This assignment is designed to allow learners to implement machine learning relating to investment management

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Investment Analytics & Portfolio Management AssignmentGuide

Assignment Title: Machine Learning

ASSIGNMENT GUIDELINES

1. Assignment Outline

This assignment constitutes 40% of the total assessment for the module, BM4215 – Investment Analytics & Portfolio Management. Students will submit on a group basis a type-written report and perform a group presentation. You will be randomly assigned into an assignment group by your module tutor. This assignment is designed to allow learners to implement machine learning relating to investment management.

2. Learning Outcome After the completion of this assignment, learners will be able to:

1. Implement a machine learning cycle from data preparation to model evaluation, with the aid of machine learning techniques relevant to investment management.

3. Requirements

1. Assignment brief for each assignment group:

Your team will be provided a financial dataset. You will perform predictive-type or classification-type supervised learning on this dataset using RapidMiner.

There are two datasets.

1. Raw dataset

The raw dataset, or Global Equity Market RAW.xls, has 32,912 observations.

2. Scoring dataset

This dataset, or Global Equity Market SCORING.xls, has 10 observations.

From the raw dataset, your group is to undertake prediction-type and classification-type supervised learning to score a new dataset (scoring dataset). The scoring dataset retain the actual values of the labelled attribute for comparison purposes.

Attachments:

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