scholarly journals Extension's Role in Commodity Marketing Education: Past, Present, and Future

2013 ◽  
Vol 45 (3) ◽  
pp. 537-555
Author(s):  
John M. Riley
Keyword(s):  
Price Volatility ◽  
Commodity Markets ◽  
Market Volatility ◽  
Agricultural Markets ◽  
Agricultural Commodity ◽  
Price Forecast ◽  
Marketing Education ◽  
The Future ◽  
Market Situation

Historically, market situation and outlook has often included some form of price forecast. Recent volatility in agricultural commodity markets is making price forecasts challenging and at times less reliable. In addressing this price volatility, changes in agricultural markets are highlighted along with price forecasts: pre- and postincreased market volatility. Given these recent challenges, the future of Extension agricultural commodity marketing is discussed.

scholarly journals Impact of Weather on Agriculture Commodity Market and the Price Discovery: An Empirical Analysis

2021 ◽  
pp. 60-70
Author(s):  
Suraj E. S ◽  
Ojasvi Gupta
Keyword(s):  
Price Discovery ◽  
Commodity Prices ◽  
Price Volatility ◽  
Future Market ◽  
Contributing Factors ◽  
Agricultural Commodity ◽  
Spot Prices ◽  
The Future ◽  
Demand Fluctuations ◽  
Derivative Market

This paper focused on studying the agricultural commodity prices in India and it's extreme volatility due to many reasons such as government interference, growth, market forces factors, regular floods and droughts, transport and warehousing problems, etc. These are contributing factors to demand fluctuations. In this case, the future market plays an important role in the economy. The demand for commodity futures has three particular economic functions: price discovery, price risk management, and price volatility. The future market plays a key role in the process of price discovery. The main aim of this system is to regulate prices to minimize uncertainty, to provide price signals to market traders for futures spot prices through the price discovery phase. So, this study emphasized the role of the derivative market in reducing the volatility of agricultural commodity prices in the Indian market. Keywords: volatility, future market, derivatives

Forecasting Prices for Industrial Commodity Markets

1970 ◽  
Vol 34 (2) ◽  
pp. 28-32
Author(s):  
Theodore D. Frey
Keyword(s):  
Commodity Markets ◽  
Sale Price ◽  
Price Forecast ◽  
The Future ◽  
Price Trends ◽  
Capital Intensive

An accurate price forecast is crucial when deciding on a new investment proposal for capital intensive commodities. In such industries as metals, plastics, and fertilizers, the sale price is the key profitability factor. New investments are too often based on specious forecasts which use historical price trends to predict the future. Another way to forecast prices which can provide more meaningful results is presented in the article.

scholarly journals Globalization, Cropping Choices, and Profitability in American Agriculture

2001 ◽  
Vol 33 (2) ◽  
pp. 315-326 ◽  
Author(s):  
Steven C. Blank
Keyword(s):  
United States ◽  
Agricultural Production ◽  
The United States ◽  
Commodity Markets ◽  
Agricultural Markets ◽  
Agricultural Commodity ◽  
Technological Advances ◽  
American Agriculture ◽  
Over Time

AbstractThe paper discusses the linkages between the “globalization” of agricultural markets over recent decades and the decisions being made by individual farmers and ranchers in the United States. It is noted that technological advances lead to globalization of agricultural commodity markets and profit pressures. The continuing profit squeeze in agricultural production is having a significant effect on the cropping choices of America's farmers. When possible, acreage is being shifted out of low-revenue-generating crops and into higher-revenue-generating crops. This shift makes crop portfolios more risky over time, thus encouraging farmers to consider diversifying out of agriculture.

scholarly journals Price volatility of Polish agricultural commodities in the view of the Common Agricultural Policy

2018 ◽  
Vol 64 (No. 5) ◽  
pp. 216-226 ◽  
Author(s):  
Piotr Bórawski ◽  
Aneta Belłdycka-Borawska ◽  
James W. Dunn
Keyword(s):  
Agricultural Policy ◽  
Price Volatility ◽  
Global Market ◽  
Agricultural Markets ◽  
Agricultural Commodities ◽  
Long Period ◽  
Market Situation ◽  
High Volatility ◽  
The Common ◽  
The Eu

In the paper, the price volatility was examined. The authors used 650 weekly observations from 2003 to 2015. Such a long period of analysis helped to reveal periods with high volatility. The objective of the paper was to recognize price volatility of agricultural commodities in Poland. The authors chose beef, pork and wheat markets to show the differentiation of price volatility. It revealed periods of large and small volatility. The global market situation impacted Polish agricultural markets with the opening markets and a greater access to the new markets. The periods having the strongest impact on Polish agricultural markets were the integration with the EU, the global crisis in 2008, and problems in the EU zone. The prices of analysed agricultural commodities differed in various EU countries. The prices of wheat increased most in France, Hungary and Lithuania. The prices of store cattle increased most in the years 2004–2015 in Estonia, Sweden and Luxemburg. The prices of pigs increased most in Malta, Sweden and Cyprus. 

