Posts Tagged ‘Special situations’

The phenomenal Zero Hedge has an article, Goldman Claims Momentum And Value Quant Strategies Now Overcrowded, Future Returns Negligible, discussing Goldman Sachs head of quantitative resources Robert Litterman’s view that  “strategies such as those which focus on price rises in cheaply-valued stocks…[have] become very crowded” since August 2007 and therefore unprofitable. The strategy to which Litterman refers is “HML” or “High Book-to-Price Minus Low Book-to-Price,” which is particularly interesting given our recent consideration of the merits of price-to-book value as an investment strategy and the various methods discussed in the academic literature for improving returns from a low P/B strategy. Litterman argues that only special situations and event-driven strategies that focus on mergers or restructuring provide opportunities for profit:

What we’re going to have to do to be successful is to be more dynamic and more opportunistic and focus especially on more proprietary forecasting signals … and exploit shorter-term opportunistic and event-driven types of phenomenon.

In a follow-up article, More On The Futility Of Groupthink Quant Strategies, And Why Momos Are Guaranteed To Lose Money Over Time, Zero Hedge provides a link to a Goldman Sachs Asset Management presentation, Maybe it really is different this time (.pdf via Zero Hedge), from the June 2009 Nomura Quantitative Investment Strategies Conference. The presentation supports Litterman’s view on the underperformance of HML since August 2007. Here’s the US:

Here’s a slide showing the ‘overcrowding” to which Litterman refers:

And its effect on the relative performance of large capitalization value to the full universe:

The returns get really ugly when transaction costs are factored into the equation:

A factor decay graph showing the decline in legacy portfolios relative to current portfolios, lower means and faster decay indicating crowding:

Goldman says that there are two possible responses to the underperformance, and characterizes each as either a “sticker” or an “adapter.” The distinction, according to Zero Hedge, is as follows:

The Stickers believe this is part of the normal volatility of such strategies

• Long-term perspective: results for HML (High Book-to-Price Minus Low Book-to-Price) and WML (Winners Minus Losers) not outside historical experience

• Investors who stick to their process will end up amply rewarded

The Adapters believe that quant crowding has fundamentally changed the nature of these factors

• Likely to be more volatile and offer lower returns going forward

• Need to adapt your process if you want to add value consistently in the future

In Contrarian Investment, Extrapolation, and Risk, Josef Lakonishok, Andrei Shleifer, and Robert Vishny argued that value strategies produce superior returns because most investors don’t fully appreciate the phenomenon of mean reversion, which leads them to extrapolate past performance too far into the future. Value strategies “exploit the suboptimal behavior of the typical investor” by behaving in a contrarian manner: selling stocks with high past growth as well as high expected future growth and buying stocks with low past growth and as well as low expected future growth. It makes sense that crowding would reduce the returns to a contrarian strategy. Lending further credence to Litterman and Goldman’s argument is the fact that the underperformance seems to be most pronounced in the large capitalization universe (see the “A closer look – value” slide) where the larger investors must fish. If you’re not forced by the size of your portfolio to invest in that universe it certainly makes sense to invest where contrarian returns are still available. Special situations like liquidations and event-driven investments like activist campaigns offer a place to hide if (and when) the market resumes the long bear.

My firm Acquirers Funds® helps you put the acquirer’s multiple into action. Click here to learn more about our deep value strategy.


Read Full Post »

%d bloggers like this: