In this research paper, Drs. Alexandre Antonov, Serguei Issakov and Serguei Mechkov generalize the American Monte Carlo method to efficiently calculate future values (or exposures) of derivatives using an arbitrage-free model.
Specifically, they present efficient calculations of the portfolio values (exposure) in a self-consistent way using an arbitrage-free model that is calibrated to both implied market and real-world projections. They propose a new algorithmic method of simulation of exposures (distributions of future values) based on an iterative backward induction, a generalization of backward induction, especially attractive for exotic portfolios.
Backward Induction for Future Values
Overall, highlights of this article include the generalization of the American / Least Square Monte Carlo method to compute the full future value – which we call Observation Value – by backward induction. The Observation Value accounts for all scenarios, including those on which exercises do occur, i.e. scenarios on which the instrument changes.
Complete the form to download this complimentary whitepaper, “Backward Induction for Future Values”
Authors: Dr. Alexandre Antonov,Dr. Serguei Issakov, and Dr. Serguei Mechkov
Complete the form below to download this complimentary research paper.
Sibos 2023
Derivative Insider Webinar Series: Future Directions for Capital Markets Technology in the Digital/...
Risk Live Europe 2023
Risk Hong Kong 2023
EQ Derivatives 2023
E-World Energy & Water 2023
Thinking Derivatively – March 2023 Newsletter
CASE STUDY: Exos Financial
Thinking Derivatively – January 2023 Newsletter
Thinking Derivatively – December 2022 Newsletter
Thinking Derivatively – November 2022 Newsletter
Coalition Greenwich - Modernizing Risk Management Technology: Has the Game Changed?