Investment decisions and sensitivity analysis: NPV-consistency of rates of return

被引:57
作者
Marchioni, Andrea [1 ]
Magni, Carlo Alberto [2 ]
机构
[1] Univ Modena & Reggio Emilia, Dept Econ Marco Biagi, Viale Berengario 51, I-41121 Modena, Italy
[2] Univ Modena & Reggio Emilia, CEFIN Ctr Res Banking & Finance, Dept Econ Marco Biagi, Viale Berengario 51, I-41121 Modena, Italy
关键词
Finance; Sensitivity analysis; Investment decisions; NPV; Return On Investment; NONNEGATIVE INTERNAL RATE; PLANT LOCATION PROBLEM; NET PRESENT VALUE; OPERATIONAL-RESEARCH; SUFFICIENT CONDITION; CASH FLOWS; PROJECT; MODELS; CRITERIA; UNCERTAINTY;
D O I
10.1016/j.ejor.2018.01.007
中图分类号
C93 [管理学];
学科分类号
120117 [社会管理工程];
摘要
Investment decisions may be evaluated via several different metrics/criteria, which are functions of a vector of value drivers. The economic significance and the reliability of a metric depend on its compatibility with the Net Present Value (NPV). Traditionally, a metric is said to be NPV-consistent if it is coherent with NPV in signaling value creation. This paper makes use of Sensitivity Analysis (SA) for measuring coherence between rates of return and NPV. In particular, it introduces a new, stronger definition of NPV-consistency that takes into account the influence of value drivers on the metric output. A metric is strongly NPV-consistent if it signals value creation and the ranking of the value drivers in terms of impact on the output is the same as that provided by the NPV. The degree of (in)coherence is calculated with Spearman (1904) correlation coefficient and Iman and Conover (1987) top-down coefficient. We focus on the class of AIRRs (Magni 2010, 2013) and show that the average Return On Investment (ROI) enjoys strong NPV-consistency under several (possibly all) methods of Sensitivity Analysis. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:361 / 372
页数:12
相关论文
共 84 条
[1]
[2]
[Anonymous], 2008, GLOBAL SENSITIVITY A
[3]
[Anonymous], 2007, Sensitivity analysis in practice: A guide to assessing scientific models (Reprinted)
[4]
OPERATIONAL-RESEARCH AND FINANCIAL MANAGEMENT [J].
ASHFORD, RW ;
BERRY, RH ;
DYSON, RG .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1988, 36 (02) :143-152
[5]
Using neural network rule extraction and decision tables for credit-risk evaluation [J].
Baesens, B ;
Setiono, R ;
Mues, C ;
Vanthienen, J .
MANAGEMENT SCIENCE, 2003, 49 (03) :312-329
[6]
Baroum S. M., 1996, Journal of Operations Management, V14, P209, DOI 10.1016/0272-6963(96)00005-8
[7]
Technical Note: Economic Rates of Return and Investment Analysis [J].
Barry, Peter J. ;
Robison, Lindon J. .
ENGINEERING ECONOMIST, 2014, 59 (03) :231-236
[8]
Ben-Horin M, 2017, Q REV ECON FINANC, V66, P108, DOI 10.1016/j.qref.2017.01.004
[9]
A SIMPLIFICATION AND AN EXTENSION OF THE BERNHARD-DEFARO SUFFICIENT CONDITION FOR A UNIQUE NONNEGATIVE INTERNAL RATE OF RETURN [J].
BERNHARD, RH .
JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS, 1980, 15 (01) :201-209
[10]
Applying operations research techniques to financial markets [J].
Board, J ;
Sutcliffe, C ;
Ziemba, WT .
INTERFACES, 2003, 33 (02) :12-24