This was originally published sometime back by myself on LinkedIn. The genesis of this article is when I took upon myself to value a highly cyclical company during my month-long internship with a small startup. To value cyclical companies is very difficult with uneven cash flows and the valuation here relies a lot on assumptions.

Abraham Lincoln might not have been the greatest valuation specialist of all time, but he undoubtedly was one of the greatest leaders and statesman of all time. He worked for equality and free rights for all. To be free has been an eternal quest for humans. In the parlance of valuation, free cash flow is the gold standard for measuring financial value of an organization. As an intern with aYatti, I valued a small startup with uneven cash flows looking at its balance sheet, income statement, and cash flow statement. It was a very challenging task to value a highly cyclical company, given the company is generating stable profits, growing at a healthy rate and has business leaders as its clients with a strong order book. In a highly cyclical industry where the cash flows are very uneven ranging from positive to negative cash flows, the best discounting method is to discount free cash flow using the weighted average cost of capital known as discounted cash flow model1. Using DCF makes the value much less volatile compared to earnings or cash flow of a company according to Marco de Heer and Timothy M. Koller in their paper Valuing Cyclical Companies. DCF method measures free cash flows of a company i.e. cash flows generated after operational and capital expenses and discounting the cash flows with the weighted cost of capital. Weighted cost of capital is the weighted average cost of capital for equity and debt of the company.

CAPM model gives a comprehensive value to calculate the weighted average cost of capital. CAPM= Rf + β (Rm- Rf) where it’s easy to calculate risk-free rate and market premium but calculating beta which is covariance of the stock with benchmark index is not possible in case of unlisted companies. Looking at the seasonality of cash flows, a 0.7 beta of an unlisted equity seemed reasonable although a listed stock will have a much higher beta. Cyclical stocks usually are highly volatile which signifies that they would either rise or fall by higher measure when compared to the benchmark index. The benchmark index could be NASDAQ, S& P 500 etc. for listed companies in the US.

Further, the company is debt-free making other methods to value costs of tax breaks like Adjusted Present Value redundant. Scenario analysis is used to predict two different business cycles in companies wherein it breaks out of its existing business cycle. Scenario analysis is effective for companies with stable past earnings of more than ten years to decipher business cycles and earnings pattern. Moreover, it’s highly improbable to predict actual cash flows for companies with very uneven cash flows. The other way is to extrapolate trend analysis looking at data for past five years of data although it’s very difficult to find key business cycles. To avoid this limitation, I followed a conservative approach with a linear projection of future cash flows instead of replicating the uneven business cycle. This assumption is based on the idea that high cash flows would eventually even out low or negative cash flows generating a balanced earnings view. I further estimated future cash flows using below average growth rates of key variables like Net Income for fair estimation.

To give an example, I used ratio analysis like depreciation as a percentage of total income which was consistent within a range over the years analyzed. To calculate the change in capital expense which is a change in fixed assets, I averaged the difference between the change in fixed assets over consecutive years to derive a value for predicting future change in capital expenses. To predict change in working capital is very difficult. Working capital here would not include cash and notes payable. I simply used past annualized growth in current assets and current liabilities results to estimate future cash flows for change in working capital. This helped in averaging out the change in working capital which was varied the most during the years analyzed.

However, the pitfall of using this method is that you might forecast excessive cash flow for a year. For example, in one year, the free cash flow (cash flow generated after operating and capital expenses) was double that of last year. I avoided using terminal value for estimating perpetual cash flow considering it would increase unjustly the final enterprise value of the startup. Terminal value is a good tool to predict the perpetual value of cash flows for a well-established enterprise with a long history of generating positive cash flows.

Discounting cash flow at WACC helps to smoothen outliers over a longer period. In the end, using this method helps you to average out the cyclical unpredictability with a fair value of the company over the long-term. The exercise helped in distinguishing nuances of valuing companies with highly cyclical business cycles with limited data. Correlation between various data variables helps in establishing the relationship between different variables used for measuring cash flow. At the same time, it helps to set up a method which gives a range of values depending on estimates of few controlled variables.

1. Valuing Cyclical Companies: Marco de Heer and Timothy M. Koller