Seminar: Asset Allocation with MATLAB

	Date	11 March 2010
	Venue	Garden Court Eastern Boulevard
	Time	08:30 - 12:30
	The task of asset allocation combines familiar concepts of asset pricing, risk measurement, and portfolio optimization to develop tradable portfolios of assets that have low turnover, stable moments, and desirable return and risk characteristics. This seminar introduces financial professionals to MATLAB and the Financial Toolbox using examples based in asset allocation.

 

This introductory seminar will show you how you can use MATLAB and the Financial Toolbox to analyse and create tradable portfolios. During this seminar, we will demonstrate MATLAB's data input capabilities to acquire data from multiple data sources such as databases, datafeeds and spreadsheets. A simple portfolio will be constructed using the available functionality. This portfolio will be analysed using different visualisations and refined accordingly. Once this step has been completed, the portfolio will be back-tested to ascertain its optimality. Finally, you will be shown how optimisation techniques and genetic algorithms can be used to deal with various practical constraints commonly encountered in portfolio management applications.

Seminar Highlights

Through a series of modelling and analysis steps, attendees will see how to use the financial tools in MATLAB to

• Estimate moments of asset returns, even with missing data
• Use mean-variance analysis to generate optimal portfolios
• Visualize the time-evolution of optimal portfolios on the efficient frontier to identify a stable region of return and risk with minimal turnover
• Back-test the performance of portfolios from this stable region to demonstrate the superiority of these portfolios
• Use a range of optimization routines to obtain constrained portfolios

Agenda

• 08:30 - 09:00 - Registration. Tea, coffee and pastries
• 09:00 - 09:30 - Introduction
• 09:30 - 10:00 - Asset pricing
• 10:00 - 10:30 - Portfolio Optimisation
• 10:30 - 10:45 - Tea/coffee break
• 10:45 - 11:30 - Visualisation
• 11:30 - 12:00 - Backtesting
• 11:30 - 12:00 - Optimisation and Genetic Algorithms
• 12:00 - 12:30 - Concluding remarks - Questions and Answers