How in the blue f**k are biotech / pharma growth stocks valued ?

Help me out guys,

I am not talking about the Pfizers / Roche of this world, but about the stocks of firms whose products are mostly in the R&D phase.

So I never studied medicine, chemistry or biology.

How is a generalist supposed to know if oncology product X in phase Y is going to get approved, and if yes what the sales will be ?

Basically my question is, is it even worth it to start reading up about this stuff to understand what the hell these firms are up to ?

We valued using forward EV/Revenue.

Start with a probablity based model and different sensitivities/scenarios. I never did analyze firms pre approval, that was far too risky. But firms that were approved, we used a forward EV/Rev multiple.

They are generally valued on a weighted average of the revenue probabilities based on expected market size and expected penetration. This is the least efficient part of the stock market. You have two types of investors here: Gamblers and specialists. I would avoid this area for the most part.

I am long zero biotechs and short a couple that have zero chance of success and are committing fraud.

In general, oncology and experimental drugs are the longest shot. Anything with preclinical or stage 1 trials are unlikely to go anywhere. If the stock is less than $300mm of market cap, statistically stage 2 and 3 trials are also very likely to fail.

They’re typically valued based on probability-weighted DCF’s based on total addressable market, typically, and reasonable (or sometimes unreasonable) assumptions around sales ramp

It is very difficult for anyone without an advanced degree to pick developmental stage biotechs; however, companies that do have FDA approved products can still be investible by generalists. I am long a couple biotechs myself.

Another method that is frequently used to value development stage biotechs is called “put my finger up in the air and pick a random number,” where that number is some number greater than zero and that equals the price target.

I listened to Damodaran’s valuation class this morning on the drive in and I’m on the part where he talks about using option pricing to value companies that have 1 or 2 projects in the pipeline like that. He said the strike was the cost of development, time was like the life patent protection, underlying was the estimated npv, and volatility was an estimate (from monte carlo or industry average). If the npv is above the strike, any cash flows are like dividends. I suppose you could build qualitative measures into the npv but over, seems like it could really be subject to major errors. Seems like you are just valuing unknown volitility, but what do i know.

hpracing007, as you alluded to, valuing development-staged biotech is very subjective and a lot of it simply comes down to business judgment. The best proxy of a potential ramp is seeing how previous drugs targeted market opportunities of similar size/demographics have ramped, while also handicapping your best sense of FDA approval probability.

Some people develop convoluted models for this stuff, 300-400 rows deep, but in many cases it’s just “garbage in, garbage out” and sometimes the added layers of assumptions and variables just gives them a false sense of security in their estimates.

If you use option pricing to value an early stage company in the way described by Damodaran, you are essentially saying that you have no idea what the company outlook is, what contingencies must be satisfied in order for the product to be commercialized, and how deep it can penetrate the market. Instead of building a firm-specific set of scenarios based on your research of the company’s positioning, you are throwing a lognormal distribution as a one-size-fit-all estimate for your company’s range of outcomes. You pack all the information from a decision tree / scenario analysis into a single input - the volatility - which is extremely subjective and has a non-transparent impact on your valuation.

Needless to say, this method makes for a nice powerpoint presentation to impress a client, or a good lecture for your class, and makes you look quantitative, but it is by far not an adequate substitute for a detailed scenario analysis grounded in industry knowledge.

Especially so for a biotech, where the outcome is so binary (go bust or have a multibillion-dollar drug) - the lognormal distribution, which packs most of its weight in the middle rather than at the extremes, seems like a particularly poor fit.

After posting this thread, I read up on a ER report made by a pretty established firm. It’s pretty much what you are describing. Also, they were using a 20% discount rate.

I find it extremely subjective. How do you determine that product x has a 25 % chance of bringing revenues and not 15%; why a 20% discount rate and not 25% or 15%, and how the fuck do you determine revenues of a product that doesn’t yet exist.

Actually now that I think of it, it is not so much different from seed / VC investing when nothing is known in advance, except that the equity is listed…

Is the rationale for investing in those the same as for investing in established pharma stocks (defensive, low beta, etc.), except with an extra growth exposure ?

As with many situations in the equity markets, you can reach basically any conclusion you want based on changing the numbers in your model. This is why biotech stocks are so volatile. The volatility in turn attracts volatility day traders. I have no edge here so I mainly sit on the sidelines unless I find an example where I can determine with 100% objectivity based on facts that the company has a zero or close to zero probability for success. I can’t recall ever buying a zero revenue biotech stock. I did used to own TEVA but that is a pharma company.

To answer your question though, in general, analysts will look at the market size and try to do some top down guess of how much market share the new drug could get, and then usually provide a scenario analysis based on a range – this is why they have probability adjusted scenario valuations because there is so much uncertainty. Of course that requires guessing about the probability which is another issue altogether. The valuations are probably systematically too high across all of biotech in general because the research analysts on the sell side are also the underwriters and biotechs repeatedly need to issue equity, so there is an embedded conflict.

I have often wanted to do a study but never have – how many biotechs haved “expired” worthless over the history of the capital markets? How many per decade? How many in each drug category? How much total equity capital has been infused into publicly traded biotechs?

I think you would find that over 80% never do anything (probably higher, 80% seems low) and that on the whole capital is destroyed in this industry – that’s my guess. Of course we still need biotechs because the results of the positive outcomes ar so valuable for society but I think it’s a particularly hard place to consistently invest successfully.

^^

You confirmed what I was thinking about the SEDA / equity line that these firms have set-up with their brokers. Makes sense, since they usually can’t get debt ; bank or FI.

I also like your use of the notion of expiration. It captures the segment well, IMO.

Would you recommend reading up on the medical side of it or not even bother (just FYI I work in Europe where the biotech investors are much less specialised than in the US) ?

I don’t see how you can realistically compete with specialists who do it full-time, so I would say no.

^^

Bromion, 2 more questions for you :

  • How do you spot biotech microcaps frauds ?

  • How do you go short on such companies ? In my experience they are usually in the range of say 50-80 M Market Cap, and very thinly traded. How do you short it ?

Not really. There are some huge ones. The biggest one I have seen excluding QCOR is $1.5B. There are many in the $200-600 range. There are a few tricks to find them but I don’t think I should share since this part of the market is so inefficient and I want to keep reaping the gains.