By Markus Seywerd, CIO, Park Lane Capital
Our firm, Park Lane Capital is a specialist in market behaviour. We develop behavioural statistics that help us understand market dynamics. In addition, for our investors, publish a weekly report highlighting notable changes in Market Stability. The report includes our Park Lane Market Stability Index for major world markets.
The term Market Stability, for our initial measurement of market behaviour, was coined by my business partner Mario Reinisch, shortly after we launched our firm in June of 2011. He was looking for a simple way of describing the quantitative aspects of our portfolio management process. The name stuck as it provides a visceral understanding of where we are in a market’s evolution. Everyone wants stable, that is predictable markets. These are the types of environments where everyone makes money. Nobody wants fragile(unstable) or broken markets. In these environments only the highly skilled, highly lucky or perma-bears seem to succeed. Our initial statistics were designed to provide an unbiased, third opinion of where we stood. They acted as a warning system for us, and our investors, flagging when extra vigilance was needed.
I believe the markets are always right. Their future level is what you and I are trying to predict and if we get the direction wrong, we are punished by both financial and reputational losses. If we get it right, our investors make money, we make money and our reputations are enhanced. With these motivations clearly Keynesian “animal spirits” are the main driving factors of any speculative market.
The markets can be “right” and still present opportunities. I highly recommend four authors who do a fine job of highlighting the peccadilloes of market behaviour. Robert Haugen, Andrew Lo and Nassim Taleb, Benoit Mandelbrot.
The must reads include:
Robert Haugen: The New Finance: The Case Against Efficient Markets, 1995, Beast on Wall Street,1998, Prentice Hall, Upper Saddle River, NJ and The Inefficient Stock Market—What Pays Off and Why,1999, Prentice Hall, Upper Saddle River, NJ
Andrew Lo: with Campbell, John Y.; MacKinlay, A. Craig (1997). The Econometrics of Financial Markets. Princeton, NJ: Princeton University Press, with MacKinlay, A. Craig (1999). A Non-Random Walk Down Wall Street. Princeton, NJ: Princeton University Press, and Adaptive Markets: Financial Evolution at the Speed of Thought. Princeton University Press. 2017
Nassim Taleb: Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. New York: Random House. 2001.
Benoit Mandelbrot in The Fractal Geometry of Nature, 1982 and his The Misbehaviour of Markets: A Fractal View of Financial Turbulence, 2004
Stephen Wolfram’s book on complexity, A New Kind of Science, 2002 is also excellent at showing how a few simple rules can lead to very complex behaviour.
I have concluded that Keynes’s simple rules are all that is needed!
Keynes was right, “animal spirits” combined with his “beauty contest” drive speculative market prices. The “Keynesian Beauty Contest” is crucial. It introduces a simple feedback mechanism which results in complex, nonlinear price movement.
The Keynesian Beauty contest doesn’t ask; who is the most beautiful? But rather; who do you think will be voted most beautiful? Empirical studies have shown very significant shifts in voting behaviour and this is with a secret ballot! The market however is an open ballot. We are constantly receiving information on how people are voting. Even small perturbations have participants questioning which assets are going to win and which assets are going to lose the beauty contest.
Fear and greed combined with everyone trying to outguess everyone else, and a running tally powers the feedback loops, resulting in truly complex behaviour.
My conclusion thus far:
The emotional(behavioural) framework clearly contributes a large part to the price movements we witness.
Emotion ——> Price Movement
What we need to answer:
Can we do the inversion?
Price Movement ——> Emotion
Does the emotional signal rise above the noise?
Is this the dominant pricing mechanism?
My Formative Years
I graduated with my MBA in finance in 1996. I had great finance professors. Maurice Levy, Espen Eckbo, Bernard Schwab and Tsur Sommerville. I left university with a good grounding in Discounted Cash Flow analysis, the Efficient Market Hypothesis (EMH), Fama & French’s Factors and reading Grinold & Kahn’s “Active Portfolio Management”.
