Robust Framework for Quantifying the Value of Information in Pricing and Hedging

被引:5
|
作者
Aksamit, Anna [1 ]
Hou, Zhaoxu [2 ]
Obloj, Jan [3 ,4 ]
机构
[1] Univ Sydney, Sch Math & Stat, Sydney, NSW 2006, Australia
[2] Univ Oxford, Math Inst, Oxford OX2 6GG, England
[3] Univ Oxford, Math Inst, Oxford OX1 3JP, England
[4] Univ Oxford, St Johns Coll, Oxford OX1 3JP, England
来源
SIAM JOURNAL ON FINANCIAL MATHEMATICS | 2020年 / 11卷 / 01期
基金
欧洲研究理事会;
关键词
robustness superhedging; pricing-hedging duality; informed investor; asymmetry of information; filtration enlargement; path restrictions; dynamic programming principle; modeling with beliefs; UTILITY MAXIMIZATION; OPTIMAL TRANSPORT; RISK; DUALITY; OPTIONS;
D O I
10.1137/18M1177597
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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 Obloj [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.
引用
收藏
页码:27 / 59
页数:33
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