A Geometric Construction for the Arithmetic Mean, the Geometric Mean and the Harmonic Mean of Two Positive Numbers

1961 ◽  
Vol 61 (1) ◽  
pp. 45-46
Author(s):  
Adrien L. Hess
Author(s):  
William H Black ◽  
Lari B Masten

There is ongoing controversy in the business valuation literature regarding the preferability of the arithmetic mean or the harmonic mean when estimating ratios for use in business valuation. This research conducts a simulation using data reported from actual market transactions. Successive random samples were taken from data on valuation multiples and alternative measures of central tendency were calculated, accumulating more than 3.7 million data points. The measures (arithmetic mean, median, harmonic mean, geometric mean) were compared using hold-out sampling to identify which measure provided the closest approximation to actual results, evaluated in terms of least squares differences. Results indicated the harmonic mean delivered superior predictions to the other measures of central tendency, with less overstatement. Further, differences in sample size from 5 to 50 observations were evaluated to assess their impact on predictive performance. Results showed substantial improvements up to sample sizes of 20 or 25, with diminished improvements thereafter.


Axioms ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 144
Author(s):  
Radu Iordanescu ◽  
Florin Felix Nichita ◽  
Ovidiu Pasarescu

The main concepts in this paper are the means and Euler type formulas; the generalized mean which incorporates the harmonic mean, the geometric mean, the arithmetic mean, and the quadratic mean can be further generalized. Results on the Euler’s formula, the (modified) Yang–Baxter equation, coalgebra structures, and non-associative structures are also included in the current paper.


2017 ◽  
Vol 8 ◽  
pp. 1
Author(s):  
Juan A. Marin-Garcia ◽  
Julien Maheut ◽  
Julio J. Garcia Sabater

<p>We present the results of comparing various ways of calculating students' final grades from continuous assessment grades. Traditionally the weighted arithmetic mean has been used and we compare this method with other alternatives: arithmetic mean, geometric mean, harmonic mean and multiplication of the percentage of overcoming of each activi-ty. Our objective is to verify, if any of the alternative methods, agree with the student’s performance proposed by the teacher of the subject, further discriminating the grade be-tween high and low learning outcomes and reducing the number of approved opportunists.</p><p> </p><p>[Comparación del efecto de diferentes modos de agregar las califica-ciones de evaluación continua en la nota final]</p>


1971 ◽  
Vol 97 (2-3) ◽  
pp. 297-324 ◽  
Author(s):  
Peter Marks ◽  
Alan Stuart

SummaryThis paper investigates the recalculation from its base date of theFinancial TimesIndex of Industrial Ordinary Shares (hereafter called theFTIndex) using the ordinary arithmetic mean of the values of its constituents, rather than the geometric mean that is actually used in its calculation. The value of this arithmetic version of theFTIndex represents that of a portfolio invested equally in each of the original constituents at the base date. The behaviour of the recalculated index may therefore be described in portfolio terms.The arithmeticized index has been calculated at each end-year since the base date of theFTIndex (1 July 1935). By the end of 1970 its value was 38% higher than that of the (geometric)FTIndex. The percentage by which the new index exceeded the original was found to have increased approximately linearly with time; a least-squares linear fit over the whole period indicated that the percentage excess of the arithmetic version over the original index had increased on average by 0·8% a year. A separate fit for the period from end-1960 onwards shows that this rate had increased to 2·7% per year, and even over the period since 1950, it has been 1·1% per year. Use of these relationships gives a rough adjustment of theFTIndex for portfolio comparison purposes.We also calculated a series of arithmetic indices with base dates at the end of each year since the original base date of theFTIndex. In the majority of calendar years since its foundation, theFTIndex has not fallen far behind the corresponding arithmetic version over the twelve month period. However, over periods of more than a year, the geometric and arithmetic indices can show dramatically different results, particularly if the percentage change in the index value is considered. It is clear that longer-term changes in the value of theFTIndex cannot be interpreted as the changes that would have occurred in the value of a portfolio equally invested in the thirty constituent shares at the beginning of the period.None of these findings affects the usefulness of theFTIndex for its original purpose, as a sensitive daily indicator of changes in the industrial ordinary share market. It is purely its long-run use as a portfolio standard that is misleading. For this purpose the more recently instituted arithmetic indices are likely to be useful in the future. Meanwhile, our arithmeticizedFTIndex values may be useful to correct the downward drift imposed on theFTIndex by its geometric construction.


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