This proposal establishes novel techniques for extracting real-time economic information from derivatives securities. We develop new inference techniques to ensure satisfactory performance based on a parametric model for option prices with minimal restrictions on the dynamics driving the underlying asset prices. The estimated system embeds valuable information about market conditions, the pricing of risk in general and crash risk in particular. We outline applications involving predicting future equity returns, extracting spot volatility, pricing volatility risk and volatility derivatives, and documenting global linkages in market “fears.”
|Effective start/end date||9/1/15 → 8/31/18|
- National Science Foundation (SES-1530748)
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