EV/EBITDA Ratio is a very commonly used metric for business valuation. EV/EBITDA Ratio compares the value of a company, inclusive of debt and other liabilities, to the actual cash earnings exclusive of the non-cash expenses.
EV/EBITDA Ratio is a very commonly used metric for estimating business valuation of companies. This valuation metric compares the value of a company, inclusive of debt and other liabilities, to the actual cash earnings exclusive of the non-cash expenses. It measures the price (in the form of enterprise value) an investor pays for the benefit of the company's cash flow (in the form of EBITDA). This metric is also known as Enterprise Multiple and EBITDA Multiple.
EV/EBITDA Ratio Formula
The EV/EBITDA Ratio is calculated by dividing the enterprise value (EV) by earnings before interest, taxes, depreciation, and amortization (EBITDA).
EV/EBITDA Ratio Interpretation
The main advantage of EV/EBITDA over the PE ratio ratio is that it is unaffected by a company's capital structure, in accordance with capital structure irrelevance. It compares the value of a business, free of debt, to earnings before interest.The enterprise multiple can be used compare the value of one company to the value of another company within the same industry. A lower enterprise multiple can be indicative of an undervalued company.
Good quantitative factors exhibit relationships with stock returns that not only have a fundamental and/or theoretical basis for stock returns but are also stable and persistent over time.
The EV/EBITDA Ratio is not usually appropriate for the comparison of companies in different industries. Capital requirements of industries vary from one another. Therefore, this factor may not give reliable conclusions when compared against a universe of stocks.
The Quantitative Analyst assesses individual stock factors by:
- separating the stocks into quintiles (or deciles) based on the value of the factor
- calculating the performance of each quintile based on rebalance period and total back-test period
- analyzing the spread of performance between Quintile 1 to Quintile 5
Ideally the performance spread should be "monotonic", meaning that Quintile 1 outperforms Quintile 2, Quintile 2 outperforms Quintile 3, and so forth.
Using the above process, the stocks from the S&P 500 were sorted into quintiles based on the quarterly EV/EBITDA Ratio versus stocks in the same industry, then evaluated over the 10 year back-test period 2005-2014 with a 3 month rebalance period.
The quantitative analysis was performed using both 3 month and 1 year rebalance period the results expressed in annualized percent profit shown in the column charts below.
The 3 month rebalance period has a nice spread between Quintile 1 and Quintile 5 when stocks are tested relative to their own industry. This test should be repeated using different random start dates and time periods in order to confirm the above results.
In Quantitative Analysis, single factor back-tests are not executed to generate real-life performance figures or to outdo a benchmark. At this stage the Technical Analyst is simply trying to identify whether the stock factor contains useful predictive value. There are many other considerations involved in the construction of a portfolio that will change the performance numbers.