STA5091Z - Data-analysis For High-frequency Trading
15 credits at NQF level 9
Entry Requirements:
Acceptance into Master’s programs in Advanced Analytics, Data Science or Biostatistics, and/or statistical background deemed sufficient by the Head of Department. Course entry requirements: Acceptance into Master’s programs in Advanced Analytics or Data Science, and/or statistical background deemed sufficient by the Head of Department.
Course Outline:
The course aims to equip students with data-science skills required to manage and explore high-frequency financial market data. This includes managing large financial data-sets, carrying out statistical analysis of large data-sets and knowledge relating to the link between statistical analysis of fast large data-sets, the modeling thereof and how this can be used to understand and control real-time trading and risk systems in modern financial markets. The course aims to consolidate prior knowledge relating to the statistical properties of daily sampled financial data and to then extend this to the analysis, exploration and data-science of large data-sets relating to both limit-order data and real-time transaction data.