Events - Seminars

MATLAB for Computational Financenew

Seminar Overview

Would you like to research, rapidly prototype and deploy financial models throughout your enterprise?

Come along to this free one-day seminar to see why finance professionals worldwide use MATLAB to develop and run quantitative applications up to 90% more efficiently than with traditional programming languages.

Experienced MathWorks engineers will demonstrate how you can use MATLAB to:

• Support a complete quantitative analysis workflow
• Perform risk analysis
• Develop pricing routines rapidly, validate and test them
• Build and analyse an index tracker
• Build, test and deploy quantitative trading models

Thank you for your interest in MathWorks Seminars. There are no dates currently scheduled for this Seminar. For more information on our seminars and products contact MathWorks sales or please visit:

Who Should Attend

This seminar is relevant to those who are involved in the following application areas:

• Market & Credit risk
• Trading and portfolio management
• Quantitative Analysis
• Pricing & Valuation
• Econometrics
• Computational finance software development

Seminar Highlights

Using worked examples we will:

• Demonstrate how to import, visualise and analyse data
• Construct and model portfolios
• Perform risk analysis
• Develop pricing routines using tree based methods and stochastic differential equations
• Deploy parallel computing techniques to improve efficiency
• Demonstrate how to work with 3rd party software and how MATLAB can call and be called from other languages

Agenda
09:30 - 10:00	*Coffee and Registration*
10:00 - 10:10	Welcome and Introduction
10:10 - 11:00	Introduction to MATLAB This session introduces MATLAB as a platform for computational finance. With examples we demonstrate how MATLAB supports a complete quantitative analysis workflow to: • Import, visualise and analyse data • Construct and model portfolios • Perform risk analysis • Use MATLAB as a unified platform for financial modelling
11:00 - 11:30	*Coffee Break*
11:30 - 11.35	Overview of The MathWorks
11:35 - 11:50	Customer Feedback and Development As an organisation, The MathWorks is committed to developing software and features that provide value for our clients. In this session we summarise how we incorporate customer feedback into our decisions to help drive our development efforts
11:50 - 12:25	Using MATLAB to Price Instruments One long standing use of MathWorks products in finance has been to price ever more complex products. This session will focus on techniques contained within the tools that enable users to develop pricing routines rapidly, and validate and test them. In this presentation, we focus on techniques including: • Tree based methods • Simulation of stochastic differential equations
12:25 - 13:00	Case Study: Building and Analysing an Index Tracker Here we use an algorithm designed to track an index to examine how MATLAB can be used to backtest the tracking strategy, perform style, attribution and risk analysis, and allow users to quickly test many different scenarios
13:00 - 14:00	*Lunch*
14:00 - 14:05	The MathWorks Community
14:05 - 14:50	Quantitative Trading: Research, Test, and Trade This presentation will introduce the use of MATLAB and other MathWorks products for quantitative and algorithmic trading. We will consider the process involved in building, testing, and deploying quantitative trading models, with specific focus on gathering data, historic and real time; prototyping trading strategies; and building a robust back-testing framework. We will also deploy parallel computing techniques to improve efficiency and generate models to work with third-party software
14:50 - 15.30	Taking MATLAB into Production The MATLAB development environment and open architecture make it possible to incorporate models directly into your production environment, without needing to re-code. This presentation examines how MATLAB can complement your software development process by discussing: • Interfacing MATLAB with other languages and applications • Best practice application development, including code sharing, object-oriented programming, testing and performance optimisation. • Application deployment, to desktop or server
15:30 - 15:45	Questions and Close

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