Practical Application of Quantitative Analysis and Financial Modeling: An Internship Experience in Asset Management
Overview
This paper reflects on the author's internship experience as a quantitative summer analyst at China Asset Management Co. Ltd, where they developed stock trading strategies and quantitative models. The author discusses the development of technical and soft skills including mathematical problem-solving, creative thinking, coding, communication, and teamwork through practical project work.
What this reflection paper covers
- Introduction to internship role and responsibilities as quantitative summer analyst
- Description of stock trading strategy development and multi-factor model projects using mathematical and creative approaches
- Analysis of skills acquired including technical competencies, problem-solving, communication, and teamwork benefits
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Business Analysis
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Business Analysis
I have worked on several projects as an intern, and during my internship, I engaged in numerous activities. For instance, in China, asset management Co. Ltd in July 2021- August 2021 as a quantitative summer analyst, the responsibilities enabled me as an individual to be able to use my combination of mathematical abilities that is my ability to perform tasks that require to be solved mathematically and creative thinking skill that includes the ability to use skills to come up with new solutions (Bhattacharya & Neelam, 2018) . The two talents were portrayed when I established two stock trading strategies with different characteristics. Researched their returns by screening out targets stocks by each model and using a single exponential moving technique, low latency trending line of or market time, and conducted a thorough analysis of the return characteristic of each model. In addition, I led a team of three to complete replays of two multi-factor stock selection models, coding, and testing. I mastered the use of jointQuant quantitative trading forum that involves using data-based models to determine the chances of specific outcomes from happening, depicting my ability to solve problems creatively (Anjum, 2020). We had a complete model that conducted quantitative trading using historical stock market data within two weeks (Bhattacharya & Neelam, 2018). The win rate of our high-dividend model is 66.7%, which is very close to the securities model's 67%.