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Title: REaaS: Enabling Adversarially Robust Downstream Classifiers via Robust Encoder as a Service
Award ID(s):
2131859
PAR ID:
10464833
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
ISOC Network and Distributed System Security Symposium
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  1. null (Ed.)
  2. Abstract

    We introduce an arbitrage‐free framework for robust valuation adjustments. An investor trades a credit default swap portfolio with a risky counterparty, and hedges credit risk by taking a position in defaultable bonds. The investor does not know the exact return rate of her counterparty's bond, but she knows it lies within an uncertainty interval. We derive both upper and lower bounds for the XVA process of the portfolio, and show that these bounds may be recovered as solutions of nonlinear ordinary differential equations. The presence of collateralization and closeout payoffs leads to important differences with respect to classical credit risk valuation. The value of the super‐replicating portfolio cannot be directly obtained by plugging one of the extremes of the uncertainty interval in the valuation equation, but rather depends on the relation between the XVA replicating portfolio and the closeout value throughout the life of the transaction. Our comparative statics analysis indicates that credit contagion has a nonlinear effect on the replication strategies and on the XVA.

     
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