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Computational Quantitative Finance

· Students are required to implement a trading strategy and evaluate its performance relative to a random walk strategy.

· Students can choose one trading strategy covered in term 1, a strategy from the literature or implement their own.

· Students are required to collect data for their chosen trading strategy from one of the following sources:

§ Refinitiv

§ Bloomberg

§ Capital IQ

§ WRDS (including Datastream)

§ yfinance

· The report should contain the followings: 

o Details of the random walk model for asset returns, including critique of relevant stochastic models.

o Details of the chosen trading strategy, including critique of the chosen strategy with reference to relevant literature.  

o Implementation details such as trade entry, exit, risk control and transaction frequency & costs. 

o Financial performance; average return, Sharpe ratio, Maximum Drawdown, etc.  

o Historical simulation of the trading strategy using in and out of sample data.

o Critical evaluation of the results. 

· Details and critique of trading strategies should be written in Markdown.

· Analysis and Evaluation of code output should be written in Markdown.

· Explanation about code should be written within code cells with the ‘#’ notation.

· The report should be written in a Jupyter Notebook and submitted as a ‘.ipynb’ file.

Overall word limit: 1500

MARKING GUIDELINES

Performance in the summative assessment for this module is judged against the following criteria:

· Relevance to question(s)

· Organisation, structure and presentation

· Depth of understanding

· Analysis and discussion

· Use of sources and referencing

· Overall conclusions