spreadsheet models
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2021 ◽  
Author(s):  
Songzhi Lin

Portfolio efficiency and suitability are two important goals in the asset allocation processing involving a financial advisor and clients. The Analytic Hierarchy Process (AHP) technique is employed as a framework to address an investor's multiple investment objectives. Questionnaires, GAMS (General Algebraic Modelling System) programs and spreadsheet models are developed to facilitate the communications between the financial advisor and investor.


2021 ◽  
Author(s):  
Songzhi Lin

Portfolio efficiency and suitability are two important goals in the asset allocation processing involving a financial advisor and clients. The Analytic Hierarchy Process (AHP) technique is employed as a framework to address an investor's multiple investment objectives. Questionnaires, GAMS (General Algebraic Modelling System) programs and spreadsheet models are developed to facilitate the communications between the financial advisor and investor.


PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0194916
Author(s):  
Stephanie L. Bailey ◽  
Rose S. Bono ◽  
Denis Nash ◽  
April D. Kimmel

2017 ◽  
Vol 47 (3) ◽  
pp. 260-269 ◽  
Author(s):  
Larry J. LeBlanc ◽  
Michael R. Bartolacci ◽  
Thomas A. Grossman

Author(s):  
Daniel Diermeier ◽  
Evan Meagher

In 2008 San Francisco International Airport (known by its three-letter airport code, SFO) had announced a $383 million plan to renovate and reopen Terminal 2. Assistant deputy director of aviation security Kim Dickie and her team had selected Quantum Secure's SAFE software suite as the new Terminal 2 credentialing system, but she needed to develop a business case quickly that would convince senior management to give the green light to fund the purchase. The case describes a scenario that occurs frequently in the real world, in which a decision offers some real but qualitative value in ways that are difficult or impossible to quantify. The discussion and analysis gives students the opportunity to consider the factors that will drive the internal rate of return (IRR), net present value (NPV), and discounted payback period calculations without constructing comprehensive spreadsheet models. Analyzing the case suggests the limits of such approaches in cases where perceived value is difficult to quantify. The case prepares students to evaluate and justify purchasing requests when interacting with financial gatekeepers such as CFOs and CEOs by introducing a framework to analyze the quantifiable benefits of a capital expenditure while keeping in mind important intangible benefits.After analyzing the case, students should be able to: Understand how return on investment (ROI) calculations work, with an emphasis on identifying incremental effects Decide how to use results from similar entities making similar purchases to estimate the incremental benefit of a proposed solution Identify and use the best data available in making assumptions Justify the validity of benefits that are difficult to quantify in conjunction with the presentation of a traditional ROI analysis


2016 ◽  
Vol 118 ◽  
pp. 234-250 ◽  
Author(s):  
Jácome Cunha ◽  
João Paulo Fernandes ◽  
Pedro Martins ◽  
Jorge Mendes ◽  
Rui Pereira ◽  
...  
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2015 ◽  
Vol 27 (1) ◽  
pp. 33-56 ◽  
Author(s):  
Linda Leon ◽  
Zbigniew H. Przasnyski ◽  
Kala Chand Seal

Most organizations use large and complex spreadsheets that are embedded in their mission-critical processes and are used for decision-making. Identification of the various types of errors that can be present in these spreadsheets is, therefore, an important first step to creating controls that organizations can use to govern their spreadsheets. While a considerable amount of research on quantitative error taxonomies exists, there is comparatively little research concerning qualitative error taxonomies. In this paper, we propose a taxonomy for categorizing qualitative errors in spreadsheet models that offers an exploratory framework for evaluating the quality of a spreadsheet model before it is released for use by others in the organization. The classification was developed based on types of qualitative errors identified in the literature and errors committed by end-users in developing a spreadsheet model for Panko's (1996) “Wall Problem.” A principal component analysis of the errors reveals four logical groupings thereby creating four categories of qualitative errors. The usability and limitations of the proposed taxonomy and areas for future research are discussed.


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