Monte Carlo Methods for Quantitative Finance - PIMS Industrial Short Course
- Start Date: 02/22/2012
- End Date: 02/24/2012
Tony Ware is an Assoc. Prof. in the Dept of Mathematics and Statistics at the University of Calgary, where he is the Director of the Mathematical and Computational Finance Laboratory. He works with energy companies including Nexen, TransAlta, Enmax, Louis Dreyfus Energy and Direct Energy.
Simon Fraser University, Harbour Center Campus, Vancouver
Monte Carlo Methods for Quantitative Finance
A course for risk managers, quantitative analysts and others who want to learn how to make use of Monte Carlo and related techniques.
Learn how to:
• use Monte Carlo methods for accurate option pricing, hedging and risk management.
• understand what the values produced by Monte Carlo computations mean and how much confidence should be placed in them in practice.
• increase the efficiency of their Monte Carlo applications through variance reduction techniques and the use of .quasi-Monte Carlo methods.
• incorporate the latest developments into their current practice.
The basic timeline for each day is as follows:
09:00-10:15 Session 1
10.45-12:00 Session 2
13:00-14:15 Session 3
14:45-16:00 Session 4
DAY 1 (Room 1315 Scotiabank lecture room)
1.1 Introduction and overview
Basic ideas and history of Monte Carlo applications to option pricing and risk management
1.2 Monte Carlo fundamentals
Randomness, reliability and efficiency working in high dimensions: multi-asset and path-wise simulations variance reduction: antithetic variates, control variates, stratification, importance sampling
1.3 Quasi-Monte Carlo methods
Comparison with traditional Monte Carlo low-discrepancy sequences: typical problems and how to avoid them randomized quasi-Monte Carlo
DAY 2 (1315 Scotiabank lecture room)
2.1 Computing sensitivities
Finite differences pathwise differentiation the `smoking adjoints' approach of Giles and Glasserman the likelihood ratio method
2.2 American options
Lower bound methods (Longstaff-Schwartz) dual methods for upper bounds applications to swing options and storage contracts
2.3 Other price processes
Stochastic volatility, jump-diffusion and other processes
2.4 Risk management applications
VaR and other risk measures, variance reduction using delta-gamma
DAY 3 (Room 1330 IBM Computer lab)
3.1 Hands-on session
Software will be provided to enable people to experiment with many of the concepts from Day 1 and Day 2 and reinforce what has been learned
3.2 Case studies
We will work with one or more case studies, again using software provided to course participants.
Location: SFU Harbour Centre, Vancouver BC
515 West Hastings Street,
Canada. V6B 5K3
Registration fee: $1,344 (HST Included)
Accomodations will be the responsibility of the participants. Downtown Vancouver has a large number of hotels to fit every budget and most are within walking distance to SFU Harbour Centre.
Should you have any specific questions regarding this event, please contact Tony Ware at firstname.lastname@example.org.