MoneyScience Financial Training
Course Length: 2 Days | Cost: £2100
In the seminar we discuss the application of the Monte Carlo method to Quantitative Finance. In particular we focus on pricing derivatives. We investigate how several methods to simulate sample paths of risky assets, tune the efficiency of the method and finally solve advanced problems like computing hedge sensitivities and early exercise features.
We furthermore show how to implement it in an object oriented fashion using VBA. Choosing this language is motivated by the fact that Excel is the most widespread application. In addition we give hints how to set up the method in C++ and matlab.
It is essential to cover the implementation to fully grasp the implications and benefits of the method for derivatives pricing. Starting from a simple Black / Scholes / Merton dynamic and simple option payoffs, we show how to extend the application to cover complex models and payoffs. For example we show the implementation of the Heston model together with the QE scheme and apply it to the pricing of path-dependent options but also jump diffusion processes, Lévy processes or bridge simulation.
The source code will be made available such that further practice at your own location is possible. The code could also serve as a starting point for a proprietary application
Course Overview
- Applications of Monte Carlo Methods in Finance and Mathematical Background Derivatives Pricing
- Random Number Generation
- Path Generation – One Dimensional Cases
- Path Generation – Multi-Dimensional Cases
- Stochastic Volatility Models
- Variance Reduction Methods
- Advanced Monte Carlo I - Calculation of Sensitivities
- Advanced Monte Carlo II – Early Exercise Features
What do you learn?
- Generating random variables due to a given distribution
- Setting up sample paths using incremental and bridge techniques
- Using Sobol numbers for quasi Monte Carlo simulation
- Handling multi-dimensional models
- Using Monte Carlo simulation for processes apart from the standard Brownian Motion
- Applying Variance Reduction Methods
- Calculating Greeks using Monte Carlo simulation
- Pricing early exercise features using simulation
Who should attend?
This course has been developed for financial professionals who want to use simulation methods or gain further insights into the methodology in terms of effectiveness and further applicapilty. The course introduces and elaborates on how to apply Monte Carlo methods, creating a flexible application in VBA to illustrate the methods.
The course is also of interest for risk managers, IT professionals, quants, consultants and backoffice staff interested in modern techniques for Quantitative Finance.
It is assumed that the attendees have some working knowledge of VBA to follow the examples.
Course Tutor
JOERG KIENITZ is the head of Quantitative Analysis at Deutsche Postbank AG. He is primarily involved in the developing and implementation of models for pricing of complex derivatives structures and for asset allocation. He is also lecturing at university level, Universities of Oxford, Bonn and Duisburg on advanced financial modelling and gives courses on ‘Applications of Monte Carlo Methods in Finance’ and on other financial topics including Lévy processes and interest rate models as well as lecturing on finance conferences like RISK Europe. Joerg holds a Ph.D. in stochastic analysis and probability theory. Jörg authored several papers on mathematical and computational finance. He also is the co - author of the book “Monte Carlo Object Oriented Frameworks in C++” (together with Daniel J. Duffy) which will be published by Wiley in September 2009.
All delegates will receive a copy of Jörg Kienitz's book with Daniel Duffy:
Monte Carlo Frameworks: Building Customisable High-performance C++ Applications
