The purpose of this course is to provide an update treatment of the core topics in the modeling of high-frequency data. Advances in computing and data technology make it possible to observe markets at very fine intervals of time. Using high-frequency data permits the calculation of realized measures which are superior to volatility measures generated from GARCH and stochastic volatility models. However, the processing and financial modeling of high-frequency data remains a challenge to both researchers and practitioners. As such, this course aims to provide guidance on the techniques involved in processing, filtering and modeling such type of data. Using data from TAQ and TICK- DATA databases, the attendance will have an intensive introduction to both the theoretical and empirical aspects of high-frequency data.
- Familiarize with Matlab syntax, functions, and write own functions.
- Computation of realized measures of volatility.
- Introduction to the theoretical foundations and mathematical models of continuous / discontinuous time modeling.
- Forecasting techniques.
- Monte Carlo Simulations: Design and implementation.
- 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)
- Estimation of Quadratic Variation and its Components
- Stylized facts (Normality, persistence and noise)
- Intra-day periodicity
- Leverage effect
- Jump estimation and identification
- Forecasting using short and long memory specifications
- Monte Carlo Simulations
This course will take place online. For further details and registration, please visit our website.