Module Code and Title

IC208 Programming for Finance

Type of Assessment

Individual project

Weighting of Assessment

60%

Submission Deadline

19th April 2024, 12pm (noon)

Submission Point

(Blackboard/Turnitin/Other)

Blackboard

Items to be Submitted

One report with an appendix

Individual or Group Assessment

Individual

Module Convenor Office Hours/Opportunities for advice and feedback

The module convenors and teaching assistants are available for

advice and feedback. Individual appointments can be arranged upon request. Please use their emails addresses listed in

Blackboard.

I strongly encourage you to utilise the discussion board.

1. What is the purpose of this assessment?

Module Learning Outcomes being assessed

Carryout a practical project that involve Python applications in Finance

Data Management and visualisation

Make use of historical data and programming techniques to read, analyse and use different variables and signals for a decision-making process

Interpret and critically discuss the empirical results in light of prior finance literature

2.   What is the task for this assessment?

Task (attach an

assignment brief if

required)

The purpose of this project is to implement and evaluate a trading strategy(ies) using Python coding skills. The project is divided into subtasks, as follows:

1)    Download and manage a dataset of financial assets from an

online database.  You should choose at least 30 financial

assets during a period of at least 2 years. There is no

restriction on which assets should be included.

2)    Produce summary statistics of the financial assets’

characteristics,e.g., returns, trading volume, liquidity etc.,

during the sampled period of your choice. Discuss the

outcomes of your Python codes. There are merits for

explaining your choice of the financial assets, graphical

illustrations, discussions in linkages to prior literature.

3)    Define a trading strategy(ies) for individual assets.

4)   Construct a portfolio of financial assets based on certain

criteria, e.g., risk-return optimization.

5)    Evaluate the performances of the trading strategy(ies) in (3)

and the portfolio in (4).

3. What is required of mein this assessment?

Guidelines/details of how to prepare your

submission

Your submission should comprise:

•    Report with clear structure (at least introduction, main body, conclusion) and tables and figures.

•    Appendix with Python 3.6+ codes. Codes should be for Jupyter Notebook.

•    Reference list with all sources used.

The Python codes should be put only in the appendix. The report should NOT include Python codes.

The submission should be uploaded to [Blackboard> IC208> Assessment].

No extra libraries are allowed except for ones in the Anaconda package and ones covered during the lectures.

Three key pieces of advice based on the feedback

given to the previous

cohort who completed this assignment

It is essential to get your codes work in Jupyter Notebook.     In addition, the readability of your codes is important. Using comments (#) is recommended.

Furthermore, you should be able to interpret outcomes of your

codes and empirical results. "It does not matter whether you find a good trading strategy(ies) or not, you should provide a correct and  appropriate interpretation of your findings. Ensure that you

dedicate sufficient time to understanding your findings and their implications and communicate this clearly in your report.

For a high mark, you are expected togo beyond the references

provided under ‘Resources’ below to show that you have read

widely for this project and can link your findings to those of existing studies.

Formatting Guidelines

Microsoft Word

Word limit/guidance and penalty applied

1,500 words, excluding tables/figures, references.

Referencing Style

Harvard

Guidance on Academic Misconduct (including  using Turnitin practice  area)

You should ensure that the work you produce adheres to the

University’s statement on academic integrity and to the regulations regarding academic misconduct (such as plagiarism and cheating).   You can find information about this at:

http://www.reading.ac.uk/internal/exams/Policies/exa- misconduct.aspx

4. The Marking Scheme (Marking criteria/rubric)

Please refer to the marking criteria rubric at the end of this document.

5. What resources might I use to get started?

Python 3.6+.

Microsoft Word can be used to prepare the report and to format tables / figures.

Lecture and seminar notes.

Students are expected to read relevant literature which can be accessed via the Library Resources, a recommended guide include:

-      Brock, W., Lakonishok, J. & LeBaron, B. (1992) Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance, 47, 1731– 1764.

-      Conrad & Kaul (1998) An anatomy of trading strategies. Review of Financial Studies, 11, 489–519.