Abstract
A random cash/futures basis is derived in a dynamic multimarket learning game with sequential information shocks and strategic arbitrageurs who trade to exploit gaps in the basis. Statistical properties of the authors' theoretical basis are derived both with and without index arbitrage. The authors find that basis volatility, a measure of intermarket mispricing, may initially increase even as individual prices become more precise and that arbitrage reduces basis volatility. The model is also used to analyze regulatory issues such as the possible impact of 'circuit breakers' on the quality of the trading process. Copyright 1994 by University of Chicago Press.
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