Understanding the difference between fundamental and quantitative
Portfolio managers (also known as investment managers) use various styles and approaches when managing money. Here we examine two well-known methods – fundamental and quantitative.
A portfolio manager who bases their investment decisions on fundamental analysis will attempt to determine a security’s intrinsic value by examining factors that could affect its price. Many focus on aspects that are qualitative and subjective in nature in order to get an “edge”.
There are two approaches to performing fundamental analysis:
Top-down. The analysis begins by looking at the “big picture” and examining the broader market, sector, or industry, before narrowing down to a specific security.
Bottom-up. The analysis begins with examining the fundamental factors of a specific security, like the financials or management of a company, before considering the overall market.
Managers can use either approach to come up with a value for a security that they can then use to compare to the security’s price, thereby determining if the security is overvalued or undervalued. Based on this analysis, the portfolio manager will build a portfolio of stocks that he or she believes have the optimal risk/return profile for a specific investment strategy and then routinely monitor the performance of each stock. The goal is to buy each stock when it’s undervalued and sell when it’s overvalued.
Quantitative (“quant”) investing employs a computer-based model to guide investment decisions. A software model, developed by a team of programmers and investment professionals, is used to identify patterns in large quantities of stock and trading data.
Once a pattern that could potentially form the basis of an investment strategy is identified, an algorithm is developed to:
determine the optimal time to buy or sell a set of securities (within a set of parameters and according to various factors)
target or limit exposures to securities that exhibit the characteristics of the desired factors
assess and manage risk levels
This model is then vigorously stress-tested in different market environments to ensure that it performs in the way that it was programmed to.
Quant managers rely on their computer programs to varying degrees. Some use their models to form the optimal portfolio (as mandated by their investment strategy and risk profile) and then make the trades manually. Others will rely on the model to optimize the portfolio and automatically execute trades at set time intervals mandated by a rebalancing schedule.
Regardless of the extent to which the manager automates the investment process, the model is constantly reviewed in order to assess its ability to generate excess returns.
Can be a mixture of both
In fact, in the increasingly data-driven investment industry, computer modelling and algorithms are becoming table stakes in the pursuit of better portfolio returns. Which is why investment managers of various style and disciplines are looking to integrate them into their investment processes.