Dr. Peter Carr is the Head of Quantitative Financial Research at Bloomberg LP, where his group is responsible for all facets of the business operation relating to modeling and analytics. He is also the Director of the Masters in Math Finance program at NYU's Courant Institute. Prior to his current positions, he headed equity derivative research groups for six years at Banc of America Securities and at Morgan Stanley. His prior academic positions include 4 years as an adjunct professor at Columbia University and 8 years as a finance professor at Cornell University. Since receiving his PhD. in Finance from UCLA in 1989, he has published extensively in both academic and industry-oriented journals. He is currently the treasurer of the Bachelier Finance Society and a practitioner director for the Financial Management Association. Peter is also an associate editor for 8 academic journals related to mathematical finance and derivatives. He has given numerous talks at both practitioner and academic conferences. He is also credited with numerous contributions to quantitative finance including: co-inventing the variance gamma model, inventing static and semi-static hedging of exotic options, and popularizing variance swaps and corridor variance swaps. Peter has recently won awards from Wilmott Magazine for ``Cutting Edge Research'' and from Risk Magazine for ``Quant of the Year'' Published in: Journal of financial economics
Publication year: 2001
Co-author 1: Helyette Geman
Co-author 2: Dilip B. Madan
We present a new approach for positioning, pricing, and hedging in incomplete markets that bridges standard arbitrage pricing and expected utility maximization. Our approach for determining whether an investor should undertake a particular position involves specifying a set of probability measures and associated floors which expected payoffs must exceed in order for the investor to consider the hedged and financed investment to be acceptable. By assuming that the liquid assets are priced so that each portfolio of assets has negative expected return under at least one measure, we derive a counterpart to the first fundamental theorem of asset pricing. We also derive a counterpart to the second fundamental theorem, which leads to unique derivative security pricing and hedging even though markets are incomplete. For products that are not spanned by the liquid assets of the economy, we show how our methodology provides more realistic bid–ask spreads. r 2001 Published by Elsevier Science S.A.
We present a new approach for positioning, pricing, and hedging in incomplete markets that bridges standard arbitrage pricing and expected utility maximization. Our approach for determining whether an investor should undertake a particular position involves specifying a set of probability measures and associated floors which expected payoffs must exceed in order for the investor to consider the hedged and financed investment to be acceptable. By assuming that the liquid assets are priced so that each portfolio of assets has negative expected return under at least one measure, we derive a counterpart to the first fundamental theorem of asset pricing. We also derive a counterpart to the second fundamental theorem, which leads to unique derivative security pricing and hedging even though markets are incomplete. For products that are not spanned by the liquid assets of the economy, we show how our methodology provides more realistic bid–ask spreads. r 2001 Published by Elsevier Science S.A.