Advanced Financial Modeling, Forecasting & Analysis
Details
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Designing and aligning models with their decision-support role
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Techniques to conduct and automate sensitivity and scenario analysis
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Advanced Excel calculations
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Using Lookup and other functions to build dynamic and highly flexible models
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Best practices in function choice and their parameters; functions to avoid, functions to use only in specific circumstances; criteria for function selection and use
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Cleaning, analyzing and querying data sets using a variety of approaches, including filters, Pivot Tables and database functions
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Automating activities and working more effectively using VBA macros e.g. manipulating data sets, running sensitivities and resolving circularities
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Designing models with the right features, structure and layout; key questions to ask, tools and techniques to apply; tools to consolidate multi-data-set models
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Review of modelling issues in many core applications: cash flow valuation, financial statement modelling, project finance, Monte Carlo simulation, options and deal options modelling
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Around 50 hands-on exercises and demonstrated completed models
Outline
- The modelling process
- Capturing decision-makers’ requirements and objectives
- Mapping requirements into model design
- Overview of best practice principles
- Building complex formulae through sensitivity techniques
- Running automated sensitivity analysis
- Scenario analysis and optimisation techniques; creating scenarios, using GoalSeek and Solver; introduction to simulation techniques
- Creating and testing complex formulae using sensitivity techniques
- Running automatic sensitivity analysis on one or two input variables
- Conducting break-even analysis
- Running scenarios and variance analysis
- Optimizing portfolio composition, and other uses of optimisation methods
- Logical and conditional calculations in Excel
- Use of array formulae and array functions
- Statistical functions
- Mathematical and financial functions
- Selected issues and best practices in function and parameter choice
- Use of functions such as SUMIFS, SUBTOTAL, AGGREGATE in various contexts
- Use of array functions in cost allocation, depreciation calculations, finding first matching item in a conditional list
- Calculation of core statistical measures; regression and multiple regression; scatter plots, linear forecasting
- Calculation of confidence intervals for average and volatility estimates (including applications to calculating the cost of capital, measuring oil price volatility etc.)
- Calculations of correlations and rank correlations
- Non-linear curve fitting using optimisation
Introduction and Uses in a Variety of Modelling Applications
- Overview of Information, Date and Text functions
- Overview of Lookup functions
- Best practices in the selection of functions (incl. why to not use VLOOKUP etc.).
- Use of flag variables
- Finding the occurrence of an event
- Dealing with multi-currency datasets
- Consolidating, reversing, transposing data sets
- Creating time-shifting capabilities e.g. delaying planned production start
- Creating flexible, variable-sized and dynamic ranges for use within functions
- Creating models in which new data sets can be added or data sets can be deleted quickly and without major re-work; working flexibly with multi-sheet models
- Creating models which update as actuals are input
- Creating formula that handle acceptable errors or exceptions
- Detecting input data errors
- Creating dynamic labels and charts; updating cell labels and graph legends and titles
- Creating unique identifiers in order to match items in different dataset
- Planning the date of maintenance activities (e.g. last Friday in each month)
Introduction
- Excel Tables: definitions, benefits, advantages and limitations
- Database functions
- PivotTables and PivotTable analysis
- Comparison of possible approaches e.g. finding the conditional maximum using Excel arithmetic functions, database functions, or array functions
- Splitting data, extracting data, separating fields using Text-to-Columns menu (e.g. from internet download)
- Cleaning data and finding errors using filters, advanced filters, conditional formatting, find/replace etc.; Inspecting for integrity, uniqueness and duplicates
- Finding unique values and unique combinations
- Checking for data consistency with information and logical functions
- Splitting text and numerical fields using functions
- Combining databases by matching fields and creation of keys (after manipulation of field data)
- Summarizing daily production by month and year; report creation; calculation of days per model period
- (Demos) More complex applications, requiring integrated use of multiple advanced functions
- Automatic sorting of data sets
- Using database functions to run multi-criteria (or changing criteria) queries of databases
- Use of PivotTable filters, slicers, and time-line slicers
Overview and Key Practical aspects of VBA and its Functionality
- Main uses and benefits
- Topics in syntax and controlling code execution: Use of With, Set, and conditional statements
- Debugging tools: Use of break points; running parts of code; stepping over other called routines etc.
- Best practices: Comments, indenting and formatting, data types, variable declaration etc.
- Introduction object orientation
- Simple recording example (e.g. code to copy ranges)
- Running code and stepping through line-by-line
- Adapting recorded code through direct writing of code (looping structures, named ranges, referring to ranges)
- Comparing copy/paste with assignment statements
- Creation of buttons to run code, and of simple Input and Message Boxes
- Using macros to run sensitivity and scenario analysis
- Recording and adapting the running of GoalSeek for breakeven analysis
- Running multiple database queries using a macro
- Demo of other applications: (e.g. multiple database queries, reversing items in a data sets automatic deletion of unwanted data, repeated extraction of specific elements, consolidation of multiple data sets into one)
Modelling Structures and Best Practices: Further Discussion
- Sensitivity and flexibility requirements; balancing flexibility with complexity; ensuring transparency
- Optimal model structures. The selection of data architectures; modular versus global data architectures, optimizing layout (e.g. generic structure for input and calculation areas, and their respective benefits)
- Formulae-dominated versus data-dominated modelling approaches
- Tools to consolidate multi-sheet models
- Modelling with circular references: Their nature, type, ways how to deal with them
- Other best practices (e.g. use of named ranges, multi-sheet models, linked workbooks, formatting, conditional and custom formatting, auditing, checking for integrity and errors etc.); Selected short-cuts
- Economic principles: Time value of money, net present value, internal rate of return, sunk cost, cost of capital
- Cash flow valuation: Key modelling issues, including calculation of beta and confidence intervals
- Financial statement models: Selected key modelling issues, including tips and techniques to ensure integrity of model (balance sheet that balances), options to deal with circular references, etc.
- Project finance (selected areas: calculations of core coverage ratios, debt capacities, use of circular references)
- Simulation modelling, real options modelling and valuation
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Sensitivity analysis of NPV and IRR calculations to project delays
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Modelling debt repayment profiles; use of corkscrew structures
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Using VBA to achieve circular logic without circular formulae
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Consolidation of multiple data sets using Excel; demo on possible approaches using VBA macros
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Using VBA for simulation modelling; demo of Excel add-in to facilitate more complex models
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Other selected modelling topics, and demo of other simple completed models
Speaker/s
Special Offer
Early bird: Less SG$100 for registration on or before 20th April 2016
Group discount: 10% discount for 3 or more participants
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