scholarly journals Short-Period Pricing Models for Fed Cattle and Impacts of Wholesale Carcass Beef and Live Cattle Futures Market Prices

1981 ◽  
Vol 13 (1) ◽  
pp. 125-132 ◽  
Author(s):  
Clement E. Ward
Keyword(s):  
Task Force ◽  
Futures Market ◽  
National Commission ◽  
Pricing Models ◽  
Market Prices ◽  
Trade Associations ◽  
Spot Prices ◽  
Transaction Prices ◽  
Short Period ◽  
General Accounting Office

Cattlemen have expressed concern about wholesale beef and fed cattle pricing and have antitrust lawsuits pending against supermarkets, meatpackers, trade associations, and a meat price reporting firm. Lawsuits allege manipulation of wholesale carcass beef prices to artificially depress spot prices for fed cattle (General Accounting Office, 1977). Congressional and administrative investigations have focused on wholesale carcass beef pricing and price reporting and their effects on fed cattle pricing (Committee on Small Business, General Accounting Office, 1978; National Commission on Food Marketing; Packers and Stockyards Program, 1978). Cattlemen also have expressed dissatisfaction with live cattle futures markets before congressional and administrative committees, alleging that futures market prices adversely affect spot prices for fed cattle (Leuthold and Tomek; Meat Pricing Task Force). However, economists have not empirically studied the impacts of wholesale carcass beef and live cattle futures market prices in short-period pricing models for fed cattle, that is, impacts on individual transaction prices.

Relationship between Coffee Prices in Spot and Futures Markets-An Empirical Analysis

2020 ◽  
pp. 180-188
Keyword(s):  
New York ◽  
Correlation Coefficients ◽  
Strong Relationship ◽  
Futures Market ◽  
Regression Coefficients ◽  
Futures Prices ◽  
Market Prices ◽  
Spot Prices ◽  
Correlation And Regression Analysis ◽  
Highly Correlated

The present study explored the relationship between spot and futures coffee prices. The Correlation and Regression analysis were carried out based on monthly observations of International Coffee Organization (ICO) indicator prices of the four groups (Colombian Milds, Other Milds, Brazilian Naturals, and Robustas) representing Spot markets and the averages of 2nd and 3rd positions of the Intercontinental Exchange (ICE) New York for Arabica and ICE Europe for Robusta representing the Futures market for the period 1990 to 2019. The study also used the monthly average prices paid to coffee growers in India from 1990 to 2019. The estimated correlation coefficients indicated both the Futures prices and Spot prices of coffee are highly correlated. Further, estimated regression coefficients revealed a very strong relationship between Futures prices and Spot prices for all four ICO group indicator prices. Hence, the ICE New York (Arabica) and ICE Europe (Robusta) coffee futures prices are very closely related to Spot prices. The estimated regression coefficients between Futures prices and the price paid to coffee growers in India confirmed the positive relationship, but the dispersion of more prices over the trend line indicates a lesser degree of correlation between the price paid to growers at India and Futures market prices during the study period.

scholarly journals Household electricity demand, the intrinsic flexibility index and UK wholesale electricity market prices

2020 ◽  
Author(s):  
Jacopo Torriti
Keyword(s):  
Electricity Market ◽  
Power Plants ◽  
Electricity Demand ◽  
Market Prices ◽  
Vast Number ◽  
Spot Prices ◽  
Time Use Survey ◽  
Wholesale Electricity Market ◽  
The Uk ◽  
Flexibility Index

AbstractDuring peak electricity demand periods, prices in wholesale markets can be up to nine times higher than during off-peak periods. This is because if a vast number of users is consuming electricity at the same time, power plants with higher greenhouse gas emissions and higher system costs are typically activated. In the UK, the residential sector is responsible for about one third of overall electricity demand and up to 60% of peak demand. This paper presents an analysis of the 2014–2015 Office for National Statistics National Time Use Survey with a view to derive an intrinsic flexibility index based on timing of residential electricity demand. It analyses how the intrinsic flexibility varies compared with wholesale electricity market prices. Findings show that spot prices and intrinsic flexibility to shift activities vary harmoniously throughout the day. Reflections are also drawn on the application of this research to work on demand side flexibility.

scholarly journals Empirical Evidence on Time-Varying Hedging Effectiveness of Emissions Allowances under Departures from the Cost-of-Carry Theory

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Kai Chang
Keyword(s):  
Futures Market ◽  
Time Varying ◽  
Conditional Volatility ◽  
Conditional Correlation ◽  
Spot Prices ◽  
Market Participants ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Cost Of Carry ◽  
The Cost

Under departures from the cost-of-carry theory, traded spot prices and conditional volatility disturbed from futures market have significant impacts on futures price of emissions allowances, and then we propose time-varying hedge ratios and hedging effectiveness estimation using ECM-GARCH model. Our empirical results show that conditional variance, conditional covariance, and their correlation between between spot and futures prices exhibit time-varying trends. Conditional volatility of spot prices, conditional volatility disturbed from futures market, and conditional correlation of market noises implied from spot and futures markets have significant effects on time-varying hedge ratios and hedging effectiveness. In the immature emissions allowances market, market participants optimize portfolio sizes between spot and futures assets using historical market information and then achieve higher risk reduction of assets portfolio revenues; accordingly, we can obtain better hedging effectiveness through time-varying hedge ratios with departures from the cost-of-carry theory.

