High Frequency Financial Econometrics Using Matlab - 2 Day Course
Wednesday 25 April 2018, 9:00am to Thursday 26 April 2018, 5:00pm
Venue
Management School A001 (Computer Lab), LANCASTER, LA1 4YXOpen to
Alumni, Postgraduates, Public, StaffRegistration
Cost to attend - booking requiredRegistration Info
Accommodation
You can either stay on the University Campus or in Lancaster House Hotel, from where everything will be in walking distance of the training event venue. Alternatively, you can stay in Lancaster City Centre – a short bus ride or taxi journey away from the Campus. There are also other rural/out of town options for those with a car or who are happy to take a taxi or public transport.
Lancaster City Centre Accommodation
The Borough (no lift access)
Ticket Price
COMMERCIAL 2-day pass (25/04/2018 - 26/04/2018) £1,295 ACADEMIC £1,010 STUDENT £430 25% Discount is offered to attendees of the Frontiers of Factor Investing, which take place on 23rd & 24th April 2018 - http://wp.lancs.ac.uk/fofi2018/Event Details
This course provides an in-depth training in using Matlab in the analysis of high frequency financial data.
This course provides an in-depth training in using Matlab in the analysis of high frequency financial data. Advances in computer power and data technology have led to the introduction of high frequency data. These data are vital in understanding issues pertaining to market microstructure noise, and permits the calculation of non-parametric intraday measures of variation that are superior to parametric measures based on daily data. The sheer size of this type of data often pause huge challenges to both researchers and practitioners. As such this course aims, using Matlab and state of the art high frequency data from TICKDATA database to highlight the best techniques and practices to overcome the empirical challenges of analysing high frequency data.
GENERAL OBJECTIVES:
To demonstrate the empirical techniques and methods employed to analuse high frequency data with special emphasis on the calculation of realised measures, forecasting and Monte Carlo methods and design.
SPECIFIC OBJECTIVES:
- Learn how to write efficient codes in Matlab
- Be able to create your own functions in Matlab
- Learn how to compute realised measures of volatility and generate forecasts
- Develop an understanding of the theoretical foundations and mathematical models of continuous / discontinuous time modelling.
- Monte Carlo Methods, Design and Implementation
DAY 1
- Fundamentals of programming in Matlab
- Importing and exporting data
- Descriptive statistics and Density/log-density estimation
- inter and intra-daily plots
- Time stamp, frequency conversion and data aggregation
- Data bases comparison Tick vs TAQ
- Data Types (Equity, Forex and Indices)
DAY 2
- Estimation of Quadratic Variation and its Components
- Stylizised facts (Normality, persistence and noise)
- Intra-day periodicty
- Leverage effects
- Jump estimation and identification
- Forecasting using short and long memory specifications
- Monte Carlo Simulations
Contact Details
| Name | Teresa Aldren |
| Telephone number |
+44 1524 510906 |
| Website |