Advanced Equity Derivatives and Structured Products Modelling

19 & 20 November 2008, London

An intensive two-day course exploring current industry best practice and emerging trends in equity derivatives and structured products. Pricing, trading and structuring principles are illustrated with many practical examples. The course emphasizes Model Agnostic Financial Engineering whereby traders and analysts can define the model freely and semi- parametrically as a general regime switching dynamics without affecting performance. A main focus of the course is to review the engineering principles behind the design of pricing and calibration engines and emphasizes GPU based architectures. Source code snapshots are handed out and discussed in class.

This is an intermediate to advanced level course aimed at:

• Traders wanting to build realistic pricing models embedding their views and as much useful information as they deem fit
• Analysts and developers building trading system
• Structurers wanting powerful analytics to understand and design effective payoff structures

Main topics covered during this training

• In depth analysis of structuring principles and trading strategies
• Overview of market products from volatility derivatives to long-dated equity structures and basket trades
• Insight into standard market models: local volatility, Heston, jump models and regime switching models
• Numerical methods and calibration methodologies: lattice models, Monte Carlo methods, optimization technique
• Deployment design patterns on CPUs and GPU clusters
• Practical PC-based workshops and worked examples (source code samples in ANSI C will be provided to delegates)

Course level: Intermediate to Advanced

Since the course emphasizes both model building for structuring and trading purposes and system engineering, we expect delegates of various backgrounds.

A trader and structure without quant background will learn how to build regime switching models embedding monetary policy projections and subtle features of the foreign exchange process. He will learn also how this impacts structuring and risk management. An understanding of the system architecture issues and the code discussed in class is not strictly necessary, especially since the lecture will be recorded and the trader or structurer will be able to pass the recording along to more technical members of his team.

A quantitative analyst who intends to follow the technical discussion of the numerical analysis, code and system issues needs to have an average education in quantitative finance, at least MSc level.

Teaching method

This is a highly practical course with many PC-based exercises that will help you to immediately apply theory into practice.

You will also benefit from comprehensive take-away course documentation

In order to help us establish your individual and business concerns, you will be asked to fill a pre-course questionnaire

Because of the nature of the course the number of places is limited and will be filled on fist come, first accepted basis. We advise to book in advance in order to avoid disappointment.

Who should attend?

From Financial Institutions, Investment Banks, Hedge Funds and Pension Funds, Consultancy Groups and Solution Providers Heads, Managers, Advisors and Market Players in:

• Trading: Structured Products and Exotic Derivatives
• Trading and Markets: Equity, Fixed Income and Currencies
• Portfolio Management and Strategy
• Quantitative Analysis and Research
• Derivatives Research
• Structuring
• Risk Management, Risk Analysis and Control
• Data Monitoring and Data Processing

COURSE DIRECTOR

Prof. Claudio Albanese

Claudio Albanese currently works as independent consultant and is Visiting Professor of Mathematical Finance at King’s College London. His academic background includes a PhD in Physics from ETH Zurich and a number of academic positions up to the rank of full professor at several universities including NYU, Princeton, University of Toronto and Imperial College London. Claudio worked as a consultant and trained at several investment banks and hedge funds including Mitsubishi Securities, Merrill Lynch, Bloomberg, CDC-Naxis, Carador, Shinsei, ABN AMRO, BBVA, ZKB and others.

Claudio's main focus is in building engineering frameworks for derivative pricing which are flexible enough to accommodate regime switching models. These engines are very efficient and accurate, especially if implemented by leveraging on GPU technology.