What determine the price of Bonga sheep at the market level in Southwestern Ethiopia? A hedonic price analysis

Background Bonga sheep is a mutton type breed with a long-fat-tail and better body weight at maturity. The breed is especially located in the Southwestern mid and highland land areas of Ethiopia. Currently, the breed was well known in Ethiopia and also its price is higher as compared to other sheep breeds in the country. However, empirical evidence is lacking on price determinants of the breed in Ethiopia. Therefore, this research aims at identifying sheep attributes and other factors that determine the market prices of Bonga sheep in Southwestern Ethiopia. Methodology Data from 300 traded sheep and sheep marketers were collected from five major sheep marketing centers in the Kaffa zone. A hedonic price model adjusted for heteroscedasticity was employed to analyze the observed price data. Results The model result showed that the attributes of the sheep are important guiding criteria in price formulation. Among the attributes age, sex (male), colour (red), body condition (good), tail type (very fat) and absence of horn significantly and positively determine the sheep price. As well, market place (Gojebi and Bonga) near to big cities and season (holiday) and purpose of purchase are also significant determinants of bong sheep price out of the sheep attributes in Southwestern Ethiopia. Conclusion Targeting in systematic improvement of the significant attributes which are demanded by the market and establishment of a breeding program to make sheep improvement in a sustainable way. Besides, effort should be geared to transform the system into a market-oriented system using a value chain framework by improving access to market information.

Price Analysis and Forecasting for Bitcoin Using Auto Regressive Integrated Moving Average Model

This paper investigated Bitcoin daily closing price using time series approach to predict future values for financial managers and investors. Daily data were sourced from CoinDesk, with Bitcoin Price Index (BPI) for 5 years (January 1, 2016 to May 31, 2021) extracted. Data analysis and modelling of price trend using Autoregressive Integrated Moving Average (ARIMA) model was carried out, and a suitable model for forecasting was proposed. Results showed that ARIMA(6,1,12) model was the most suitable based on a combination of number of significant coefficients and values of volatility, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). A two-month test window was used for forecasting and prediction. Results showed a decline in prediction accuracy as number of days of the test period increased; from 99.94% for the first 7 days, to 99.59 % for 14 days and 95.84% for 30 days. For the two-month test period, percentage accuracy was 84.75%. The study confirms that the ARIMA model is a veritable planning tool for financial managers, investors and other stakeholders; especially for short-term forecasting. It is however imperative that the influence of external factors, such as investors’/influencers’ comments and government intervention, that may affect forecasting be taken into consideration.

Stock price analysis based on the research of multiple linear regression macroeconomic variables

The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock price changes of domestic agricultural listed companies. The article uses a stable time series based on the ARMA model for stable agricultural value-added, fiscal expenditure and market interest rates. The regression method is used to study its impact on the stock price index. Compared with the existing stock forecasting methods, this method has simple data collection and no specific requirements for data selection, and the prediction results have a high degree of fit. Therefore, this method is suitable for most stocks.

Costing, Adobe Technique as a Sustainable Construction System in the City of Cuenca

Adobe is an old material used in construction but over time, this construction system has lost space and preference among population. Hence, the need to seek alternatives as professionals in the construction area to encourage the use of the Adobe technique has raised. Thus, the present study made a cost of the items involved in the construction of houses from the adobe based on the theoretical references. In addition, it established a unit price analysis that identifies the particularities of this system focusing on an analytical, descriptive-conclusive methodology whose data are analysed from the results of applying a survey (n = 96) to the inhabitants of the rural sector of Cuenca and construction experts (n = 11). The average price of the construction of houses with Adobe is $ 38,357.23 dollars for a house of 150 m2 taking into account that the real costs and the construction activity are sensitive to changes in the population and market prices.

Evaluation and Analysis of Unit Prices of a Rammed Earth Construction System

The tapial is part of the traditional construction worldwide, which uses environmentally friendly materials of natural origin such as raw earth, wood and water for its manufacture. The construction technique was used for the construction of habitable spaces, which are part of the ancestral construction system of our country; Despite the above, no updated studies on the costs required in the construction process have been identified in Ecuador. This is mainly due to the constant development of new technologies that introduce new construction systems to the market that use industrialized materials for their manufacture. Therefore, this document evaluated and analyzed the unit prices of the items involved in the construction of works using mud as its main component. Field and exploratory research was applied, through the application of surveys to a sample of 97 professionals of Civil Engineering and Architecture in the city of Cuenca, as well as 30 professionals with experience in construction of the indicated construction system. The Unit Price Analysis determined that the average cost of a 140 m2 typical house is $ 46,236.64 with an estimated cost of $ 330.26 per square meter; Similarly, the study determined a maximum cost of $ 53,172.14 USD with a value of $ 379.80 USD per square meter and a minimum value that represents $ 39,301.14 with a cost per square meter of $ 280.72.

Assessment of genetic diversity within eucheumatoid cultivars in east Sabah, Malaysia

Studies have shown that cultivars of the carrageenophytes Kappaphycus and Eucheuma are clones of a limited number of strains originally domesticated from wild populations. For the development and selection of new cultivars, it is important that a comprehensive record of available variants exists. This study was conducted to provide up-to-date analysis and compilation of the current state of cultivars as the last list of cultivars was compiled nearly a decade ago. The present study analyzed the cox2–3 spacer and cox1 (1356 bp) genetic diversity of cultivars collected from 2019 to 2020 from the east coast of Sabah where the seaweed farms are concentrated. These data were compared with cultivars reported from 2010 to 2012 to assess changes, if any, to the gene pool of farmed eucheumatoid in Malaysia. Kappaphycus alvarezii, K. striatus, and K. malesianus are currently cultivated while Eucheuma denticulatum is no longer an important cultivar compared to a decade ago, probably due to its lower price. Analysis of the cox2–3 spacer revealed a new haplotype, LBT10, and, by including published GenBank data, a further four previously unnamed haplotypes were recognized from Sabah. This study confirms that there is a limited gene pool within cultivars in Malaysia and suggests the need for new or genetically diverse cultivars which can adapt to a changing environment, to ensure a more sustainable carrageenan industry.

Stock Analysis Method based on Multiple Linear Regression

In order to research the application of multivariate linear regression in stock price analysis, seven independent variables were selected to estimate in this paper. The regression coefficient was calculated by SPSS and the statistical test was carried out. And finally, the model was applied to the closing price prediction, and the prediction error was within acceptable range.