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Abstract

The corporate cost of capital is used by valuators to discount future flows of income from an entity in order to derive a present-day, forward-looking value of that entity. The cost of capital is therefore determined as the weighted cost of the various sources of funding, being typically equity, debt and preference instruments. The tricky and important part is estimating the cost of equity, which usually needs the application of finance models. The study on the texts on mineral valuation or mineral project evaluation demonstrates that the capital asset pricing model (CAPM) is a general model for estimating the cost of equity. However, according to shortfalls and problems relating to it a relatively similar and simpler model i.e. the single-index market model is proposed. The single index market model is an important tool in contemporary research in finance. Much of the importance of the model follows from its 'beta' parameter which, ideally, measures the sensitivity of returns on a security to changes in a market model. To estimate the cost of equity of the mining and cement companies listed in Tehran Stock Exchange (TSE) The single-index market model is selected because of the shortfalls and problems of the CAPM as well as the lack of commercial services for determining the market premium. The regression analysis as well as the statistical analysis is carried out using Excel spreadsheet. The statistic significance of the model is tested using t and F test statistics. The results showed that the independent variable (the rate of return on the market index) has a genuine effect on the dependent variable (the rate of return for the stock) and there is a statistically significant linear relationship between the two variables at significance level of 5%. Finally, the cost of equity formining and cement companies is estimated 25.0% and 31.0% respectively. Knowing the cost of equity, calculating the discount rate will not be very difficult.

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Authors and Affiliations

Mohsen Taheri
Mehdi Irannajad
Majid Ataee-Pour
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Abstract

Zinc plant residue is a hazardous waste which contains high quantity of nickel and other valuable metals. Process parameters such as reaction time, acid concentration, solid-liquid ratio, particle size, stirring speed and temperature for nickel extraction from this waste were optimized using factorial design. Main effects and their interactions were obtained by the analysis of variance ANOVA. Empirical regression model was obtained and used to predict nickel extraction with satisfactory results and to describe the relationship between the predicted results and the experiment results. The important parameters for maximizing nickel extraction were identifi ed to be a leaching time solid-liquid ratio and acid concentration. It was found that above 90% of nickel could be extracted in optimum conditions.
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Authors and Affiliations

Mahdi Gharabaghi
Mehdi Irannajad
Amir Reza Azadmehr
Majdi Ejtemaei

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