Investing in Small-Cap Biotech through Hedge Funds

Biotechnology is hard for most buy-and-hold value investors to understand and forecast.

Since a typical small biotech company has no sales, negative cash flows, and negative earnings, many of the conventional financial multiples have no economic significance. Prices can change based on investor sentiment and suffer from high variance due to the binary nature of clinical trials: Drugs either pass or fail.

So if we can’t rely on discounted cash-flow models or multiples, how can we invest in biotech?

After analyzing data from 2007 on, I have found that higher hedge fund ownership is positively correlated with forward returns and that stocks with higher short interest are correlated with negative forward returns.

Also, in looking at several companies with high hedge fund ownership, I noticed a preponderance of health-care–specific hedge funds as opposed to more generalist funds like Pershing Square or AQR that invest in any sector.

The efficient market hypothesis (EMH) holds that the way to generate higher returns is by increasing systematic risk, but my research suggests this may not apply to small-cap biotech. The smart money in the industry has higher hit rates overall and can pick more big winners and avoid more big losers.

Intuition

Hedge fund ownership and short interest seem to work because of high intra-industry variance.

While politicians have some influence on drug pricing, biotech stock prices rise and fall based largely on the probability of a drug passing or failing clinical trials. Even if politicians attempt to cap drug prices, though the overall industry may suffer, there will still be winners and losers depending on which drugs are approved. Therefore, biotech hedge funds can pick the relative winners and losers regardless of the political situation.

By contrast, in the energy sector, the most powerful predictor of returns is the price of oil itself. So an energy hedge fund has to anticipate whether oil is going up or down. If the fund goes long on low-quality companies, it will outperform when oil prices are rising but underperform when they are falling. In general, the factors in the energy industry that work well in one scenario will fail in another.

Digging In

In my analysis, I took all the biotech stocks in the Russell 2000 Index from 2007 to 2015 — about 105 each month on average — and categorized each firm for each month into four quartiles based on hedge fund ownership as a percentage of shares outstanding. Q1 contained the least hedge fund ownership and Q4 the most. I also categorized short interest as a percentage of a float, with Q1 having the least short interest and Q4 the highest.

I then calculated the one-year forward returns for each stock in the index at the end of the month. For companies that were acquired or went bankrupt before the 12-month forward date, I took the total return from the given date to the final trade date. Below are the average short interest and hedge fund ownership of each quartile.

Sources: FactSet, Russell, company filings

Results

The chart below shows hit rates for each quartile of hedge fund ownership. All one-year forward return buckets are mutually exclusive. For example, the bluish-grey <-15 bucket indicates that 20% of the stocks in Q1 earned returns between -15% and -40%.

Distribution of Returns by Hedge Fund Ownership

Sources: FactSet, Russell, company filings

Of the buckets with positive returns, Q4 hedge fund ownership had higher hit rates in each bucket than Q1 hedge fund ownership. Looking at the negative return buckets, Q1 hedge fund ownership tended to pick more big losers than Q4, with the exception of the 0 to -15% bucket.

The results were similar when it came to short interest.

Distribution of Returns by Short Interest

Sources: FactSet, Russell, company filings

In all the positive return buckets, Q4 (high short interest) has the lowest higher hit rate, while in all the negative return buckets, Q4 has the highest hit rate. The other quartiles (Q1–Q3) are not noticeably different from each other. Thus, the stocks that are heavily shorted indicate which are more likely to underperform.

While this short interest factor is not as strong as the hedge fund factor, it does provide a great indicator as to which stocks with high hedge fund ownership to avoid. Over the sample, within Q4 hedge fund ownership, high short interest detracts an average of 15%, as the chart below indicates.

One-Year Average Forward Return

Sources: FactSet, Russell, company filings

Robustness over Time and Holding Period?

So are these results likely to be sustained or are they just the product of a few especially strong years? To find out, I calculated the information coefficient over time, which I computed as the correlation between the expected decile return rank and the actual decile return rank.

One-Year Forward Information Coefficients

Sources: FactSet, Russell, company filings

The results demonstrate that the two factors have worked most of the time, and when one factor hasn’t performed, the other has helped mitigate some of the losses.

Moreover, this strategy holds for periods other than one year, as we can see below.

Holding Period Effect on Information Coefficients

Sources: FactSet, Russell, company filings

Putting This to Work

Betting on high hedge fund ownership and low short interest stocks worked particularly well over this sample. But does it make sense to buy or short biotech based on hedge fund ownership alone?

Among Q4 hedge fund stocks, there may be quantitative hedge funds that own positions in each but have no insight into the probability of drugs passing clinical trials. Or there may be large hedge funds that take small bets as a percentage of their portfolio in the hope of large payoffs.

While this analysis does not address such questions, I have tested hedge fund ownership in other industries and found little to no correlation with forward returns. This leads me to conclude that health care–specific hedge funds are superior investors in the sector.

So what’s the best way to apply this study? Use it as a screen: Identify stocks with the highest probability of outperformance and then exercise your discretion in choosing among them.

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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: Getty Images/ALFRED PASIEKA/SCIENCE PHOTO LIBRARY