What is Cross-Sectional Analysis

Cross-sectional analysis is a type of analysis that an investor, analyst or portfolio manager may conduct on a company in relation to that company's industry or industry peers. The analysis compares one company against the industry in which it operates, or directly against certain competitors in the same industry, in an attempt to assess performance and investment opportunities.

BREAKING DOWN Cross-Sectional Analysis

When conducting a cross-sectional analysis, the analyst uses comparative metrics to identify the valuation, debt-load, future outlook and/or operational efficiency of a target company. This allows the analyst to evaluate the target company's efficiency in these areas, and to make the best investment choice among a group of competitors within the industry as a whole. When comparing the target firm to competitors, the analyst must be careful to consider the unique operating characteristics of each company, and how those characteristics will affect any comparative metrics used.

Analysts implement a cross-sectional analysis to identify special characteristics within a group of comparable organizations, rather than to establish relationships. This type of analysis is based on information-gathering and seeks to understand the "what" instead of the "why." Cross-sectional analysis allows a researcher to form assumptions, and then test their hypothesis using research methods.

Cross-sectional analysis looks at data collected at a single point in time, rather than over a period of time. The analysis begins with the establishment of research goals and the definition of the variables that an analyst wants to measure. The next step is to identify the cross-section, such as a group of peers or an industry, and to set the specific point in time being assessed. The final step is to conduct analysis, based on the cross-section and the variables, and come to a conclusion on the performance of a company or organization.

Examples of Cross-Sectional Analysis

Cross-sectional analysis is not used solely for analyzing a company; it can be used to analyze many different things in business. For example, a study released on July 18, 2016, by the Tinbergen Institute Amsterdam (TIA) measured the factor timing ability of hedge fund managers. Factor timing is the ability for hedge fund mangers to time the market correctly when investing, and to take advantage of market movements such as recessions or expansions.

The study used cross-sectional analysis and found that factor timing skills are better among fund managers who use leverage to their advantage, and who manage funds that are newer, smaller and more agile, with higher incentive fees and a smaller restriction period. The analysis can help investors select the best hedge funds and hedge fund managers.

The Fama and French Three Factor Model credited with identifying the value and small cap premiums is the result of cross-sectional analysis. In this case, the financial economists Eugene Fama and Kenneth French conducted a cross-sectional regression analysis of the universe of common stocks in the CRSP database.