Pricing of decision-making units under non-constant returns to scale

In this article, we revisit a recent work on pricing decision-making units by Färe et al (2013) and extend it to allow for non-constant returns to scale technologies.     

Ranking decision-making units using common weights in DEA

Data envelopment analysis (DEA) is a linear programming technique that is used to measure the relative efficiency of decision-making units (DMUs). Liu et al. (2008) [13] used common weights analysis (CWA) methodology to generate a CSW using linear programming. They classified the DMUs as CWA-efficient and CWA-inefficient DMUs and ranked the DMUs using CWA-ranking rules. The aim of this study is to show that the criteria used by Liu et al. are not theoretically strong enough to discriminate among the CWA-efficient DMUs with equal efficiency. Moreover, there is no guarantee that their proposed model can select one optimal solution from the alternative components. The optimal solution is considered to be the only unique optimal solution. This study shows that the proposal by Liu et al. is not generally correct. The claims made by the authors against the theorem proposed by Liu et al. are fully supported using two counter examples.     

Measuring the performances of decision-making units using interval efficiencies

Efficiency is a relative measure because it can be measured within different ranges. The traditional data envelopment analysis (DEA) measures the efficiencies of decision-making units (DMUs) within the range of less than or equal to one. The corresponding efficiencies are referred to as the best relative efficiencies, which measure the best performances of DMUs and determine an efficiency frontier. If the efficiencies are measured within the range of greater than or equal to one, then the worst relative efficiencies can be used to measure the worst performances of DMUs and determine an inefficiency frontier. In this paper, the efficiencies of DMUs are measured within the range of an interval, whose upper bound is set to one and the lower bound is determined through introducing a virtual anti-ideal DMU, whose performance is definitely inferior to any DMUs. The efficiencies turn out to be all intervals and are thus referred to as interval efficiencies, which combine the best and the worst relative efficiencies in a reasonable manner to give an overall measurement and assessment of the performances of DMUs. The new DEA model with the upper and lower bounds on efficiencies is referred to as bounded DEA model, which can incorporate decision maker (DM) or assessor's preference information on input and output weights. A Hurwicz criterion approach is introduced and utilized to compare and rank the interval efficiencies of DMUs and a numerical example is examined using the proposed bounded DEA model to show its potential application and validity.     

Evaluating the performances of decision-making units based on interval efficiencies

Efficiency could be not only the ratio of weighted sum of outputs to that of inputs but also that of weighted sum of inputs to that of outputs. When the previous efficiency measures the best relative efficiency within the range of no more than one, the decision-making units (DMUs) who get the optimum value of one perform best among all the DMUs. If the previous efficiency is measured within the range of no less than one, the DMUs who get the optimum value of one perform worst among all the DMUs. When the later efficiency is measured within the range of no more than one, the DMUs who get the optimum value of one perform worst among all the DMUs. If the later efficiency is measured within the range of no less than one, the DMUs who get the optimum value of one perform best among all the DMUs. This paper mainly studies an interval DEA model with later efficiency, in which efficiency is measured within the range of an interval, whose upper bound is set to one and the lower bound is determined by introducing a virtual ideal DMU, whose performance is definitely superior to any DMUs. The efficiencies, obtained from interval DEA model, turn out to be all intervals and are referred to as interval efficiencies, which combine the best and the worst relative efficiency in a reasonable manner to give an overall assessment of performances for all DMUs. Assessor's preference information on input and output weights is also incorporated into interval DEA model reasonably and conveniently. Through an example, some differences are found from the ranking results obtained from interval DEA model and bounded DEA model using the Hurwicz criterion approach to rank the interval efficiencies.     

Measuring the performances of decision-making units using geometric average efficiency

Journal of the Operational Research Society - The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two...     

Economic inefficiency measurement of input spending when decision-making units face different input prices

In a recent paper, Kaoru Tone (J Opl Res Soc (2002) 2: 429–444) showed that when the Farrell measure of cost efficiency is estimated for two firms that have different input prices, a firm with higher costs can be deemed more efficient than a firm with lower costs. As an alternative approach, Tone proposed a radial cost efficiency measure that is estimated using levels of spending on each input, rather than input quantities. Thus, firms with higher costs are less efficient than firms with lower costs. In this paper, we extend Tone's approach by allowing for non-radial changes in spending. Our approach builds on earlier work by Luenberger (J Math Econ (1992) 21: 461–481) and Chambers et al (J Econ Theo (1996) 70: 407–419) who use directional distance functions to measure inefficiency. We provide an example and illustration of our approach using Japanese bank data.     

