Thursday, December 23, 2010

Generating Alpha by Using Behavioral Finance Approach: Biotech and Oil

Behavioral Finance is one of the fastest growing, yet least understood of investment management fads. Unfortunately, when a new investment strategy or technique becomes fashionable it is often latched upon by practitioners looking to reword and reinterpret it in order to fit their pre-existing strategy. Especially when this pre-existing investment strategy involves earning money on commission! It’s funny how much discourse on utilizing behavioral finance techniques involves ending up in promulgating a long only investment ‘strategy’!

This article on behavioral finance has a different objective. It is intended to argue that alpha generation-in terms of isolating stock picking ability-could be produced in the biotech and oil exploration and production (E & P) sectors. Moreover, this alpha generation could be significantly enhanced by using behavioral finance techniques to produce a hedge trading strategy. ETFs would be an integral part of this strategy.

Do to this I will have to answer three questions

What is Behavioral Finance?
What Sectors or Stocks are Best Suited to Behavioral Finance?
How to Generate Alpha Using this approach?

What is Behavioral Finance?

Behavioral Finance is best encapsulated in the work of Kahneman and Tversky’s seminal volume ‘Judgment under Uncertainty’. In this work the authors develop a series of case studies which all emanate from a central starting premise or observation. This premised is the idea that when faced with decisions under uncertainty we use heuristics or ‘short cuts’ to reach a conclusion. Unfortunately, these heuristics are, quite often,  not the optimal solution to the problem.

Moreover, according to Nassim Taleb, medical research has discovered that we use the emotional parts of our brains to make decisions based on risk. Knowing this, it should come as no surprise that we often make in-optimal decisions based on greed and fear in the markets.

There is plenty of literature on the subject and I would refer to the work of Kahneman and Tversky in the first instance. However, I shall briefly mention one heuristic, namely, the availability heuristic. This relates to our tendency to over estimate the importance of near-term or ‘available’ information. For example, I believe that investors tend to irrationally discount the rest of a biotech companies pipeline, just because they have had a recent failure in the lab. I think a similar process applies to Oil E & P stocks.

Why Biotech and Oil Stocks are Suited to Behavioral Finance

The key is uncertainty. These are sectors that exhibit a high degree of individual stock volatility, but interestingly that does not necessarily mean a high degree of dispersion. This allows them to be subject to long/short strategies which I will outline in the last section. For now, I want to focus on the two sectors in more detail.

Biotech investing is fraught with uncertainty. Not only are there the usual concerns of clinical safety and efficacy, but also regulatory and pricing concerns are paramount too. There are also competitive concerns to any company pipeline. This comes not only from generics (after patents run out) but from competitors starting to trial ‘me-too’ drugs with similar modes of action to the one that is in more advanced trial stages. I will focus on the clinical and competitive issues here, because arguably the other issues will reflect across the industry as a whole. Recall that we are trying to generate pure alpha here, not call the sector higher or lower.

Probabilities of Success in FDA Clinical Trials?

Evaluating the pipeline of a biotech company inevitably involves making some assumptions over the ‘chance of success’ of a drug achieving endpoints in clinical trials and getting FDA approval. This involves uncertainty. Biotech investors can use this uncertainty to their benefit, if they understand not to overreact to a companies trial results. In addition, there are all sorts of general assumptions made over drugs probabilities of success in FDA clinical trials, which turn out to be misguided or plain wrong.

I will go into more detail on this in another article in future. For now, let me give one example. How many times have you seen an analyst research report ‘pencil in’ a 50% probability of success for a drug in Phase III? The reason they do this is because historical evidence suggests that, that is a fair estimate. However, this evidence rarely analysis the influence of the mode of action. Is the compound using a similar mode of action to a compound that has been FDA approved before? What about the trial sizes? Is this a novel class of drug? What about the time spent in clinical trials? How tricky is the target indication? There are myriad inputs and a one size ‘50%’ fits all solution will not do.

 I argue that investors can use this to their advantage. I also argue that investors tend to mentally adjust ‘probabilities of success’ based on whether the company has had success/failure recently in other trials.

Chance of Success for Oil Exploration?

Similarly, with Oil E & P, I would argue that their exploration campaigns are fraught with uncertainty. A company with recent success with the drill bit suddenly sees its existing drilling program being presented in the best possible light. However, one with a few failures gets sold off and then many investors are convince themselves that the management are idiots. Another example is how companies get bid up just because they have prospects in a region similar to that which has had success. It doesn’t seem to matter that the prospect could be in an unrelated field or be a different type of play entirely.

Generating Alpha Using Behavioral Finance

What makes Biotech and Oil E & P interesting is that the individual share price movements display a high degree of event volatility, yet they will be correlated. This means that a long/short investor can generate alpha by buying a portfolio of stocks in the sector and then shorting the relative ETF.

For example, accepting that Oil companies are priced based on a factor of their reserves, an investor could argue that the chance of success in his oil stock portfolio is 40% He and the market agree that the un-risked NPV is $1000. This gives him a risked NPV of 1000*.4=$400 In other words, he thinks his portfolio is worth $400.  However, the market is pricing his stocks at $300. The market thinks the oil reserves in his stocks are only worth $300.  There is a value discrepancy here.

 He buys the stocks at $300 then shorts $300 worth of oil. When the value discrepancy is ironed out- by his companies discovering oil- then he will make $100 because his stocks go to $400. Note that this $100 return is irrespective of whether the price of Oil has doubled or not. In other words, this is pure alpha generation using a hedged approach to risk.

It is not hard to see how this approach would work with biotech stocks too. However, biotech stocks tend to be less correlated with the economy than Oil stocks. Also, I would expect their results to be more dispersed, because their end product is not a commodity as would be the case for oil producers. Biotech is subject to more technological obsolescence by medical science developments. This makes it more feasible to be used as a non-correlated concentrated portfolio than Oil E & P.

Nonetheless, both are great sectors to generate alpha utilising a behavioral finance approach. As a proxy for shorting Oil or Biotech a relevant ETF should give good exposure.


Kahneman, Daniel and Tversky, Amos ‘Judgment under Uncertainty: Heuristics and Biases’ Cambridge University Press, 1982

Kahneman, Daniel and Tversky, Amos ‘Choices, Values and Frames’, Cambridge University Press, 2000

Taleb, Nassim Nicholas ‘Fooled by Randomness’ Random House, 2008


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