24th
Adding The Time Axis To Financial Modeling
One of the discussions that I am following closely is the one related to the crisis of financial modeling. A side effect of the financial meltdown of August 2007 (subprime) - September 2008 (Lehman, AIG) and the following credit crunch, is that existing models, mostly based on the Efficient Market Hypothesis, showed all their shortcomings.
My take is that all pre-meltdown models were representing static snapshots of the markets based on equilibrium hypotheses. New models will have to add a temporal axis and describe markets as dynamic systems, at the cost of abandoning formal elegance, nice equations and closed-form solutions.
The bare existence of “stocks” (i.e. pools of money, investment funds, house inventories), each with its own incoming and outgoing “flows” (i.e. investment flows, equity commitments and exits, construction of new houses and house sales) and related delays (i.e. time between investment decision and time to measure investment results, especially in illiquid markets) creates a dynamic system regulated by differential equations whose solutions are exponential and periodic functions over time.
Accumulating and depleting stocks of vast size allow the financial markets to deviate from equilibrium positions for long periods of time. System unbalances can build up and grow exponentially over years before collapsing. Social interactions among investors (aka herd behavior) can inflate bubbles that are sustainable for much longer than any static model can predict, hence reinforcing herd behavior.
The presence of stocks and delays in the system makes it possible for sources of instability to accumulate until finally some random event triggers a chain effect reversing the same self-reinforcing loops into self-destructive loops.
Some more food for thought:
- Insight: Regulating human nature by Andrew Lo of MIT Sloan
- Periodic Systemic Risk by Michael Spence of PIMCO