An equilibrium efficiency frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs

Based on the minimal reduction strategy, Yang et al. (2011) developed a fixed-sum output data envelopment analysis (FSODEA) approach to evaluate the performance of decision-making units (DMUs) with fixed-sum outputs. However, in terms of such a strategy, all DMUs compete over fixed-sum outputs with “no memory” that will result in differing efficient frontiers’ evaluations. To address the problem, in this study, we propose an equilibrium efficiency frontier data envelopment analysis (EEFDEA) approach, by which all DMUs with fixed-sum outputs can be evaluated based on a common platform (or equilibrium efficient frontier). The proposed approach can be divided into two stages. Stage 1 constructs a common evaluation platform via two strategies: an extended minimal adjustment strategy and an equilibrium competition strategy. The former ensures that original efficient DMUs are still efficient, guaranteeing the existence of a common evaluation platform. The latter makes all DMUs achieve a common equilibrium efficient frontier. Then, based on the common equilibrium efficient frontier, Stage 2 evaluates all DMUs with their original inputs and outputs. Finally, we illustrate the proposed approach by using two numerical examples.     

Measurement of the worst practice of decision-making units in the presence of non-discretionary factors and imprecise data

The objective of the present paper is to propose a novel pair of data envelopment analysis (DEA) models for measurement of relative efficiencies of decision-making units (DMUs) in the presence of non-discretionary factors and imprecise data. Compared to traditional DEA, the proposed interval DEA approach measures the efficiency of each DMU relative to the inefficiency frontier, also called the input frontier, and is called the worst relative efficiency or pessimistic efficiency. On the other hand, in traditional DEA, the efficiency of each DMU is measured relative to the efficiency frontier and is called the best relative efficiency or optimistic efficiency. The pair of proposed interval DEA models takes into account the crisp, ordinal, and interval data, as well as non-discretionary factors, simultaneously for measurement of relative efficiencies of DMUs. Two numeric examples will be provided to illustrate the applicability of the interval DEA models.     

Risk-Neutral Pricing for Arbitrage Pricing Theory

Journal of Optimization Theory and Applications - We consider infinite-dimensional optimization problems motivated by the financial model called Arbitrage Pricing Theory. Using probabilistic and...     

Projection Pricing

A significant problem in modern finance theory is how to price assets whose payoffs are outside the span of marketed assets. In practice, prices of assets are often assigned by using the capital asset pricing model (CAPM). If the market portfolio is efficient, the price obtained this way is equal to the price of an asset whose payoff, viewed as a vector in a Hilbert space of random variables, is projected orthogonally onto the space of marketed assets. This paper looks at the pricing problem from this projection viewpoint. It is shown that the results of the CAPM formula are duplicated by a formula based on the minimum-norm portfolio, and this pricing formula is valid even in cases when there is no efficient portfolio of risky assets. The relation of the pricing to other aspects of projection are also developed. In particular, a new pricing formula, called the correlation pricing formula, is developed that yields the same price as the CAPM, but is likely to be more accurate and more convenient than the CAPM in some cases.     

二次式变异期权的定价模型

本讨论了一种变异期权-收益结构为二次式的欧式买入期权定价问题。在股票价格服从几何布朗运动的行为模型下，推导出收益结构为二次式的欧式买入期权的定价公式。     

Bus Fares Pricing

Transport pricing at the level of the firm is addressed. The numbers of full fare passengers travelling on three routes of two competing bus companies are analysed using a multiplicative discontinuous price model. Results show that generally only the operator increasing the price suffers a loss of passengers and the price elasticity is a non-linear function of the resulting price difference. The method of analysis and the results have implications for the market modelling of fast moving consumer goods. It is noted that almost no studies of transport pricing at the level of the firm have been carried out previously because of lack of data.     

Structure of multi-criteria decision-making

Multi-criteria decision-making (MCDM) is presented as an eight-stage process of shaping information that satisfies the following criteria. The information should be accessible, differentiable, abstractable, understandable, verifiable, measurable, refinable and usable. For some stages, the decision-advisor should emphasize doing the stage convincingly by carrying out first its technical aspects, then relating to the context of the problem, and finally by taking into account the particular situation of the decision. For others, the decision-advisor should emphasize evincing information from the decision-maker first by relating to the situation of the decision, then seeing it in its context, and finally in its technical aspects. Methods for supporting the first four stages are shown to be personal construct theory for accessing the information, grounded theory for differentiating clusters of constructs, critical realism for abstracting their real meaning, and Nomology to understand how they fit into the criteria tree. An illustration is given.     

美国灾害保险期货期权的保险精算定价

考虑连续情形、几何平均保险期货价格的基础上研究欧式看涨保险期货期权的定价,运用保险精算定价的方法,最终给出了连续情形、几何平均欧式看涨保险期货期权的定价.     

广义交换期权定价

基于风险中性(等价鞅测度)定价理论和经典的Black-Scholes市场环境,我们给出了更一般情形下的欧式交换期权(ExchangeOption)封闭形式的解析定价公式,进而得出了欧式交换期权的价格公式、Black-Scholes期权定价公式.     

产品定价的艺术

产品定价水平的优劣,直接体现着企业管理水平的高低,在一定程度上决定着企业的竞争力与持续发展的潜能。