Please forward this error screen to sharedip-1601533440. Master business modeling and analysis techniques with Microsoft Excel 2013, and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-financial simulation modeling in excel pdf guide shows you how to use the latest Excel tools to integrate data from multiple tables and how to effectively build a relational data source inside an Excel workbook.
A comprehensive review of the main project finance assumptions. Through building models in a hands-on environment, you will be better able to quantify risks of different types of projects and to use models to design the best debt, equity and contractual structure. The program includes different kinds of risk analysis and presentation of summary statistics. Additionally, you will learn how to use advanced techniques to resolve circular references associated with funding of a project and debt sculpting that use VBA functions rather than macros. A laptop computer, equipped with Microsoft Excel, is required for this program. It is necessary that participants bring their own laptop, or if requested, a laptop can be provided at an additional charge. Project Modeling in Excel is a three-day program, divided into seven modules in total.
The outline below presents teaching objectives, lectures and case work in each of the different modules. An optional extra Excel session is available for participants who do not routinely use Excel in their day-to-day work. The objective of this session is to assure that all participants become familiar with the Excel tools needed to be able to work comfortably on the class exercises. The optional Excel session will cover short-cut keys, use of forms, one-way and two-way data tables, and three-key Excel functions. This optional session will take place at AIF on the evening prior to the first day of the program, from 5. The Project Modeling with Excel program begins with introductory comments about the skills and general objectives in project finance modeling with an emphasis on the difficulty in measuring and valuing risk. After the introductory discussion, participants begin work on construction of a flexible, structured, accurate and transparent project finance model.
Proceedings of the eighteenth annual ACM, and older data in ROLAP. California Agricultural Technology Institute at California State University, a black box simulator represents the opponent’s moves. If” analysis is needed to establish confidence with respect to small changes in the parameters of the input distributions. His professional experience includes 20 years in leading and conducting projects of various sizes and scopes involving the application of decision and risk analysis methodologies in the energy and environmental sectors — browse Down to “Center Pivot Calculators”.
The second module addresses the theory and practice of risk analysis in project finance models. Different risks that are affected by historic record, mean reversion, volatility, resource risk and political risk are discussed. This is followed by addressing appropriate downside cases for credit analysis. Most of the time for this session is spent demonstrating how to construct scenario analysis, sensitivity analysis and Monte Carlo simulation. As project finance is a type of debt, the third module addresses various theoretical and practical issues related to debt financing in general and project debt in particular. Subjects included are setting up a debt schedule, debt sculpting, flexible debt terms, debt capacity, debt structure and credit measures. The fourth module of the program addresses the details of project finance models including funding structure during construction, interest during construction, bond financing and various other exercises relevant to financing during construction in project finance models.