Training

We offer bespoke training courses on financial modelling, company valuation and advanced data analysis in. As a visiting lecturer at City University, Simon created the highly successful Financial Modelling in Excel course and has taught Financial Modelling & Corporate Finance courses for Abu Dhabi Investment Authority, Citigroup, The Investor Relations Society, Nomura and RBS
Our training courses can be tailored to your needs but have at their core a focus on building models that are simple, robust, flexible and transparent.  These courses tend to be 10-20 hours in length and can be delivered as intensive study our spread out over a number of weekly sessions. We can travel to any UK location to deliver training. We have listed below 3 course outlines below as an illustration of the training we can offer.

Illustrative outline for Financial Modelling Course

1) Using Excel efficiently and modelling best practice

  • Course Structure:
  • Setting Excel Defaults
  • Custom Number Formats
  • Using styles within Excel
  • Keyboard shortcuts
  • Customising the Quick Access Toolbar
  • Modelling Best Practice: Design consistency,
  • Modelling Best Practice keeping unique formulae to a minimum; Limiting formulae complexity;
  • Separating inputs, calculations outputs;
  • Using Range Names

2) Forecasting the Income Statement and Balance Sheet

  • The Structure of the IS
  • Revenue Patterns
  • Different revenue drivers for different industries
  • Cost Behaviour
  • Lookups ( VLOOKUP, INDEX & MATCH)
  • The structure of the balance sheet
  • Forecasting PPE
  • Forecasting Working capital
  • Working Capital Days

3) Forecasting the cash flow and modelling complex debt structures

  • The Structure of the Cashflow
  • The interest calculation and the circularity issue
  • Adding in forecasts for taxes, depreciation & dividends
  • Recap on financial statement forecasting
  • Building in error traps into the model
  • Sumif Formula with an inexact condition
  • Data validation
  • Modelling Complex Debt Structures: The debt hierarchy.
  • Modelling Complex Debt Structures: Creating debt rules
  • Modelling Complex Debt Structures: An LBO model
  • Modelling debt covenants and debt headroom

4) Sensitivity analysis

  • Models, best estimates and the flaw of averages
  • An introduction to sensitivity analysis
  • Different forecast scenarios
  • Using Data Tables
  • Tornado diagrams
  • A brief introduction to Monte Carlo Simulation

5) Advanced modelling techniques

  • Introduction to macros
  • Using the camera tool
  • Macros: Basic Security issues
  • Using Solver & Goal seek
  • Using user forms

Illustrative outline for course in Data Analysis & Visualisation using Microsoft Excel

1) Thinking about data:

  • Classifying data into numerical, ordinal, categorical, date and string data types

2) Sourcing & Extracting Data:

  • Importing data from external databases
  • Web scraping

3) Organising Data:

  • Tables in Excel
  • Range Names
  • Dynamic Range Names

4) Cleansing & Validating Data

  • Using Text Functions to extract information from data strings
  • Cleansing Dates
  • Data Validation

5) Manipulating Data:

  • IF Statements and Boolean alternatives
  • Sumif(s), Countif(s) and Averageif(s) formulae. Creating equivalent formula for
  • Maxif(s)
  • Pivot Tables
  • Power Pivot
  • Lookup Functions
  • Data Sorting & Filtering
  • Data Mining add in
  • What if Functionality (Goal Seek & Data Tables)
  • Using Solver for Optimisation problems
  • Array Formulae

6) Classifying Data:

  • K means clustering in excel to segment data populations

7) Predicting & Testing Data

8) Visualising Data

  • From Florence Nightingale to Steven Few: A very brief history of data visualisation
  • Gestalt Principles of data visualisation
  • Data Visualisation in Excel: Using Excel charting functionality in Excel 2013 and
    earlier versions
  • Using add ins and workaround to tackle visualisations not possible in Excel 2013 and
    earlier versions (waterfall charts, treemaps)
  • New visualisations in Excel 2016

Illustrative outline for course in Valuation Modelling/Corporate Finance

1) Financial modelling best practice:

  • Some basic rules for making your model transparent and user friendly

2) The model starting point: An integrated set of P&L, Balance Sheet & Cash Flow forecasts

  • The Structure of the P&L
  • Revenue Patterns
  • Cost Behaviour
  • The structure of the balance sheet
  • Forecasting PPE
  • Forecasting Working capital
  • Working Capital Days
  • The Structure of the Cashflow
  • The interest calculation and the circularity issue
  • Adding in forecasts for taxes, depreciation & dividends
  • Recap on financial statement forecasting
  • Building in error traps into the model

3) An overview of valuation methodologies: Absolute & Relative approaches to valuation

4) Absolute valuation methodologies – The discounted cash flow:

  • The constituents of an enterprise discounted free cash flow: What is included what is not
  • Coming up with an appropriate discount rate
  • Sense checking the numbers: What does the cash flow tell us about predicted returns on capital? Is this realistic?
  • Choosing a terminal growth rate

5) Relative Valuation approaches:

  • An overview of possible relative valuation metrics to use (Sales based, cash flow based, profit based, asset based)
  • What metric is most appropriate for your business
  • What timeframe to look at
  • What reference points in terms of companies and indices to use in relative valuation
  • When to use asset based multiples