I liked the idea of efficient markets, but 10 years of work in geophysics, hanging out with many penny stock mining promoters had taught me a lesson. Emotions consistently trump rational thinking. As Guilford Brett, the discoverer of the high-grade gold mine on Table Mountain near the British Columbia/Yukon border once told me. “Markus, we don’t sell gold. We don’t sell stock. We sell dreams!”
I soon witnessed this on a grand scale in 1998 & 1999 with the inflating and bursting of the Internet Bubble. Emotion again trumped reason. Reason did win out in the long run. However, many players, shorting the high flying, highly overpriced stocks were already broke. In the long run, (dramatic pause) you are dead!
So how to reconcile these two disparate views of the market? One idea is that EMH is something akin to gravity. A weak force that can eventually collapse a bright star to a black hole. Or that that the markets are like a chaotic attractor with something like the EMH at its core but with prices fluctuating wildly and unpredictability around it.
If you want to read the article that introduced chaotic attractors to the public at large, myself included, look for Scientific American DECEMBER 1986 VOL. 254 NO. 12, 46-57, Chaos, by James P. Crutchfield, J. Doyne Farmer, Norman H. Packard, and Robert S. Shaw.
In my mind I have reconciled it this way. In the long run, a company that consistently throws off free cash, has great profitability ratios and is cheap by any or the commonly used metrics, barring unforeseen circumstances won’t go broke. If it pays a dividend rather than reinvesting its cash, you will see a return. However, only by winning the Keynesian beauty contest will its price appreciate. While history tells us, on average, this will happen in the future, there is no guarantee.
So, what is our goal? To generate alpha of course! But what are the real sources of alpha in today’s market? WHAT IS ALPHA?
The Hunt for Alpha
Alpha is elusive. It is not simply the constant produced by a regression you chose and not the simple regression of your returns against your bogey. Just because you haven’t explained the source of the return, in the age of factors, doesn’t mean that is your alpha!
In 2018 AIMA published an excellent paper: Perspectives 21- Industry Leaders on the future of the Hedge Fund Industry. It was really well researched and covered a broad range of topics. The real gem though was the infographic below: “The New Hedge Fund Product Taxonomy”.
To establish a meaningful and consistent
taxonomy, you must understand the environment, and this is difficult in a world
of hedge fund marketing that is constantly coming up with new words for old. I
think they have it right. The only sources of Alpha left are security selection
and market timing.
Security Selection; it sounds easy, it is hard! Even harder is Market Timing.
I postulate, that selecting a good company, with good management, with good cash flows, with good earnings, which is cheap, is much easier than knowing when to buy that company’s securities.
Some managers realize that picking a company is the easier part of alpha generation. After positioning themselves, they go on a media campaign to convince other people that that company is either beautiful or ugly. In a poll with a running total, they actively sway the Keynesian Beauty Contest. If more and more people start to believe, that a stock is beautiful, they build a snowball and people pile in. A new winner is born!
This can sometimes lead to very public, acrimonious, brawls. We recently witnessed this between Carl Ichan and Bill Ackman over the company Herbalife.
Their platforms are about truth (beliefs? opinion?), they need people to be swayed emotionally so that they can either buy or sell the stock. Greed or Fear! Once momentum builds in the stock, all observers see what the herd believes, and greed drives most to join the herd to make money.
Herding Inherent in Finance Industry structure
Another place this herding behaviour is evident is the trading desk. Here again it is predicated on the animal spirts of Keynes.
The setup is: 10 traders on a desk, 9 believe a stock is beautiful and they will retire within a year and 1 believes the stock is ugly. Likelihoods of either outcome are 50:50.
The stock then goes up and 1 trader is fired. The rest of the desk gets huge bonuses. However, if the stock goes down, 90% of the trading desk has lost money. Now what happens on the desk?
If the desk is shut down. No one has a job and you don’t get a bonus. Being right has not served you any better than being wrong.
If the desk stays in business, it might downsize, and 2 traders get sacked! Small bonuses are paid to those who remain. The probability of keeping your job going with the herd is 80% and the probability if you were the lone wolf is 50%.
The next quarter is business as usual.
What this illustrates is that to
minimize career risk in the finance industry and to maximize bonuses, you need
to run with the herd. After the 2008 crisis, the industry shrank, almost
everybody lost money, many were still paid a bonus and most remained employed.
