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In recent years skewness has become a much-discussed factor in financial research, and many studies/models involve the skewness of various financial variables. This paper (i) points out the universal neglect in the finance literature of skewness' sampling error and its significant consequences; (ii) presents a simple approach for roughly constructing a confidence interval for skewness estimated from lognormal populations; (iii) points out directions of further research for developing a comprehensive approach for estimating skewness reliably. [ABSTRACT FROM AUTHOR]

The two standard steps for estimating PERT times are: Step 1, estimate a, m, and b; and Step 2, use the 'classical' formulae μ = (a + 4m + b)/6 and σ = (b - a)/6. We review the shortcomings of the textbook definitions of a, m and b; we also review the inconsistency of Step 1 with the literature on probability elicitation. A 5- or 7-fractile alternative is then proposed and justified for Step 1. Next, we develop simple but very accurate formulae for computing μ and σ with the fractiles estimated in our Step 1. For contrast, we also show that the classical PERT formulae are very inaccurate, even for the very restricted subset of beta distributions for which the formulae are supposedly applicable. Our overall purpose is to combine earlier findings with some new results to argue that: (i) the classical PERT formulae are both illogical and inaccurate, so we should not continue to teach and use them; and (ii) simple and more logical alternatives are available. [ABSTRACT FROM AUTHOR]

This paper considers an extension of the classical newsboy problem where a stochastic price-demand relationship exists for the product. First presented is a versatile approach capable of modeling price-demand relationships of various levels of complexities. Solution procedures are then presented for different optimization objectives. For the simplest price-demand relationship, analytical solutions are obtainable. For other cases, very efficient numerical procedures are developed. [ABSTRACT FROM AUTHOR]