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Definition of LTM EBITDA

LTM EBITDA is the Last twelve-month Earnings before Interest, Tax, Depreciation, and amortization. It is one of the popular relative valuation metrics used for businesses’ valuation purposes in their early to medium growth stage. It is also known as TTM EBITDA (Trailing Twelve-month).

In its simplest form, it intends to measure the performance of a business purely on the grounds of its operating performance without the impact of different taxation rules, depreciation treatment, and capital structure (mix of Debt and Equity). It is a historical valuation measure and is frequently used in Mergers, takeovers, and amalgamation purposes, to name a few.

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Explanation

Measuring the performance of two identical businesses requires some relative valuation tools. Among them, it is one such metric that helps make operational performance comparison easy to understand and appreciate for the intended user community.

It provides a recent one-year performance of the business, which helps in averaging outlier quarters and provides a more concise view of the year’s performance comprising the last twelve months. This figure forms part of the company’s financial analysis report, and value is attached to the business based on multiple LTM EBITDA.

How to Calculate LTM EBITDA?

Let’s explain this with the help of two companies:

Particulars

Company A

Company B

Net sales for the year

Q1

Q2

Q3

Q4

600000

125000

100000

200000

175000

800000

125000

100000

200000

175000

EBITDA for the last four quarters (12 months)

Q1

Q3

Q4

108000

25000

15000

38000

30000

106000

18000

26000

32000

30000

LTM EBITDA (25000+15000+38000

+30000)= 108000

+30000)=106000

LTM EBITDA/SALES (108000/600000)=0.18 (106000/800000)=0.13

EBITDA/ SALES (most recent quarter Q4) (30000/175000)=0.17 (30000/175000)=0.17

Thus, we can observe that EBITDA/SALES for the most recent quarter provide the same multiple of 0.17; however, using LTM EBITDA provides better insights and multiplier differences, leading to better valuation for the two companies.

Example of LTM EBITDA

ABC International Limited has reported the following data:

Particulars

31.03.2023

31.12.2023

30.09.2023

30.06.2023

Sales \$200,000 \$180,000 \$65,000 \$140,000

Expenses \$120,000 \$110,000 \$22,000 \$85,000

Depreciation \$18,000 \$13,500 \$18,000 \$9,000

Interest expenses \$25,000 \$14,000 \$22,000 \$13,000

Tax expense 7400 8500 600 6600

Net Profit \$29,600 \$34,000 \$2,400 \$26,400

Based on the above, let’s compute LTM EBITDA:

LTM EBITDA = Net Profit + Tax Expense + Interest Expenses + Depreciation

Particulars

31.03.2023

31.12.2023

30.09.2023

30.06.2023

EBITDA \$80,000 \$70,000 \$43,000 \$55,000

LTM EBITDA as on 01.04.2023= (\$80000+\$70000+\$43000+\$55000) = \$248,000

Uses

It offers multiple usages across various spectrums of functions. The main uses are enumerated below:

Helps in the valuation of the business more objectively as it is more focused on operational performance and unaffected by a capital structure, making it an apt measure of comparing similar businesses.

Useful for various ratio analyses such as EV/LTM EBITDA, Sales/LTM EBITDA, etc.

It is based on actual historical data, which makes it more credible and unaffected by subjective assumptions.

Due to its historical nature, it lacks any forward-looking usage and disinterests those more interested in knowing the future multiples than past ones.

LTM EBITDA vs NTM EBITDA

Both are used in conjunction and provide a healthy way to analyze a company; however, there are differences between the two, as enumerated below:

Basis

LTM EBITDA

NTM EBITDA

Introduction It is based on the last twelve months’ data and involves actual data. It is based on the next twelve months’ data and more on assumptions that differ from person to person and are subjective.

Accuracy and reliability It is more accurate and reliable. It is less accurate and subject to change compared to LTM EBITDA.

Preceding It precedes NTM EBITDA. It is forward-looking and uses LTM EBITDA as the premise for forecasting and other business projections.

Easy to compute and understand the same.

It is prone to less manipulation compared to other valuation matrices.

It is based on published data, making it more accurate and reliable.

Removes variable which is not relevant such as Depreciation, Interest expenses, etc.

It considers only twelve-month data, which is too small a period to make any meaningful insights.

It doesn’t reflect the cash tax paid by the business and is a poor proxy if one measures the firm’s Free Cash flow.

LTM EBIDTA also ignores the cash flow effects on account of investment in the business’s Working Capital and Fixed Investment.

It is purely historical and doesn’t incorporate any future projections, which is necessary for any potential investor.

It is not an apt valuation matrix for seasonal or cyclic businesses. Also, this matrix cannot measure business in new technology areas.

Conclusion

It is a popular valuation matrix that is an apt measure for companies with stable growth prospects and unaffected by personal bias on future projections as it is based on actual data. However, it lacks usage in companies with cyclical and seasonal impacts, limiting its usage. In addition, at times, LTM EBITDA can be manipulated by businesses through excessive use of leverage to artificially inflate operating profit since it ignores interest components paid on debt borrowing is not considered. Despite the shortcomings, the method finds its utility in valuation matrices used by the business while undertaking Mergers and Acquisitions and in normal parlance to analyze operational efficiency simultaneously.

It is one such relative valuation matrix and cannot be used as the only matrix in valuing business due to its inherent shortcomings. It can only be used in conjunction with more forward-looking relative valuation measures.

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This is a guide to LTM EBITDA. Here we also discuss the definition and How to Calculate LTM EBITDA? Along with an example. You may also have a look at the following articles to learn more –

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