FX fair value model using BEER approach

  • A stable and robust model to estimate the fair value of FX pairs

  • Easy access to experts at a fraction of the global cost


Client

  • A leading European buy-side bank wanted to develop a fair value model for major FX pairs to check if any currency pair was undervalued or overvalued relative to its long-run fair value
  • The bank also wanted to develop a quantitative method to predict the time it would take for the actual FX price to converge with its fair value

Our solution

  • Preparation
    • Data collection from public sources and other data subscriptions
    • Data cleaning for model input
    • Data manipulation and transformation for model development
    • Data maintenance for future iterations and model validation
  • Model fitting
    • Use of Behavioural Equilibrium Exchange Rate (BEER) approach.
    • Identification of four significant predictors for FX rates.
    • Cross-section OLS regression for individual FX pairs.
    • Panel regression for G10 currencies.
    • Use of Vector Error Correction Model (VECM) to calculate speed of convergence to fair value and provide forecasts of fair value FX rates
    • Model development using R and Python
  • Results interpretation and publishing
    • Helped client publish the findings of the model in research papers and other publications.
    • Maintained the model to keep it up to date and in line with econometric assumptions.
    • Tested tweaks in the model to improve forecasting accuracy.

Key Benefits

  • A stable and robust model to estimate the fair value of FX pairs and provide direction on FX price movements in the medium to longer term.
  • Easy access to experts at a fraction of the global cost.
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