The Difference between Univariate and Multivariate Financial Analysis

Financial analysis is defined as an assessment of the going concern, leverage and profitability of a business or a joint venture. It is often referred to as an accounting or financial statement analysis. To perform financial analysis, many analysts use models, and these models can be either univariate or multivariate.


A univariate analysis is the most basic type of quantitative analysis. It is carried out using a single variable. For example, if the variable revenue per reporting period was the subject of the analysis, then the researcher would look at how many reporting periods showed a high, average or low revenue figure. The main quantitative method for univariate analysis is the median, mean or average. It also describes the dispersion of data: the range, maximum and minimums, variance with average and standard deviations, as well as frequency distributions.


A multivariate analysis is based on two or more variables within a financial model. This is a far more sophisticated financial analysis as it can take into account relationships, correlations and interdependencies. Multivariate analyses describes causes and its major use is to explain, compare and highlight relationships.

Differences between univariate and multivariate analysis

Univariate analysis is primarily used at the initial stages, by analyzing data that is already available. Multivariate analysis is used for inferential research, as two or more variables can be unknown or approximated.  Univariate analysis is usually utilized for descriptive purposes, whereas multivariate analysis is aimed towards explanations.

In financial analysis, the Univariate Model usually used is the one proposed by W. Beaver, where a company is classified as a failure if any of the three events occurred: bankruptcy, bond default, or an overdrawn account. To forecast financial failure, analysts focused on three financial ratios:

Cash Flow / Total Debt Net Income / Total Assets Total Debt / Total Assets

The univariate model assumes a business fails when any one of these financial ratios indicate financial difficulty; this is a simplification as start-ups may have low cash flow and large debt balances but cannot be classified as failures. The Univariate Model does not capture all scenarios of possibilities given its limited variable input.

The Multivariate analysis used in financial circles is known as the Altman Z-Score, a multi-variable analysis which uses five financial ratios, weighted according to importance to help increase the accuracy of the model’s prediction. Using these five variables, the model produces an overall discriminate score, a Z-score or zeta number. This multivariate analysis uses different indicators of risk and profitability, resulting in a model that showed a company’s risk of failure relative to a standard.

This allows for a more comprehensive view of the business’ current financial standing, and also standardizes different sized companies so that a meaningful comparison can be conducted.

However, a multivariate financial analysis can be difficult and costly to run. Furthermore, some financial information may be deemed confidential and be unavailable to analysts. It also takes far more time to be set up and tested successfully, whereas a univariate model is a quick, easy way of getting a feel for a company’s financial position.