TTC 202 Computational Finance and High Frequency Trading
In this course, we will discover where computer systems are extensively used in finance so far. We will discuss the latest development in computational finance such as GPU-accelerated Monte Carlo Simulation and Smart Beta algorithms. Furthermore, trading algorithms and strategies are evaluated in detail. The life cycle of trading strategy development will be discussed as well as the tow main approaches, mean reversion and momentum strategies, studied.
Part 1 Where computer systems influence financial markets
- Describe different influences of modern computational methods to typical financial problems
- Explain how modern algorithms developed in aeronautic, fluid mechanics and cognitive science shape the financial landscape
- How can graphic cards accelerate option pricing and how can beta become smart?
Part 2 Trading algorithm life cycle
- Explain what steps are necessary to develop a useful automated trading strategy
- Show how to develop promising ideas for trading strategies
- Describe how to assess strategy’s success
Part 3 The two main approaches: Mean-Reverting and Momentum
- Describe why the majority of trading algorithm can be assigned to either mean reverting or momentum
- What does the term mean reverting trading/momentum strategy cover and how to develop such strategies?
- What are cointegration and pair trading?
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