Applying Property Pricing Models to Estimate a Foreclosure Discount in the Hotel Real Estate Sector

2021 ◽  
pp. 193896552110586
Author(s):  
Amrik Singh
Keyword(s):  
Hedonic Model ◽  
Repeat Sales ◽  
Cross Sectional ◽  
Market Prices ◽  
Holding Period ◽  
Transaction Prices ◽  
Real Estate Sector ◽  
Study Results ◽  
Deferred Maintenance ◽  
Independent Hotels

This study investigates the magnitude of the foreclosure sale discount in the hotel sector. The foreclosure sales discount is captured using three different models: hedonic, hybrid, and repeat sales. Controlling for various hotel attributes and time, the hedonic model shows a foreclosure discount of 40%, followed by the repeat sales model at 42% and the hybrid model at 45%, all relative to non-distressed market prices. The results of the study provide novel empirical evidence of cross-sectional variation in foreclosure discounts between independent hotels and branded hotel segments and by location. In particular, variation in the foreclosure discount is driven by independent and upscale hotels and hotels located in resorts, small metro towns, and urban locations. In addition, the study results reveal the influence of occupancy, deferred maintenance, renovation, and holding period on transaction prices.

scholarly journals Comparative Analysis of Transaction Prices and the Values of Forest Properties in Poland

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1323
Author(s):  
Radosław Gaca ◽  
Robert Zygmunt ◽  
Michal Gluszak
Keyword(s):  
Imperfect Information ◽  
Private Forest ◽  
Market Prices ◽  
Market Participants ◽  
Market Values ◽  
Transaction Prices ◽  
Property Prices ◽  
Additional Question ◽  
Unbiased Estimates ◽  
Asymmetrically Distributed

Research Highlights: In the paper, we explore systematic discrepancy between sale prices and values of forest properties in Poland. We argue that the systematic valuation bias found is partially caused by the simplified parametric appraisal methodology currently used in Poland. Background and Objectives: Most of the forests in Poland are state-owned, but in recent decades, the market for private forest properties has been dynamically growing. In the paper, we investigate the relations between the actual transaction prices, and the estimated value of forest properties in selected regions in Poland. We hypothesize that sale prices systematically deviate from valuations. An additional question arises regarding the determinants of forest property prices. We hypothesize that due to asymmetric information positive amenities are not fully capitalized in property prices in Poland. Materials and Methods: In the paper, we adopt two regression models used to investigate the valuation accuracy and bias. We test the hypothesis that valuations are unbiased estimates of transaction prices. Results: The results indicate that market prices for forest properties systematically differ from estimated values. Conclusions: Systematic deviation of forest property sales prices from market values may contribute to the imperfect information available to the market participants, especially when information is asymmetrically distributed between buyers and sellers. This may confirm the hypothesis that sellers are not fully aware of the advantages of the property being sold, and provide further explanations for large systematic differences between sales prices and valuations based on parametric valuation methods used in Poland.

The Unbiasedness and Hedging Effectiveness in KOSPI200 Futures Market

2007 ◽  
Vol 15 (1) ◽  
pp. 73-100
Author(s):  
Seok Kyu Kang
Keyword(s):  
Risk Management ◽  
Risk Premium ◽  
Futures Market ◽  
Spot Price ◽  
Sample Period ◽  
Futures Prices ◽  
Spot Prices ◽  
Hedging Effectiveness ◽  
Futures Price ◽  
Rolling Windows

This study is to examine the unblasedness hypothesis and hedging effectiveness in KOSPI20() futures market. The unbiasedness and efficiency hypothesis is carried out using a cointegration methodology. And hedging effectiveness is measured by comparing hedging performance of the naive hedge model, OLS hedge model. and constant correlation bivariate GARCH (1. 1) hedge model based on rolling windows. The sample period covers from May. 3. 1996 to December. 8, 2005. The empirical results are summarized as follows: First, there exists the cOintegrating relationship between realized spot prices and futures prices of the 10 day. 22 day. 44 day. and 59 day prior to maturity. Second. futures prices of backward the 10 day. 22 day. 44 day from maturity provide unbiased forecasts of the realized spot prices. The KOSPI200 futures price is likely to predict accurately future KOSPI200 spot prices without the trader having to pay a risk premium for the privilege of trading the contract. Third. for shorter maturity. the futures price appears to be the best forecaster of spot price. Forth, bivariate GARCH hedging effectiveness outperforms the naive and OLS hedging effectiveness. The implications of these findings show that KOSPI200 futures market behaves as unbiased predictor of future spot price and risk management instrument of KOSPI200 spot portfolio.

