Pros and Cons: Quantitative Versus Fundamental Analysis

Posted by Dana Funds Investment Team on Jul 10, 2019 4:21:47 PM

Of the thousands of mutual fund managers in operation today, there are countless opinions on quantitative versus fundamental analysis. Many managers use a combination of the two. Let’s dig into both disciplines and touch on the strengths and weaknesses of each.

Quantitative Analysis

Leveraging technology to analyze significant amounts of data, a quantitative or “quant” approach often uses mathematical and statistical modelling to analyze and/or rank various investments. This can be especially useful for smaller teams that do not otherwise possess the necessary resources to analyze an entire peer group of investments. Similarly, a quant approach can make sense if travelling for due diligence purposes is overly challenging. For example, a U.S.-based firm that invests in international/emerging market small cap stocks may rely on quant analysis in place of meetings with management.

Ranking investments is where a quant approach can shine. Many managers often incorporate factors related to quality (ie. Return on equity (ROE)), momentum (ie. Relative strength) and value (ie. P/E ratio) into their ranking models. A model can easily be customized to weight each factor differently, and results can be monitored daily to reflect changes in the market.

Pros:

  • Unbiased: Quant tools take human emotion and biases out of the equation.
  • Efficient: Once a quant system is built, it can be an extremely effective tool for analyzing vast amounts of investment opportunities in any geography. Can also be updated daily with new data.
  • Useful for screening: Effective at narrowing-down large investable universes into shorter lists to then be analyzed in more of a fundamental fashion.

Cons:

  • Incorrect data can produce misleading results. This is often referred to as “garbage in, garbage out.” Increases emphasis on high-quality data.
  • Unable to measure sometimes-obvious yet critical qualitative aspects like company culture, morale, leadership quality or changes in the regulatory or competitive landscape.
Fundamental Analysis

This approach focuses on a company’s financials as well as macro and microeconomic factors, often to predict the future direction of a company’s stock price. Fundamentally-oriented analysts also aspire to uncover a meaningful disconnect between their estimate of the intrinsic value of a company versus the consensus estimate. This type of approach is also known as bottom-up investing.

Pros:

  • Incorporates qualitative or immeasurable characteristics around company culture, leadership, brand, reputation and competition.
  • Introduces opportunities for an analyst’s experience, expertise and network to potentially add value.

Cons:

  • Time-intensive. Requires considerable resources to analyze an entire peer group. Introduces opportunity cost; risks missing-out on other opportunities.
  • Human biases. An analyst that spends weeks or months researching a specific opportunity may become anchored or overconfident in his/her research.

Ultimately it makes sense for a combination of quantitative and fundamental analyses to be incorporated into an investment process. Quant rankings can help save time when generating investment ideas, essentially getting an analyst “into the right ballpark.” Quant tools can also help identify improving/deteriorating trends within sectors, industries or companies and essentially play devil’s advocate against a popular opinion. Fundamental analysis can then add value by carefully looking at the business model, management team, competitive landscape and future earnings/cash flow potential.

These two methodologies can also complement each other when determining when to sell a position. A quant system can quickly flag other stocks that may represent stronger relative values, or point to relative weakness in a sector or industry. Fundamental factors leading to a sale could include turnover within a management team, an unfavorable acquisition or a change in business model. 

 

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