Programme

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.