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Introduction

Technology is one of the driving force of economic growth. Investing in the right technology companies stocks not only yields considerable returns but also boosts business growth which can improve social welfare as a whole. Typical investment methods include traditional equity research and quantitative trading. The former has a focus on in-depth fundamental analysis, but it costs a lot of human resources. The latter is efficient and scalable but focuses on statistical speculation instead of value investment. Taking both investor’s interest and social good into consideration, this project will blend in-depth fundamental analysis and quantitative techniques to achieve efficient value investment. For the implementation, both qualitative and quantitative data will be collected and processed. Python is the primary developing language with pandas as the quantitative tool. Different machine learning techniques will be practiced and evaluated through back-testing. A quantitative investing strategy model with respect to business ethics and trends in the technology sector will be delivered in the end.

Methodology

Timeline

Documentations

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Project Plan

Available Now

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Interim Report

To Be Released

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Final Report

To Be Released

Contact Us

The University of Hong Kong, Pokfulam, Hong Kong

+852 52249645

alcor@connect.hku.hk

Supervisor :

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Dr. SM Yiu

Associate Professor
Department of Computer Science
University of Hong Kong

Student :

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Alcor, Qingxu Zhang

Year 4
1st major: Computing & Data Analytics
2nd Major: Business Design & Innovation