My experience as a Quantitative Investment Intern in Fortune Sg Fund Management

In this article, Ziqian ZONG (ESSEC Business School, Global BBA exchange, 2024) shares her professional experience as a Quantitative Investment Intern in Fortune Sg Fund Management.
About the company
Fortune Sg Fund Management is a leading mutual fund management company with over 300 billion RMB in assets under management as of 2023. The company was founded in 2003 as a joint venture between Baosteel Group and Société Générale and has since grown to become a significant player in the Chinese market.
Fortune Sg leverages the capital markets to provide comprehensive asset management solutions for a wide range of domestic and international investors through professional operations. The company upholds the principle of prioritizing client interests, striving to be a responsible and trustworthy firm worthy of long-term commitment from all parties involved.
Logo of Fortune Sg
Source: Fortune Sg.
My internship
I joined the Quantitative Investment Department as an intern. This department primarily employs a multi-factor approach to select high-quality stocks in the Chinese stock market. The main products offered by this department are fundamental quantitative fund and quantitative hedging fund.
My missions
During my internship, I assisted the team with various programming and data analysis tasks. Furthermore, I undertook independent research project, including tracking the latest global trends in active quantitative funds and factor models, as well as developing a factor rotation-based index enhancement strategy.
Required skills and knowledge
The role requires advanced programming skills, primarily using Python and SQL. Proficiency in these languages is essential for improving work efficiency. Additionally, due to the rapid development of quantitative finance, it is necessary to read the literature to stay updated on the latest trends and investment methods. Sometimes, programming and searching for effective alpha (the excess return on an investment relative to the return of a benchmark index) can be tedious tasks that require persistent patience and confidence.
What I learned
During my internship, I gained extensive knowledge about factor investing and practical investment strategies. The integration of fundamental analysis with quantitative investment methods significantly enhanced the efficiency of traditional research. My research on factor timing allowed me to combine macroeconomic factors with market style shifts, using data to generate insights.
Financial concepts related my internship
Factor Investing
Factor investing is an investment strategy that utilizes certain quantifiable characteristics or attributes, known as “factors,” to explain and predict the risk and return performance of assets. These factors help investors better understand the behavior of the market and individual assets, leading to the construction of more effective investment portfolios.
The basic principle of factor investing is that certain factors have historically demonstrated a strong ability to explain and predict asset returns. By identifying and exploiting these factors, investors can achieve excess returns (known as “alpha”).
Common factors include:
- Value Factor: Selecting stocks with low valuations, such as low price-to-earnings (P/E) or price-to-book (P/B) ratios.
- Momentum Factor: Selecting stocks that have recently exhibited strong performance, under the assumption that this performance will continue.
- Size Factor : Selecting small-cap stocks, which historically have outperformed large-cap stocks.
- Quality Factor: Selecting stocks with strong financial health and high profitability.
- Minimum Volatility Factor: Selecting stocks with lower volatility, which tend to perform better during periods of market uncertainty.
- Growth Factor: Selecting stocks with high growth potential, such as companies with rapidly growing revenues and earnings.
Factor timing
Factor timing is an investment strategy that involves adjusting the exposure to different factors in a portfolio based on changing market conditions and macroeconomic cycles. The idea is to dynamically allocate capital to factors that are expected to perform well in the current or upcoming economic environment while reducing exposure to factors that are likely to underperform.
Here is how I do factor timing:
- Economic and Market Analysis: Investors analyze macroeconomic indicators, market trends, and other relevant data to understand the current and projected state of the economy. This analysis helps in identifying which factors are likely to perform well in different economic conditions.
- Factor Selection and Weighting: Based on the economic and market analysis, select which factors to emphasize in their portfolio. During Economic Expansion: Momentum and growth factors perform well because companies with strong recent performance and high growth potential are likely to continue thriving. During Economic Contraction: Quality and low volatility factors may be favored because companies with strong financial health and stable earnings are more resilient in downturns.
- Dynamic Adjustment: Continually monitor economic indicators and market conditions to adjust the portfolio’s factor exposures.
Why should I be interested in this post?
With the advancement of computer technology and the increase in alternative data, quantitative finance is occupying an increasingly larger share in investments. Understanding related content can provide valuable advantages and aid in making informed decisions when purchasing quantitative-related products.
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Useful resources
The most classic factor model: Fama French factor model
About the author
The article was written in May 2024 by Ziqian ZONG (ESSEC Business School, Global BBA exchange, 2024).