
Response Analysis ◽  
Content Type ◽  
Daily Data ◽  
Level Data ◽  
Attribution Bias

PurposeThe purpose of the paper is to empirically test the overconfidence hypothesis at Bombay Stock Exchange (BSE).Design/methodology/approachThe study applies bivariate vector autoregression to perform the impulse-response analysis and EGARCH models to understand whether there is self-attribution bias and overconfidence behavior among the investors.FindingsThe study shows the empirical evidence in support of overconfidence hypothesis. The results show that the overconfident investors overreact to private information and underreact to the public information. Based on EGARCH specifications, it is observed that self-attribution bias, conditioned by right forecasts, increases investors’ overconfidence and the trading volume. Finally, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a contribution to the observed excessive volatility.Research limitations/implicationsThe study focused on self-attribution and overconfidence biases using monthly data. Further studies can be encouraged to test the proposed hypotheses on daily data and also other behavioral biases.Practical implicationsInsights from the study suggest that the investors should perform a post-analysis of each investment so that they become aware of past behavioral mistakes and stop continuing the same. This might help investors to minimize the negative impact of self-attribution and overconfidence on their expected utility.Originality/valueTo the best of the authors’ knowledge, this is the first study to examine the investors’ overconfidence behavior at market-level data in BSE, India.

The effect of engagement partner workload on audit quality

2021 ◽  
Vol 36 (8) ◽  
pp. 1068-1091
Author(s):  
Yun Cheng ◽  
Christine M. Haynes ◽  
Michael D. Yu
Keyword(s):  
Audit Quality ◽  
Firm Level ◽  
Content Type ◽  
Big 4 ◽  
The Us ◽  
Performance Benchmarks ◽  
Partner Characteristics ◽  
Partner Firm ◽  
The Individual ◽  
The Relationship

Purpose Auditing studies have shifted the research focus from the audit firm level to the individual audit partner level in recent years. Motivated by the call from Lennox and Wu (2018) to explore the effect of audit partners’ characteristics on audit quality in the US, this study aims to develop a new measure of engagement partner workload (EPW), which includes both the size and number of clients audited to test the effect of EPW on audit quality. This study also examines the moderating effect of the partner firm size on audit quality. Design/methodology/approach To test the effect of the EPW on audit quality, this study runs multivariate regressions of EPW on each specific client’s discretionary accruals and audit report delays. This study also runs a logistic regression of EPW on clients’ probability of having small profit increases to meet performance benchmarks. Findings Results of the hypotheses show that partner workload is positively related to audit quality. The results indicate that partners with larger, but fewer, clients conduct higher quality audits. Further analysis indicates that the relationship between partner workload and audit quality only holds for partners from the non-Big 4 firms. Originality/value This study contributes to the literatures of both audit quality and audit partner characteristics, and the results complement initial research aimed at identifying US partner-related characteristics that influence audit quality.

Returns and volume

2020 ◽  
Vol 37 (3) ◽  
pp. 457-473
Author(s):  
Panos Fousekis
Keyword(s):  
Trading Volume ◽  
Time Series Data ◽  
Price Volatility ◽  
Statistical Testing ◽  
Model Specification ◽  
Series Data ◽  
Causal Order ◽  
Content Type ◽  
Daily Data ◽  
The Usa

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

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