Recent advances in Financial Modelling for Risk Management

D. Hainaut, PhD

Description

This training focuses on recent developments in quantitative finance applied to risk management.

The first part covers regime switching models for stock prices in which parameters are modulated by a hidden process, representative of the economic conjuncture.

The second part is dedicated to self-excited processes that replicate the spillover of shocks in stock markets.

The third part is devoted to the Bayesian calibration of processes with Monte-Carlo Markov chain methods. The last part focuses on the Heston model for stock price and the filtering of the stochastic volatility.

For all models, we cover the option pricing by Fast Fourier transform and their econometric estimation.

The R code of illustrations will be provided to participants.

Program

  1. Economic cycles models
    • A switching jump-diffusion
    • Options pricing
    • Calibration and Hamilton’s filtering
    • A fractal-switching model
  2. Spillover in stock markets
    • Self-excited jumps in stocks market (Hawkes)
    • Calibration by the “peaks of threshold” method
    • Sampling of self-excited models
    • Properties of Self-excited processes
    • Option pricing

  3. Estimation by Markov Chain Monte-Carlo (MCMC) & stochastic volatility models

    • Metropolis-Hasting algorithm (MCMC)
    • Application to switching regime models
    • The Heston model
    • Particle filtering of the hidden volatility
    • Econometric estimation with Particle MCMC

Speaker

Donatien Hainaut

Donatien Hainaut

Scientific Advisor, Detralytics
Professor, UCLouvain

Date : On-Demand

Duration : 9h

Accreditation : 9CPD | 54PPC

Industry : Bank, insurance

Requirements : PC with dedicated R packages

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Acquired skills

At the end of this training, participants will be able

  • To design models for stock prices with various features including economic cycles, spillover of jumps or stochastic volatility.
  • To implement Fast Fourier transform (FFT) methods for pricing options in these frameworks
  • To estimate models from time series with Bayesian techniques such as MCMC or Particle MCMC

About our Speakers

Donatien Hainaut

Donatien Hainaut is a Scientific Advisor at Detralytics and a professor at UCLouvain (Belgium), where he serves as the Director of the Master’s program in Data Science with a statistical orientation. Prior to this, he held several academic positions, including Associate Professor at Rennes School of Business and ENSAE in Paris. He also has extensive industry experience, having worked as a Risk Officer, Quantitative Analyst, and ALM Officer.

Donatien is a Qualified Actuary and holds a PhD in the field of Asset and Liability Management. His current research focuses on contagion mechanisms in stochastic processes and the applications of neural networks in insurance.

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