Search
Search Results
-
Note on simple and logarithmic return
127-136Views:721In this paper we describe and clarify the definitions and the usage of the simple and logarithmic returns for financial assets like stocks or portfolios. It can be proven that the distributions of the simple and logarithmic returns are really close to each other. Because of this fact we investigate the question whether the calculated financial risk depends on the use of simple or log returns. To show the effect of the return-type on the calculations, we consider and compare the riskiness order of stocks and portfolios. For our purposes, in the empirical study we use seven Hungarian daily stock prices and for the risk calculation we focus on the following risk measures: standard deviation, semivariance, Value at Risk and Expected Shortfall. The results clearly show that the riskiness order can depend on the use of the return type (i.e. log or simple return). Generally, often – due to missing data or the nature of the analysis – one has to use approximations. We also examine the effect of these approximations on the riskiness order of stocks and of portfolios. We found differences in the riskiness order using exact or approximated values. Therefore, we believe, if this is possible, exact values instead of approximated ones should be used for calculations. Additionally, it is important that one uses the same type of return within one study and one has to be aware of the possible instabilities when comparing return results.
JEL Code: C18
-
Intensity and Profitability of Smallholder Cassava Farmers’ Participation in Value Addition in Afijio Local Government Area of Oyo State, Nigeria
Views:207This study investigated the intensity and profitability of smallholder cassava farmers’ involvement in cassava value addition in Afijio Local Government Area of Oyo State, Nigeria. Data were collected from 150 cassava farming households through the use of a well-structured questionnaire and employing a simple random sampling procedure. The data collected included information on the socioeconomic characteristics of the respondents, intensity of value addition among the respondents, factors influencing their decisions to add value as well as the extent of value addition, profitability of cassava value addition and the factors that determined the profitability level of the enterprises. The data were analyzed using the descriptive statistics for profiling the socioeconomic characteristics of the respondents, gross margin was used to measure profitability, and ordinary least squares regression model was used to determine the factors influencing the decisions of smallholder cassava farmers to add value to cassava as well as the extent of value addition among them. The results revealed that majority of the respondents were females (52.7%) with average age between 31-40 years of age while the average household size (52.7%) is between 6-10 members. Regression analysis of the determinants of the intensity of value addition revealed that the decisions to add value to cassava as well as the extent to which value was added were influenced positively by educational attainment, household size, and years of experience in cassava value addition. Results of the gross margin analysis revealed a positive return on variable costs thus indicating that the cassava value adding enterprise is a profitable one. These findings presented the need for all the stakeholders concerned to focus their attentions on proffering solutions to the challenges faced by cassava processors within the minimum time possible.
JEL code: L11, M11, M21, Q13, R32