Building sensitive forecast models and common forecast assumptions

Financial Forecasting in Python

Victoria Clark

CGMA Financial Analyst

Considerations when forecasting

  • Correctly interpret data
  • Account for changes in data
  • Account for interlinked variables
    • Dependencies
    • Sensitivities
  • Set assumptions
Financial Forecasting in Python

Assumptions

  • "Best guess" based on data available
  • Set at the beginning of a forecast process
  • Used to drive forecasting
  • Can be directly controlled
  • Can be indirectly controlled
    • Outside control of company

black swan

Financial Forecasting in Python

Different types of Assumptions

  • Probability
    • Weighted
  • Market sentiment
  • Demand and supply

Question Mark

Financial Forecasting in Python

Working with pairs in Python

Using Combined Lists

Outcome Probability (%)
1 30
2 20
3 50

 

outcome_probability = ['1|0.3', '2|0.2', '3|0.5']
Financial Forecasting in Python

Define a Python Function

Define a dependency or sensitivity formula

  • Prevent duplication of work and errors
def assumption1()
  if marketsentiment = 0.3:
    sales + sales*0.1
  else 
    sales
Financial Forecasting in Python

Let's practice!

Financial Forecasting in Python

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