CAPITAL MARKET BLIND SPOTS

This paper presents evidence suggesting that financial markets are susceptible to persistent mispricing in new financial insurance products. We argue that relatively sophisticated market participants often fail to notice that portfolios identified to be very safe by recently developed risk models may have statedependent risk exposures arising from sources outside of the model. This error can create a perverse market dynamic that is sustained by market forces and academic research. * Coval, Pan, and Stafford are at Harvard University. We thank John Campbell, Joshua Schwartzstein, Andrei Shleifer, and Jeremy Stein for valuable discussions and seminar participants at Harvard Business School, Indiana University, INSEAD, Stockholm School of Economics, NY Federal Reserve Bank, University of Michigan, and UTDallas. Markets make mistakes. Mistaken notions of risk, and therefore pricing, occasionally persist in US capital markets for decades before becoming apparent to market participants. The realization typically arrives in the form of extreme losses to those specialized in bearing these risks. Once the realization occurs, pricing, capital requirements, issuance, and trading activity are significantly and permanently altered in the specialized segment of the capital market, suggesting that the market has indeed learned. A key question is whether these lessons are shared with other segments of the capital market or whether similar mistakes can persist elsewhere for long periods of time. This paper investigates the possibility that capital markets develop blind spots when financial models are misapplied in real world capital markets. Our focus is on models that are relied upon by issuers of economic insurance products, such as index options and credit index derivatives. These are highly systematic exposures, for which there is likely to be natural demand. This creates incentives for relatively sophisticated market participants to develop low-cost methods for supplying these products. Any failure to recognize state-dependence in model errors will likely entail a replication shortfall in a poor economic state, or an abnormally low model-implied state price for poor economic states. A blind spot of this form results in the sale of economic insurance products that are underpriced and backed with insuffi cient capital. We argue that a key reason why these blind spots emerge and persist for so long is that relatively sophisticated market participants rely upon learning rules (and research methodologies) that have little power to reject their model in economically benign states. Some participants may use the observation that market prices conform very closely to model prices as further evidence that their model is correct, gaining additional confidence in an incorrect view. Only when portfolios identified by the model to be very safe lose significantly more than believed possible is the model rejected. This learning event forces acknowledgment that the specialized model needs to be adjusted, but does not require a complete understanding of why. The updating process is complicated by the joint testing of the model and market effi ciency. With a strong prior on market effi ciency, the required ad hoc model adjustments are viewed simply as changes that are required to accommodate an evolving state-space, as opposed to evidence that the model was wrong all along and that imperfectly effi cient market prices provided little power to detect this. This allows the same basic error to be repeated in other specialized areas of the capital market. Merton (1997) recasts the logic of dynamic replication into a cost of pro-