Day One
9:30 – 11:00
- The Interface, editor, comments
- Help
- Matlab syntax
- Decision rules and loops
11:00 – 11.20 – Coffee Break
11:20 – 12:50
- Matlab functions
- Matlab plots
- Importing/exporting files
- Data aggregation
12:50 – 14:00 – Lunch Break
14:00 – 15:30
- Tick vs. TAQ Database
- Estimation of Intraday returns
- Stylised Facts
- Data generating process
15:30 – 15:50 – Coffee Break
15:50 – 17.20
- Estimation of Realised Measures
- Jump-Robust Measures
- Market Microstructure Noise
- Noise-Robust Measures
Day Two
9:30 – 11:00
- Realised Jumps
- Jump Test Statistics
- Disentangling Significant Jumps
- Conditional Variance Models
11:00 – 11.20 – Coffee Break
11:20 – 12:50
- Forecasting Conditional Variance Models
- Introduction / Estimation to the HAR Model
- Forecasting Techniques
- Comparison of Conditional Variance from Daily and High-Frequency Measures
12:50 – 14:00 – Lunch Break
14:00 – 16:00
- Value-at-Risk using high-frequency measures and Conditional Variances
- Realised Betas: Estimation and Forecasting
- Monte Carlo Simulation
- Heston Model
- Simulating a Heston Model
- Simulating Microstructure Noise
- Monte Carlo Study – BNS Test
For the programme and references please visit the Programme Outline.