Wednesday, June 16, 2010

Behavioral Finance and Extreme Event Risk 2: Price-Fundamentals Feedback Loops

The Price-Fundamentals Feedback Loops
Today, we will continue the discussion we started in a post on Information Cascades. The fundamentals may depend on prices in a myriad of ways. Soros (1987) gives examples of companies fueling their growth by acquiring fast growing companies with stock which gives them higher valuation (since they now have a higher growth rate), which in turn gives them more stock to acquire fast growing companies and so on until the bust ensues. One of the price-fundamentals feedback loops during the tech bubble was the rise of spending by tech firms on tech products, which produced a self-sustaining boom-bust sequence. The recent crisis saw a number of price-fundamentals feedback mechanisms. As the house prices grew, owners withdrew cash from the equity and used it to propel spending in the economy thereby increasing GDP growth (see Figure 1), which made people feel even more confident about the future.
Figure 1: Price-Fundamentals feedback during 2003-2007 period



To be convinced that this loop actually took place (via the owner’s equity withdrawals), see this amazing chart from John Mauldin (http://www.frontlinethoughts.com/pdf/mwo101708.pdf):



Talk about tail wagging the dog. For statistical intuitions to be useful the possibilities and their probabilities must be known and more importantly themselves remain unaffected by the decisions of the participants. These conditions are obviously violated in the financial markets. The problems of information and judgment-fact feedback loops are the central problems that plague various economic theories of equilibrium, because they make the demand for financial assets highly unstable. This is the same reason that stylized psychological experiments examining statistical intuitions in a controlled setting are not applicable to finance. This is not to say that people always act rationally, only that as a practical matter, this irrationality cannot be used in any useful way to improve the risk management.

Let us summarize what we have learned and draw some conclusions for the practice of risk management. Traditional financial models assume that decisions are made by the independent participants, who incorporate all available information to form probabilities about the future possible states of the economy and then make buy and sell decisions based on this information. This independence assumption leads to stability of supply and demand in these models. This fallacious assumption is challenged by the empirical observation of information cascades and price-fundamentals feedback loops. These sharp changes in supply-demand relationships for the financial assets produced the extreme events are ignored by the traditional financial models. Risk models now used in the industry inherit this flaw when they use exponential decay weighting to slowly change the estimates of risk. This is precisely why all of the risk models rooted in the current paradigm showed low risk estimates in the beginning of 2007. They are simply ignoring the potential discontinuities and viewing financial markets as a stable system. In the words of the Basel Committee:
"…given a long period of stability, backward-looking historical information indicated benign conditions so that these models did not pick up the possibility of severe shocks nor the build up of vulnerabilities within the system. Historical statistical relationships, such as correlations, proved to be unreliable once actual events started to unfold… Extreme reactions (by definition) occur rarely and may carry little weight in models that rely on historical data.”

Let us reiterate an important point, the issue is not the irrationality per se, but the interdependence of the decision makers, particularly in the downturns, that presents the biggest problem for present day risk management. Rational participants can act in a manner which produces highly unstable markets in the presence of information cascades and price-fundamentals feedback loops, as is shown in a 1990 article by De Long, Shleifer, Summers & Waldmann. Likewise, irrational investors can produce a stable market in the absence of those two problems.
Practical Implications
1. PFF loops can make certain kinds of fundamental data nearly useless and, in fact, more dangerous than useless. This is because analysts and risk models will treat the price rises as dictated by the fundamentals and think that the market is on a solid footing. This happened repeatedly during the 2003-2007 period. For example, in July of 2005, Ben Bernanke was asked about a housing bubble during the CNBC interview.
CNBC INTERVIEWER: "Ben, there's been a lot of talk about a housing bubble, particularly, you know from all sorts of places. Can you give us your view as to whether or not there is a housing bubble out there?"
BERNANKE: "Well, unquestionably, housing prices are up quite a bit; I think it's important to note that fundamentals are also very strong. We've got a growing economy, jobs, incomes. We've got very low mortgage rates.”

Notice the fallacy that we discussed here. Bernanke gave “fundamentals” as the main reason for the explosive growth in house prices, including “economy, jobs, incomes”. Risk managers must forget about these types of fundamentals, they will never say anything useful about risk. In subsequent posts we will outline the metrics that risk managers can use to assess risk within the new paradigm of risk management that we are proposing.


2. When the price-fundamentals feedback loop is reversed, the results can be very drastic and swift, as the investors find out that so called fundamentals are little more than the mirror of price increases. Then, we have a double whammy of unwinding of a PFF loop i.e. a deleveraging, and a vicious information cascade where market participants begin to discard all fundamentals and simply focus on the waves of selloffs and possibly news of bailouts. If one looks back to the fall of 2008, it is easy to remember that, as the markets were crashing, many GDP estimates were still positive and the EPS estimates were still reasonable, but nobody cared, because investors instinctively knew that these so-called
‘fundamentals’ will unwind and reflect the prices rather than propping them up.
3. Lastly, and most importantly, the above conclusion shows that the fallacy in the common understanding of extreme events as unique Black Swans, which teach us nothing other than humility and the value of lottery tickets. In fact, all extreme events, despite having an infinity of possible causes, have similar characteristics (we will explore this further when we get to Hyman Minsky and the Financial Instability Hypothesis). A risk modeler and a risk manager must consider extreme events as a homogenous sample, which despite all their differences, have a great deal in common (this is why people speak of ‘rise in correlations’) and carry much more information than the ‘normal’ periods. In fact, ‘normal periods’ should be almost completely disregarded, which goes contrary to the current paradigm of risk modeling.



1. De Long, Bradford and Shleifer, Andrei and Summers, Lawrence and Waldmann, Robert, 1990, “Positive Feedback Investment Strategies and Destabilizing Rational Speculation”, The Journal of Finance, Vol. XLV No.2, June 1990.
2. Soros, George. The Alchemy of Finance: Reading the Mind of the Market. New York: Simon &Schuster, 1987.
3. Minsky, Hyman P., May 1992, "The Financial Instability Hypothisis", working paper #74.
4. Basel Committee on Banking Supervision (2009), “Principles for sound stress testing practices and supervision consultative paper”.

1 comment:

sample said...

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