Damodaran

It's all biased! (but do not be afraid to do mistakes!)

"You almost never start valuing a company or stock with a blank slate. All too often, your views on a company or stock are formed before you start inputting the numbers into the models and metrics that you use and, not surprisingly, your conclusions tend to reflect your biases." Aswath Damodaran

The Yuppie Investor

Feb 3, 2024 — 7 min read

Photo by Google DeepMind / Unsplash

The Little Book of Valuation

TLDR :

"You almost never start valuing a company or stock with a blank slate. All too often, your views on a company or stock are formed before you start inputting the numbers into the models and metrics that you use and, not surprisingly, your conclusions tend to reflect your biases." Aswath Damodaran
"The inputs that you use in the valuation will reflect your optimistic or pessimistic bent"
"Put these biases down on paper, if possible, before you start."
"Spend more time looking at a company’s financial statements thanreading equity research reports about the company."
"As a general rule, the more bias there is in the process, the less weight you should attach to the valuation judgment."
"The firm may do much better or much worse than you expected it to perform, and theresulting earnings and cash flows will be different from your estimates; consider this firm-specific uncertainty."
"The macroeconomic environment can change inunpredictable ways."
"Interest rates can go up or down and the economy can do much better or worse than expected."
"One implication is that you cannot judge a valuation by its precision, since you will face more uncertainty when you value a young growth company than when you value a mature company."
"Finally, collecting more information and doing more analysis will not necessarily translate into less uncertainty. In some cases, ironically, it can generate more uncertainty."
"When valuing an asset, use the simplest model that you can."

Some Truths about Valuation

Before delving into the details of valuation, it is worth noting some general truths about valuation that will provide you not only with perspective when looking at valuations done by others, but also with some comfort when doing your own.

All Valuations Are Biased

You almost never start valuing a company or stock with a blank slate.

All too often, your views on a company or stock are formed before you start inputting the numbers into the models and metrics that you use and, not surprisingly, your conclusions tend to reflect your biases.

The bias in the process starts with the companies you choose to value.

These choices are not random. It may be that you have read something in the press (good or bad) about the company or heard from a talking head that a particular company was under- or overvalued.

It continues when you collect the information you need to value the firm. The annual report and other financial statements include not only the accounting numbers but also management discussions of performance, often putting the best possible spin on the numbers.

With professional analysts, there are institutional factors that add to this already substantial bias.

Equity research analysts, for instance, issue more buy than sell recommendations because they need to maintain good relations with the companies they follow and also because of the pressures that they face from their own employers, who generate other business from these companies.

To these institutional factors, add the reward and punishment structure associated with finding companies to be under- and overvalued.

Analysts whose compensation is dependent upon whether they find a firm to be cheap or expensive will be biased in that direction.

The inputs that you use in the valuation will reflect your optimistic or pessimistic bent; thus, you are more likely to use higher growth rates and seeless risk in companies that you are predisposed to like.

There is also post-valuation garnishing, where you increase your estimated value byadding premiums for the good stuff (synergy, control, and management quality) or reduce your estimated value by netting out discounts for the bad stuff (illiquidity and risk).

Always be honest about your biases: Why did you pick this company to value? Do you like or dislike the company’s management? Do you already own stock in the company? Put these biases down on paper, if possible, before you start. In addition, confine your background research onthe company to information sources rather than opinion sources; in other words, spend more time looking at a company’s financial statements thanreading equity research reports about the company.

If you are looking at someone else’s valuation of a company, always consider the reasons for the valuation and the potential biases that may affect the analyst’s judgments. As a general rule, the more bias there is in the process, the less weight you should attach to the valuation judgment.

Most Valuations (even good ones) Are Wrong

Starting early in life, you are taught that if you follow the right steps, you will get the correct answer, and that if the answer is imprecise, you must have done something wrong.

While precision is a good measure of process in mathematics or physics, it is a poor measure of quality in valuation.

Your best estimates for the future will not match up to the actual numbers for several reasons.

First, even if your information sources are impeccable, you have to convert raw information into forecasts, and any mistakes that you make at this stage will cause estimation error.

Next, the path that you envision for a firm can prove to be hopelessly off.

The firm may do much better or much worse than you expected it to perform, and theresulting earnings and cash flows will be different from your estimates; consider this firm-specific uncertainty.

When valuing Cisco in 2001, for instance, I seriously underestimated how difficult it would be for the company to maintain its acquisition-driven growth in the future, and I overvaluedthe company as a consequence.

Finally, even if a firm evolves exactly the way you expected it to, the macroeconomic environment can change inunpredictable ways.

Interest rates can go up or down and the economy can do much better or worse than expected.

My valuation of Goldman Sachs from August 2008 looks hopelessly optimistic, in hindsight, because I did not foresee the damage wrought by the banking crisis of 2008.

The amount and type of uncertainty you face can vary across companies, with consequences for investors.

One implication is that you cannot judge a valuation by its precision, since you will face more uncertainty when you value a young growth company than when you value a mature company.

Another is that avoiding dealing with uncertainty will not make it go away. Refusing to value a business because you are too uncertain about its future prospects makes no sense, since everyone else looking at the business faces the same uncertainty.

Finally, collecting more information and doing more analysis will not necessarily translate into less uncertainty. In some cases, ironically, it can generate more uncertainty.

Simpler Can Be Better

Valuations have become more and more complex over the last two decades, as a consequence of two developments.

On the one side, computers and calculators are more powerful and accessible than they used to be, making it easier to analyze data.

On the other side, information is bothmore plentiful and easier to access and use.

A fundamental question in valuation is how much detail to bring into the process, and the trade-off is straightforward.

More detail gives you a chance to use specific information to make better forecasts, but it also creates the need for more inputs, with the potential for error on each one, and it generates more complicated and opaque models.

Drawing from the principle of parsimony, common in the physical sciences, here is a simple rule: When valuing an asset, use the simplest model that you can.

If you can value an asset with three inputs, don’t use five. If you can value acompany with three years of forecasts, forecasting 10 years of cash flows is asking for trouble. Less is more.

Start Your Engines!

Most investors choose not to value companies and offer a variety of excuses: valuation models are too complex, there is insufficient information, or there is too much uncertainty.

While all of these reasons have a kernel of truth to them, there is no reason why they should stop you from trying.

Valuation models can be simplified and you can make do with the information you have and—yes—the future will always be uncertain.

Will you be wrong sometimes? Of course, but so will everyone else. Success in investing comes not from being right but from being wrong less often thaneveryone else.