Empirical Investigation on Food Inflation and Efficiency Issues in Indian Agri-futures Market

2017 ◽  
Vol 3 (2) ◽  
pp. 156-165 ◽  
Author(s):  
Narinder Pal Singh ◽  
Archana Singh
Keyword(s):  
Trading Volume ◽  
Wholesale Price ◽  
Time Frame ◽  
Futures Market ◽  
Sufficient Evidence ◽  
Futures Trading ◽  
Causality Test ◽  
Short Period ◽  
The Government ◽  
Food Inflation

In early 2007, the Government of India (GoI) banned futures trading on some essential agro-commodities such as wheat, rice, and two varieties of lentils due to rising food inflation. However, futures trading in agri-commodities such as chana (chickpea), soy oil, rubber, and potato were temporarily suspended. Professor Abhijit Sen’s committee, constituted to study the relationship between futures trading and agricultural commodities inflation, did not find sufficient evidence of inflationary impact of futures trading in India due to too short period of commodity futures trading. Also, an efficient futures market is required for the producers, traders, and consumers to hedge their price risk. Thus, in this study, we analyze the market efficiency of agricultural futures market and the effect of futures trading on inflation with special reference to chana (chickpea) market in India. This study is for a time frame of 10 years from 2005–2014. The data on closing prices of chana in futures and spot markets and futures trading volume has been collected from National Commodity and Derivatives Exchange, and chana wholesale price index (WPI) monthly data from Office of the Economic Adviser, GoI. The collected data is analyzed for efficiency using Johansen cointegration approach and vector error correction (VEC) restrictions and inflationary effect using Toda Yamamoto (TY) version of Granger causality test. From the results, we find that the spot and futures prices for chana are cointegrated and unbiased, that is, the chana (chickpea) futures market is efficient. But, the futures trading of chana has inflationary impact, that is, futures trading volume of chana affects chana WPI. This research has got direct implications for government and market participants. India is the largest consumer of chana (chickpea)—the third most important pulse crop produced in the world. Thus, the inflationary impact of chana futures trading is a matter of concern for GoI.

Pipeline Rupture Detection Based on Machine Learning and Pattern Recognition

2016 ◽  
Author(s):  
Martin Di Blasi ◽  
Zhan Li
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Task Force ◽  
Detection System ◽  
Leak Detection ◽  
Guidance Document ◽  
Performance Expectations ◽  
Detection Systems ◽  
Short Period ◽  
Recognition And Response

Pipeline ruptures have the potential to cause significant economic and environmental impact in a short period of time, therefore it is critical for pipeline operators to be able to promptly detect and respond to them. Public stakeholder expectations are high and an evolving expectation is that the response to such events be automated by initiating an automatic pipeline shutdown upon receipt of rupture alarm. These types of performance expectations are challenging to achieve with conventional, model-based, leak-detection systems (i.e. CPM–RTTMs) as the reliability measured in terms of the false alarm rate is typically too low. The company has actively participated on a pipeline-industry task force chaired by the API Cybernetics committee, focused on the development of best practices in the area of Rupture Recognition and Response. After API’s release of the first version of a Rupture Recognition and Response guidance document in 2014, the company has initiated development of its own internal Rupture Recognition Program (RRP). The RRP considers several rupture recognition approaches simultaneously, ranging from improvements to existing CPM leak detection to the development of new SCADA based rupture detection system (RDS). This paper will provide an overview of a specific approach to rupture detection based on the use of machine learning and pattern recognition techniques applied to SCADA data.

A Bivariate Model for Deman and Spot Price of Electricity

2012 ◽  
Vol 433-440 ◽  
pp. 3910-3917
Author(s):  
Hilary Green ◽  
Nino Kordzakhia ◽  
Ruben Thoplan
Keyword(s):  
Electricity Markets ◽  
Historical Data ◽  
Extreme Values ◽  
Spot Price ◽  
Bivariate Model ◽  
Spot Prices ◽  
Short Period ◽  
Detailed Statistical Analysis ◽  
Modelling Methodology ◽  
The Mean

In this paper bivariate modelling methodology, solely applied to the spot price of electricity or demand for electricity in earlier studies, is extended to a bivariate process of spot price of electricity and demand for electricity. The suggested model accommodates common idiosyncrasies observed in deregulated electricity markets such as cyclical trends in price and demand for electricity, occurrence of extreme spikes in prices, and mean-reversion effect seen in settling of prices from extreme values to the mean level over a short period of time. The paper presents detailed statistical analysis of historical data of daily averages of electricity spot prices and corresponding demand for electricity. The data is obtained from the NSW section of Australian Energy Markets.

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