Valuing high-tech companies

[hmahncke]

I worked at a McKinsey once upon a time, and this is exactly how we did valuations. But this article elides the fact that with this kind of model, you can quite literally get any output you want from choosing your assumptions. In my view, it was better used as a "what assumptions would you have to believe to believe in a given valuation" rather than a valuation approach per se. It can be helpful to know that you'd have to have untenable assumptions to justify a given valuation. In any case, I bet the DCF model generates lower values than the private markets are paying, so it's only interesting to such companies in the public markets where you can act on your beliefs by going short.

[CamatHN]

Thanks for the comment. Though I am wondering, as a consulting firm not a finance firm, why does McKinsey model and value companies? Are they brought into double check?

[teisman]

> ... it's only interesting to such companies in the public markets where you can act on your beliefs by going short.

I disagree. As Keynes stated, the market can stay irrational longer than you can stay solvent.

[porter]

I'm curious - how did you determine defensible discount rates at McKinsey?

[aub3bhat]

The title uses the word "high-tech", while the article uses "Hot startup", I doubt if Yelp can still be classified as a "Hot startup". Answering whether Yelp is truly "high-tech" does not matters since the article makes no assertion that relies on assuming Yelp to be "High-Tech".

The article is selling standard business analysis, packaged as if it was some kind of brilliant visionary insight. This "Retro analysis"completely ignores new streams of businesses that Yelp is getting into such as Food delivery. These typically have much higher revenue albeit at lower margins, than just advertising. Not factoring it is a gross miscalculation. The article also fails to compare Yelp with Grubhub. Which would have produced a much more realistic expectation.

The article reminds me of this video by Steve Jobs discussing how Marketing & Sales end up destroying companies. https://www.youtube.com/watch?v=-AxZofbMGpM

[thesumofall]

I don't think their analysis "ignores new streams of business". They specifically highlight how the different potential markets should be approximated.

[teisman]

> Whether this price is appropriate depends on your confidence in the forecasts and their respective probabilities.

Did I miss something or did the authors not mention a discount rate, or Weighted Average Cost of Capital (WACC)? Unless I'm wrong, a discount factor is needed to calculate the present value, regardless of using a probability-weighted DCF or a simple DCF model.

If true, then without more information on the WACC, the price they state does not only depend on our confidence in the forecasts and their respective probabilities.

[alexyes]

The target audience for this article is executives at corporate America, who understand very little of tech. It is helpful to understand how the rest of the world looks at tech.

[tryitnow]

For those of you who want to learn more and don't want to waste money on a finance text book, check out Aswath Damodoran's website. Pretty much everything you need to know about valuation finance can be found there, along with a lot of data.

Importantly he has a lot of sample models and calculations which will help make the principles "real" for those of you who prefer details to simplistic high-level concepts.

[studentrob]

Do analysts ever share their data models publicly? It'd be interesting to see the data and be able to play with numbers along with these kinds of reports.

[antiviral]

If you are looking for how these models are created, you can look at the work of well-regarded experts in the valuation field like Damodoran, whose techniques many at i-banks or consulting firms would learn at some point in their careers. This link is to Damodoran's post for LinkedIn and GoPro (with downloadable, completed Excel models, which can be used as templates for other valuations):

http://aswathdamodaran.blogspot.com/2016/02/lazarus-rising-o...

[nonsequ]

Yes, sell-side (i.e. brokers like Goldman, Morgan Stanley, etc.) analysts do share their models with clients. They do this both in 'hardcopy,' pasted into published research reports, as well as 'softcopy,' sending or publishing the Excel file. Not exactly mainstream distribution, but 'public' in the eyes of the SEC and something you can find if you look for it.

[retanto]

You'll never see any of their data models or data

[xyzzy4]

In my opinion, you can only value tech companies relative to each other, because as a whole their price/earnings ratios are all too high. For example, if you sum the value of the entire solar power industry, you get roughly the value of Twitter. That does not make sense to me.

[forgetsusername]

The money is made by being able to predict the future, be that lottery numbers, disasters or the future earnings of companies.

Modelling startups is hard, because there is so much estimation and variance. But the fact that it's hard is why its so important.

[gedrap]

Thanks for sharing, it's quite handy to see the thought process written down, quite educational.