Sante Fe Institute

This week I had the privilege to attend the Sante Fe Institute’s conference in conjunction with Morgan Stanley (NYSE:MS) entitled Risk: The Human Factor.  There was quite the lineup of speakers, on topics ranging from Federal Reserve policy to prospect theory to fMRI’s of the brain’s mechanics behind prediction.  The topics flowed together nicely and I believe helped cohesively construct an important lesson—rules-based systems are an outstanding, albeit imperfect way for people and institutions alike to increase the capacity for successful prediction and controlling risk.  In the past on this blog, I have spoken about the essence of financial markets as a means through which to raise capital.  However, in many key respects, financial markets have become a living being in their own right, and as presently orchestrated are vehicles where humans engage in continuous prediction and risk management, thus making the lessons learned from the SFI speakers amazingly important ones.

This notion of financial markets as living beings in SFI’s parlance can be described as a “complex adaptive system” and is precisely what SFI is geared towards learning about.  While financial markets (and human beings) are complex adaptive systems, SFI is a multi-disciplinary organization that seeks to understand such systems in many contexts, including financial markets, but also in biology, anthropology, social structures, genetics, chemistry, drug discovery and all else where the concepts can be applied.

To highlight the multi-disciplinary nature of the event, John Rundle, one of the co-organizers of the event and a physics professor at the University of California Davis, with a special background in earthquake simulation and prediction introduced the theme for the day. Dr. Rundle presented results for his trading strategy founded upon his theories for earthquake prediction.   The strategy was built upon asking the following question: can models for market risk be constructed that implicitly or explicitly account for human risk?  Seems like things are off to a great start.

Some of the coolest, most interesting moments came during the Q&A sessions, where this year’s presenters, some past presenters, and many brilliant minds from finance including Michael Mauboussin, Bill Miller and Marty Whitman had the opportunity to engage each other on their theses, refining and expounding upon each other’s ideas.  Sitting in the room and absorbing conversations like John Rundle speaking with Ed Thorp during an intermission about their own risk management perspectives and how to maximize the Kelly Criterion in investments was a surreal experience that I sadly cannot impart in this blog post, but I hope to channel the spirit in sharing some of the important ideas I learned. Further, I’d like to invite any of you readers out there to add your own thoughts in the comments below.

Let’s start with the first presentation and walk through the day together.  In each subsection, I will give the presenter and their lecture title, followed by some notes from the lecture that I felt were relevant to my practical needs (this is not meant to be a thorough overview of each and all presentations).  I will type up my notes from Ed Thorp’s presentation in its own blog post, for there seemed to be considerable interest from fellow Twitterers on that one lecture in particular.

David Laibson, Harvard University

  Can We Control Ourselves?

Does society have the capacity to prepare for demographic change?  Experiments consistently show that people want the right thing, particularly when the question is presented as one of future choice.  However, when faced with the very same choice in the present, we fail to make the right decision; the very same decision we would make for longer-term planning purposes.   There is a behavioral reason for this: we want the right thing, but right now gets the full brunt of the emotional psychological weight, while planning is not nearly as influenced by the emotional element.  As a result, humans have a knack for making terrific plans, with no follow-through.

There is a neural foundation for this, as we have 2 systems (this is derivative of the idea presented in Daniel Kahneman’s Thinking Fast, and Slow).

  • The planning and focused system
  • The dopamine reward system based on immediate satisfaction

How can we help people follow-through on their goals in planning as it pertains to saving for retirement?

  • We can change the system from opt-in to auto-enroll, also known as the Nudge. Nudge is based on an idea presented by behavioral economists, Richard Thaler and Cass Sunstein.
  • We can use what’s called “active choice” and punish inaction, such that people must call and make a decision about their savings, rather than delaying it.
  • Make enrollment quicker by taking away the 30 minute paperwork barrier.

Which is most effective:

  • 40% participate with opt-in
  • 50% participate with an easier process
  • 70% enroll with active choice
  • 90% participate with a nudge

To that end, we were presented with information that showed people recognize self-control problems and opt for less liquid savings options if given the choice, EVEN IF the returns are exactly the same.  That is, people acknowledge their inability to control the itch to break their well-made plans.

Vincent Reinhart, Managing Director and Chief U.S. Economist at Morgan Stanley

FED Behavior and Its Implications

  1. Our paradigm for monetary policy:
    1. We have an expectation for the path of the economy and the Fed sets policy to meet that expectation
    2. The difference in policy over 2 successive actions follows a random walk. You can only acquire so much new information about the economy over the course of six weeks, making decisions based primarily on prior knowledge.
    3. The puzzle of persistence:
      1. Despite the random walk on decision-making, a chart of the Fed Funds Rate doesn’t actually follow a random walk.  It is a persistent path, whereby if the interest rate went down the prior month, it is more likely to go down again in the present month.
      2. The source of persistence:
        1. If there is persistence, and policies are predictable, then there should be ways to generate returns off of it.  Prices then would be drive to a fundamental value by arbitrage.  However, in central banking there is no arbitrage opportunity, because the mechanisms are confined to just the Fed and commercial banks, with no open market participation.
        2. While many talk about recent actions being “unprecedented” this is unequivocally not true.  These actions are very consistent with central bank behavior—QE and its ilk are balance sheet actions.
          1. Previously the Fed had a larger balance sheet as a % of GDP in the mid-1940s.
  2. Policy decisions are made by committees:
    1. Larger committees lead to less variance
    2. The right model to think about this is the committee as a jury, not a sample of policy options. The committees deliberate and take the best argument.
    3. There is an hierarchy of status in the Fed, including titles and media-friendliness that lead to greater degrees of influence from some members, over others.  This leads to the perfect setting for herding outcomes.
    4. Thus the random walk fails.
    5. Why have we not had a strong bounce-back from this recession?
      1. Milton Friedman talks of “plucking on a string” whereby a big drop should lead to a big bounce.
        1. There are serious problems with this analogy:
          1. An
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