Robust framework for quantifying the value of information in pricing and hedging

Journal article

We investigate asymmetry of information in the context of the robust approach to pricing and hedging of financial derivatives. We consider two agents, one who only observes the stock prices and another with some additional information, and investigate when the pricing-hedging duality for the former extends to the latter. We introduce a general framework to express the superhedging and market model prices for an informed agent. Our key insight is that an informed agent can be seen as a regular agent who can restrict her attention to a certain subset of possible paths. We use results of Hou and Obłój [Finance Stoch., 22 (2018), pp. 511--567], on the robust approach with beliefs to establish the pricing-hedging duality for an informed agent. Our results cover a number of scenarios, including information arriving before trading starts, arriving after the static position in European options is formed but before dynamic trading starts, or arriving at some point before maturity. For the latter we show that the superhedging value satisfies a suitable dynamic programming principle, which is of independent interest. Finally, we explore how our results allow us to develop robust valuation of information.

Authors: Aksamit, A; Hou, Z; Obloj, J

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Society for Industrial and Applied Mathematics
• Journal: SIAM Journal on Financial Mathematics
• Volume: 11
• Issue: 1
• Pages: 27–59
• Publication date: 2020-02-06
• Acceptance date: 2019-11-06
• DOI: 10.1137/18M1177597
• EISSN: 1945-497X
• Language: English
• Keywords: pricing–heding duality; enlarged filtration; path restriction; asymmetry of information; informed investor; dynamic programming principle; robust superhedging; modelling with beliefs