Human bias, complexity, and uncertainty are among the biggest obstacles investors face when it comes to investment valuation, and when Aswath Damodaran recently spoke at the 15th Annual Equity Research and Valuation Conference in Philadelphia, he offered the audience some practical guidance in responding to the uncertainties commonly faced when deriving the intrinsic value of a stock.
Damodaran first drew a distinction between estimation uncertainty and economic uncertainty. Estimation uncertainty, he said, can be caused by flawed models or incorrect inputs within a model, but can be mitigated by greater diligence on the part of the analyst. In contrast, economic uncertainty is inherent in financial markets and is “here to stay.”
When it comes to discounted cash flow (DCF) analysis, firm valuations can be impacted by micro forces, including competition, product quality, and execution by management, as well as by macro forces like the economy and interest rates. And while micro uncertainty can be diversified away within a portfolio, macro uncertainty will remain.
How best to deal with uncertainty? Let’s start with the don’ts: Unhealthy responses, according to Damodaran, include: paralysis and denial, or simply avoiding the problem; adopting mental short cuts like anchoring; herding, or following the crowd; and outsourcing by off-loading the decision making to others.
In the spirit of the season of “listicles,” here are Damodaran’s 10 rules for addressing uncertainty in valuations:
- Less is more. Don’t agonize over estimating every last line item as part of your valuation. Rather, follow the “principle of parsimony” (otherwise known as Occam’s razor), which favors simplicity when it comes to assumptions and solutions. In practical terms, Damodaran suggests that an estimate of an aggregate number, like an operating margin, is likely to be more accurate than estimates of its individual components.
- Build in internal checks for reasonableness. Estimates made as part of every DCF valuation should pass the “smell test,” particularly as the terminal year of the analysis is approached. That is, assumptions regarding items like revenues, market share, and profitability should be rational and supported by data.
- Use consistency tests. Because DCF valuations necessarily rest on assumptions, they are inherently judgmental. Ultimately, time will tell if the analysis is correct. In the meantime, it should be consistent: Don’t confuse cash flows from equity (cash flows after debt payments) and the cost of equity with cash flows to the firm (cash flows before debt payments) and the cost of capital (or real and nominal discount rates).
- Draw on economic principles and mathematical limits. The stable growth assumed in a DCF valuation cannot exceed the growth rate of the economy or, ultimately, it becomes the economy!
- Use the market as a crutch. Intrinsic valuations begin with the presumption that the market is not always right, yet it is appropriate to use market values as checks on inputs and potential biases.
- Draw on the law of large numbers. The law of large numbers states that the average of the results obtained from a large number of trials approaches the expected value as more trials are performed. When it comes to DCF inputs, according to Damodaran, “the average is your friend.” Using average betas across companies can eliminate the noise of single regression betas, and normalizing earnings can help to smooth volatile earnings when it comes to cyclical firms.
- Don’t let the discount rate become the receptacle for all your uncertainty. While it is true that in DCF valuations risk is reflected in the discount rate, too often analysts raise the discount rate to reflect any uncertainty and wind up unnecessarily underestimating a firm’s value. According to Damodaran, micro risks are likely to be diversified away so you should focus on macro risks when it comes to setting the discount rate.
- Confront uncertainty, if you can. Despite the inherent uncertainty of valuation work, analysts frequently make single point estimates for DCF inputs and arrive at a single estimate of value. As an alternative, Damodaran suggests a simulation, which allows an analyst to enter distributions for variables instead of single point estimates. The resulting distribution of expected values can be significantly more informative and reliable than a single estimate.
- Don’t look for precision. Inevitably new information will emerge, forcing you to adjust your DCF model inputs and impacting your valuation. This is the essence of risk, according to Damodaran, so you should remain flexible and accept that your models must adapt to new information.
- You can live with mistakes, but bias will kill you. Damodaran asserted that valuation mistakes are unavoidable — no one can forecast with certainty — but their impact on portfolios can be minimized with diversification. Biases, often caused by preconceived notions or financial conflicts, are potentially more costly when it comes to valuation.
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