Modelling, estimation and simulation

For risk analysis and investment management

Financial mathematics, econometrics and derivatives pricing, all in a one-day, intensive and practical workshop in the centre of London.


Have you ever had to quickly analyse a bunch of financial time series on a spreadsheet? Equity or fx returns, or bond yields, or CDS or interest rate swap spreads, or various combinations of those? Did you do it in a "fairly simple way"? Having attended our workshop, you will be sure you are doing it the correct way . Our concise and practical course will help you to see the big (though detailed) picture of the subject and to learn practical skills and tricks to get better at your game.


We will warm up with intuitive exercises involving basic probabilistic modelling and statistical inference. This will lead us to a framework of joint dynamic modelling of fairly generic families of time series. We will apply it to financial time series associated with most asset classes and derivatives. Having learnt how to identify and estimate the model, we will unleash the fury of Monte Carlos to tackle dynamic investment strategy analysis or Expected Shortfall/VAR or credit exposure.


Aimed at entry to mid-level quants, risk and portfolio managers, the course is a mixture of short segments interleaved with examples and exercises. Active participation and questioning are welcome. Most of the practical tasks will be entirely spreadsheet/formula based; VBA usage will be minimal. However, prior exposure to financial markets, including derivatives, and understanding of stochastic methods is essential. Your first probability or financial markets course it probably should not be.



  1. Early morning session, 9:00 - 10:30
  2. Probabilistic and statistical foundations
    • Random variables, sampling, sample statistics
    • Hypothesis testing, identification of distributions
    • Statistical inference, likelihood
    • Point estimates, confidence intervals
    • Dependency, linear dependency, correlations
    • PCA and factor models
  3. Coffee break
  4. Late morning session, 10:40 – 12:10
  5. Time series modelling
    • Samples vs time series
    • Autocorrelation, importance of dynamic models
    • ARMA models vs Random walk, estimation
    • Model specification, Box-Jenkins methodology
    • Residual and volatility modelling, xARCH
    • Vector autoregression (VAR) models
  6. Lunch. Optional buffet at the hotel can be prebooked.
  1. Early afternoon session, 13:30 - 15:00
  2. Modelling and estimation
    • P vs Q modelling
    • Necessity of a dynamic model
    • Joint modelling of underlyings and derivatives under P
    • Models for equity-like products and FX
    • Models for yields and swaps
    • Models for volatility surfaces
  3. Coffee break
  4. Late afternoon session, 15:15 – 16:45
  5. Monte Carlo methods
    • Historical vs parametric Monte Carlo
    • Hybrid Monte Carlo
    • VAR/ES
    • Counterparty exposure
    • Model risk
    • Q&A (time permitting)