Can Bitcoin be the Future of Digital Payments?

2019 ◽  
Vol 10 (6) ◽  
pp. 489-500
Author(s):  
Andrea Valente ◽  
◽  
David Atkinson ◽  
Keyword(s):  
Price Volatility ◽  
Global Scale ◽  
White Paper ◽  
Innovative Technology ◽  
Policy Makers ◽  
The Future ◽  
Key Drivers ◽  
Digital Payments ◽  
Robust Regulation ◽  
Stakeholder Acceptance

This study aimed to investigate the conditions in which Bitcoin has developed as a leading cryptocurrency and, according to Nakamoto (2008), could become an instrument for everyday payments around the world. In comparison to other digital payment solutions, Bitcoin is based on a peer-to-peer electronic cash system using “the blockchain”. This innovative technology allows for decentralised storage and movement of currency in a fully anonymous way, introducing advantageous methods for encrypted security and faster transactions (Hagiu & Beach, 2014). Scepticism regards Bitcoin’s foundation, energy consumption and price volatility, however, did not take long to arise (Holthaus, 2017). Ten years from its white paper release, Bitcoin is further supported by the same drivers which could sustain its growth as the future of digital payments (Russo, 2018). In order to investigate the key drivers and feasibility of acceptance, a London based survey was used to understand the desirability of Bitcoin as a day-to-day tool for digital payments. Additionally, this research analysed Bitcoin’s stakeholders and forecast drivers of sustainability for its application to become the future of the payment industry. A space which relies on policies that involve multiple layers of society, governments, regulators and tech-firms, all on a global scale. The findings confirmed how the increasing lack of trust of political and financial institutions, coupled with the increasing cases of data-breaches by tech-firms, encouraged over 70% of respondents to consider more decentralised and anonymous methods for their day-to-day actions; like payments. Policy makers need to cope with societies increasingly separating politically but gathering together digitally (LBS, 2017). For Bitcoin to truly establish itself as a global digital payment solution, key stakeholder acceptance must converge alongside the introduction of more robust regulation.

Future of Commodity Markets and Investments

2018 ◽  
Author(s):  
Hunter M. Holzhauer
Keyword(s):  
Supply And Demand ◽  
Commodity Markets ◽  
Investment Banks ◽  
Algorithmic Trading ◽  
Excess Supply ◽  
The Future ◽  
Change Concerns ◽  
Global Population ◽  
Regulatory Trends

This chapter begins with a breakdown of recent growth trends for the overall commodities market. However, the long-term future of the market will heavily depend on three pressing issues: excess supply, increased regulations, and algorithmic trading. The section on excess supply explores how traders are changing strategies to adjust to the current imbalance between supply and demand, especially in the steel industry, and how that imbalance might change in the future based on global population trends and climate change concerns. The next section examines several regulatory trends, including the dramatic exodus of some investment banks from certain segments of the commodities market followed by a section focusing on how algorithmic trading is influencing how commodities are traded. A discussion of potential scenarios for the commodities market follows. The chapter concludes by examining a few ways in which the market and commodity traders may both survive and even thrive in the future.

The dependence structure in volatility between Shanghai and Shenzhen stock market in China

2016 ◽  
Vol 6 (3) ◽  
pp. 264-283 ◽  
Author(s):  
Mingyuan Guo ◽  
Xu Wang
Keyword(s):  
Stock Market ◽  
High Frequency ◽  
Estimation Method ◽  
Garch Model ◽  
Price Volatility ◽  
Market Volatility ◽  
High Frequency Data ◽  
Dependence Structure ◽  
Frequency Data ◽  
Content Type

Purpose – The purpose of this paper is to analyse the dependence structure in volatility between Shanghai and Shenzhen stock market in China based on high-frequency data. Design/methodology/approach – Using a multiplicative error model (hereinafter MEM) to describe the margins in volatility of China’s Shanghai and Shenzhen stock market, this study adopts static and time-varying copulas, respectively, estimated by maximum likelihood estimation method to describe the dependence structure in volatility between Shanghai and Shenzhen stock market in China. Findings – This paper has identified the asymmetrical dependence structure in financial market volatility more precisely. Gumbel copula could best fit the empirical distribution as it can capture the relatively high dependence degree in the upper tail part corresponding to the period of volatile price fluctuation in both static and dynamic view. Originality/value – Previous scholars mostly use GARCH model to describe the margins for price volatility. As MEM can efficiently characterize the volatility estimators, this paper uses MEM to model the margins for the market volatility directly based on high-frequency data, and proposes a proper distribution for the innovation in the marginal models. Then we could use copula-MEM other than copula-GARCH model to study on the dependence structure in volatility between Shanghai and Shenzhen stock market in China from a microstructural perspective.

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