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Regular version of the site
Master 2022/2023

Financial Modelling

Type: Elective course (Finance)
Area of studies: Finance and Credit
Delivered by: Department of Finance
When: 1 year, 4 module
Mode of studies: distance learning
Online hours: 20
Open to: students of one campus
Master’s programme: Finance
Language: English
ECTS credits: 3
Contact hours: 24

Course Syllabus

Abstract

The course aims at understanding of financial modelling principles and their implementation for business projects and capital investment decision making. It is based in the online course, studying which, the students may create their financial models and discuss them. The course improves students’ competences in using Excel and Power BI for data proceeding and visualisation
Learning Objectives

Learning Objectives

  • The purpose of the course is to strengthen the skills of building financial models and using business intelligence methods to assess economic results and make rational decisions.
Expected Learning Outcomes

Expected Learning Outcomes

  • The ability to use information technology to create financial business models.
  • Practical skills in building financial models with Excel
  • Practical skills in building information models with Power BI desktop
  • Experience in scenario analysis ro support decision modeling in Power BI
Course Contents

Course Contents

  • Sales planning methods and models. Demand forecastinf for sales planing.
  • Products plan correction in case of demand changes. Sensitivity analsysis of the plan to various parameters.
  • Logistics and distrubution models. Price floor and pricing policy.
  • What-if analysis in financial modeling. Decision making based on scenarios.
Assessment Elements

Assessment Elements

  • non-blocking Demand forecasting
  • non-blocking Sensitivity analysis
  • non-blocking Distribution model
  • non-blocking Scenario modeling
Interim Assessment

Interim Assessment

  • 2022/2023 4th module
    0.2 * Sensitivity analysis + 0.2 * Demand forecasting + 0.3 * Scenario modeling + 0.3 * Distribution model
Bibliography

Bibliography

Recommended Core Bibliography

  • Benninga, S. (2014). Financial Modeling (Vol. Fourth edition). Cambridge, Massachusetts: The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1089520
  • Clark, D. (2017). Beginning Power BI : A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop (Vol. Second edition). Camp Hill, Pennsylvania: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1478775
  • Logistics and supply chain management, Christopher, M., 2016
  • Principles of financial with EXCEL, Benninga, S., 2006
  • Seamark, P. (2018). Beginning DAX with Power BI : The SQL Pro’s Guide to Better Business Intelligence. [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1743806
  • The definitive guide to DAX : business intelligence for Microsoft Power BI, SQL server analysis services, and Excel, Russo, M., 2020

Recommended Additional Bibliography

  • Benninga, S. (2010). Principles of Finance with Excel. Oxford University Press.
  • Fundamentals of financial management, Brigham, E. F., 2007
  • Greg Deckler. (2019). Learn Power BI : A Beginner’s Guide to Developing Interactive Business Intelligence Solutions Using Microsoft Power BI. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2252653
  • M.A. Mian. (2017). Tips & Tricks for Excel-Based Financial Modeling, Volume I : A Must for Engineers & Financial Analysts. New York: Business Expert Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1568559
  • Podskrebko Oleksandr S. (2019). Developing the Structure of Decision-Making Support System for Management of the Production Logistics of an Industrial Enterprise. Bìznes Inform, (495), 139. https://doi.org/10.32983/2222-4459-2019-4-139-146
  • Russo, M., & Ferrari, A. (2015). The Definitive Guide to DAX : Business Intelligence with Microsoft Excel, SQL Server Analysis Services, and Power BI. Redmond, Washington: Microsoft Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1601522