How do you get an edge? How do you find a stock, which will be a future winner of the Keynesian Beauty Contest?
A fundamental, bottom up, stock picker does research. Thousands of hours of research. They employ legions of analysts to do research. Thousands of newly minted CFAs and MBAs studying every nuance of a company, the management, an industry, while integrating it into a coherent model based on future expectations. If what they believe will come true does, the EMH will take care of adjusting the price. This is the standard model.
I stress the word “model”. Models are a best incomplete, may be mis-specified or outwrite wrong. Data used in the models will always be incomplete and most importantly expectations are momentary! However, what is most important to me, these legions of analysts move in herds. They are after all a trading desk!
Smaller funds, who don’t have enough people to scour thousands of companies’ news releases and financial statements rely heavily on sell-side analysts in forming their opinions.
Many sell-side analysts do excellent jobs, know their industry inside and out, have access to experts and management that smaller funds can never achieve and are therefore a good source of information. However, they also go out, pound the table and nurture the Keynesian beauty contest.
Whether write or wrong on the future fundamentals, the more people they can get to believe in their view, the more price moves. The more the price moves, the more people will believe them. And so, it snowballs. They are the lauded as the all-knowing analyst and develop a cult like following. The next time it will be easier to move the price!
Letting Others Do the Work
The input of hundreds of thousands of investors and tens of thousands of analysts, ruled by models, driven by emotions, and countless idiosyncrasies of market mechanics produce the market behaviour we observe as price. The immense amount of work, the media commentary, the hard fought for informational advantages, the market moving rhetoric, are, in the end, reflected in the price behaviour.
Over the years, many have realized that others may have an informational advantage and could be getting a leg up. Other investors and strategies have been devised to spot it and profit from it. Here are a few.
- Following insider trading reports. Do what the insiders do.
- Follow option activity. Somebody knows something when large blocks of options are bought.
- Follow the large hedge funds regulatory filings. They have thousands of analysts so just piggy back on their hard work
- Use the sell-side analysts! They are the ones that often generate herding behaviour. If they love or hate a stock, even after publishing most go out and visit their best clients to convince them that their analysis is superior. Be at the front of this herd!
These are just a few of the tactics used by money managers around the world. Very few discover a stock through diligently screening tens of thousands. They wait, listen to others, listen to the community around them. If something peaks their interest enough research gets done so that they are convince themselves that the community around them is right and they should come on board.
A great model, for harnessing others work is the “Best Ideas” model.
With the “Best Ideas” model a large investment firm which provides large amount of commissions to sell side firms asks many different firms to submit their best ideas. Normally only 1-3. They then invest in these ideas. The sell side firm is compensated in future commissions only if the ideas work out.
Therefore, after submitting the idea to the “large firm”, the firm starts to disseminate the same ideas far and wide. As Investors of secondary and then tertiary importance are convinced of the merits of the idea, more buy and the stock prices go up! The biggest gains of course go to the first firm in. The firm paying the highest fees is running at the front of the herd!
Putting it all together
What do we know?
- Speculative markets were well described by Keynes
- Herding behaviour is inherent in market structure.
- There are two sources of true
- Stock Selection
- Market Timing
- Stock selection is picking what others will find beautiful.
- Market timing requires others to find the securities you chose beautiful soon!
- There are tens of thousands of securities to screen and tens of thousands of analysts doing it.
- The market is a running ballot of who is winning and losing the Keynesian beauty contest.
Our approach is to harness the power of the tens of thousands of analysts, portfolio managers, brokers, investors and insiders. As consensus views shift market behaviour changes and this change can be detected.
We have developed a series of powerful statistics that infer changes in this behaviour, that is changes in the path of the Keynesian Beauty contest.
This solves for both sources of alpha; 1. Security selection and 2. Market timing. In effect it is measures the conclusions of the work that many others are doing.
We, by harnessing cheaply available computing power, while not knowing what individuals are thinking, we can detect shifts in the aggregate mood of thousands of market participants and position ourselves in the safest part of the herd not running towards the bear or standing in front of the bull.