AR Model Based on Time Series Modeling for Predicting Egg Market Price in 2021

Eggs,as a meat consumer product in China,are closely related to the vegetable basket project.Exploring and predicting the future trend of egg market price is of great significance for stabilizing egg price and market supply.In this study,the time series AR model was used for fitting the egg market prices in the 66 d from January 1 to March 7,2021,and the delay operator nlag18 was used for white noise test,giving pr>probability of chisq<0.005.The time series was not a white noise series,and then the stationary series was used for modeling.The optimal model was selected as the AR series(BIC(3,0)),and finally,the egg market price model AM was obtained as X_(t)=9.0556+(1+0.8926)ε_(t),which was the optimal model.The model showed that the egg price fluctuations in 2021 will be clustered,and the later price will be significantly affected by external factors in the previous period.The dynamic prediction results of the model showed that the egg price would stop falling in March 2020,and the egg price would continue to slow down in March.

Rice quality in relation to market prices in Yunnan Province

Factors affecting rice quality and their impacts on market price were investigated in this study. On-farm survey and market survey was undertaken in three selected sites namely Kunming, Dali, and Xishuangbanna in Yunnan Province, China. Market sampling was conducted to determine important rice quality characteristics. Sixty milled rice samples were collected from domestic markets of the three sites during a period of Mar to Apr in 1994. The grain physicochemical properties of the milled rice samples were analyzed on the basis of Chinese Agricultural Ministry Standard for testing rice quality. A hedonic price model (implicit price model) was further employed to quantify relationships between quality characteristics and market prices of rice. The model can be expressed mathematically as the following function (1) This function shows that the average price paid by consumer for different grades of rice with attribute Xj. Using the ordinary least square (OLS) regression of observed market prices on measures

Regression Analysis of Electric Power Market Price of JEPX

The deregulation of electric power industries is introducing around the world and electric power markets are operated under the deregulation. Also in Japan, JEPX (Japan Electric Power Exchange) operates a day-ahead market since April 2005. We have already analyzed the electric power market prices in the several markets including JEPX by autoregressive models. We compose simple regression equations, of which a dependent variable is the market price and explanatory variables are the demand and the market price of 24 hours ago. In this paper, we analyze JEPX price data in summer seasons from 2007 to 2013. In this period, the JEPX price is affected by many social phenomena such as Lehman Shock and East Japan earthquake disasters. We compare the determination coefficient and the coefficients of regression and investigate the change of coefficients over the years.

Asymmetric Price Transmission Analysis of the International Soybean Market

This study analyzed the asymmetric price transmission in the international soybean market, using data from the US (Chicago Futures), European (Rotterdam), Brazilian (Paranaguá), Argentinian (Rosario Futures and Rosario Spot), and Chinese (Spot and Futures) markets. The study looked at the price transmission between these markets over a period of almost 10 years, from September 2009 to May 2019. The Phillips-Perron unit root test was used to determine the order of integration of the time series. The Engle-Granger cointegration test failed to find any evidence of cointegration between the Chinese and Argentinian markets with any others of the international markets. The lack of cointegration was associated with highly government intervened markets. The cointegration and threshold test proposed by Enders and Siklos, succeeded in rejecting the Null hypothesis and finding cointegration among the series after structural breaks had been taken into account. The BDS test for nonlinearity showed that most of the time series were nonlinear, which prompted the investigation to look into nonlinear modelling. To evaluate asymmetric price transmission, the study used the Threshold autoregressive (TAR) model and the momentum threshold model (MTAR). The Argentine and Chinese markets were primarily suspected of exhibiting asymmetric price transmission due to structural government intervention. However, the test results failed to reject the null hypothesis and revealed asymmetric price transmission between these markets and the international market. As expected, the results found no evidence of asymmetric price transmission in the Paranaguá, Rotterdam, and Chicago markets. Hence, it can be concluded that symmetric price transmission is more prevalent in the global soybean market than asymmetric price transmission.

NECESSARY AND SUFFICIENT CONDITION FOR THE EXISTENCE OF A NONNEGATIVE EQUILIBRIUM PRICE VECTOR IN THE CAPITAL MARKET WITH SHORT-SELLING

For the capital market satisfying standard assumptions that are widely adopted in the equilibrium analysis,a necessary and sufficient condition for the existence and uniqueness of a nonnegative equilibrium price vector that clears the mean-variance capital market with short sale allowed is derived.Moreover,the given explicit formula for the equilibrium price shows clearly the relationship between prices of assets and statistical properties of the rate of return on assets,the desired rates of return of individual investors as well as other economic quantities.The economic implication of the derived condition is briefly discussed.These results improve the available results about the equilibrium analysis of the mean-variance market.

A Short-Term Electricity Price Forecasting Scheme for Power Market

Electricity price forecasting has become an important aspect of promoting competition and safeguarding the interests of participants in electricity market. As market participants, both producers and consumers intent to contribute more efforts on developing appropriate price forecasting scheme to maximize their profits. This paper introduces a time series method developed by Box-Jenkins that applies autoregressive integrated moving average (ARIMA) model to address a best-fitted time-domain model based on a time series of historical price data. Using the model’s parameters determined from the stationarized time series of prices, the price forecasts in UK electricity market for 1 step ahead are estimated in the next day and the next week. The most suitable models are selected for them separately after comparing their prediction outcomes. The data of historical prices are obtained from UK three-month Reference Price Data from April 1st to July7th 2010.

The Empirical Analysis of the Dynamic Prices Relationship between Cotton Spot Market and Futures Market in Xinjiang

The thesis analyzes the causal relationship between the cotton spot,and the tendency and impact of prices of futures markets in Xinjiang by using ADF test,co-integration analysis,Granger causality test and other econometric methods in order to discuss the interacted relationship between futures market prices of cotton and spot market prices since the futures of cotton in Xinjiang go public.The results of empirical analysis show that the spot market prices of cotton and the futures market prices in Xinjiang fluctuate prominently in the short run and tend to counterpoise in the long run;the futures market of cotton plays the role of leading the spot market prices of cotton in Xinjiang,while the spot market prices of cotton in Xinjiang impacts little on the futures market prices.The corresponding countermeasures are put forward.The government should continuously perfect the construction of the futures market of cotton in Xinjiang,so as to exert the function of price discovery and the function of hedging,and promote the development of cotton industry in Xinjiang.

Cassava sector development in Cameroon: Production and marketing factors affecting price

Regular and available supply is the prerequisite of an effective and efficient commercialization process. Using multivariate regression analysis on field data, this research appraises the production and marketing factors that influence cassava market price. The production factors include cultivated area, planting material, yield, and farmers’ field schools;while farmers access to a paved road, having a telephone, the transportation costs of fresh roots, the level of root perishability, and the prices of rice and maize stand as marketing factors. The results show that farmers who attended farmers’ field school adopted improved planting materials, propagated them in their localities and the yields in these communities increased significantly. The farm size also has a significant influence on the availability of fresh roots. On the marketing side, transportation costs, access to a paved road, the prices of rice and maize significantly affect cassava’s market price and tighten the relationship between producers and marketers. We conclude that to increase fresh roots supply, roads leading to cultivating areas should be paved, better transportation provided, communication costs reduced, even distribution of planting materials and appropriate warehouses.

Comparison of ARIMA and ANN Models Used in Electricity Price Forecasting for Power Market

In power market, electricity price forecasting provides significant information which can help the electricity market participants to prepare corresponding bidding strategies to maximize their profits. This paper introduces the models of autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) which are applied to the price forecasts for up to 3 steps 8 weeks ahead in the UK electricity market. The half hourly data of historical prices are obtained from UK Reference Price Data from March 22nd to July 14th 2010 and the predictions are derived from a sliding training window with a length of 8 weeks. The ARIMA with various AR and MA orders and the ANN with different numbers of delays and neurons have been established and compared in terms of the root mean square errors (RMSEs) of price forecasts. The experimental results illustrate that the ARIMA (4,1,2) model gives greater improvement over persistence than the ANN (20 neurons, 4 delays) model.

Duration Dependence in Housing Price Market: A Metro Level Test in United States

Duration dependence affects the dynamics of multi sate time to event outcomes. In this paper we are testing if a contraction or an expansion state for the housing price is duration dependent on previous states lengths. This test has implications for explaining the dynamics and the predictability of the housing prices in subsequent spells of contraction/expansion. The test is carried on using a discrete time duration model. This research shows that federal fund rate has strong effect on duration of both expansion and contraction. The analysis is also showing that while for both contraction and expansion spells we observe duration dependence, the risk of exiting from either spell at the beginning of the spell is practically flat for the first five to six years in the expansion spells and between seven and eight years in the contraction spells. After these periods the risk of exiting an expansion spell is increasing but in a non-monotone way, while for the contraction spell the risk of exiting the state is increasing in a monotone way, making the contraction periods easier to predict than the expansion periods.

Cotton Market Fundamentals ＆ Price Outlook

Recent price movement All benchmark prices except the CC Index increased over the past month.Prices for the March NY futures contract surged in late December,rising from75 cents/lb to just below 80 cents/lb.Following that round of increases,there

Seminar on“Cotton Price and Market”Outlook and Expectation for 2011

Sponsored by Cotton Council International and co-organized by the Hong Kong Association of Textile Bleachers,Dyers,Printers and Finishers and the Hong Kong Cotton Spinners Association,the seminar on"Cotton Price and Market:Outlook and Expectation for 2011"was held at the Clothing

Cotton Market Fundamentals ＆ Price Outlook

Recent Price Movement Global cotton prices were largely stable over the last month,with marginal increases marked in several international benchmarks The New York March futures contract edged higher the last several weeks,rising from values near 77 cents/lb in late November to those approaching