Robust upper bounds for American put options

Du, Ye; Xue, Shan; Liu, Yanchu

doi:10.1002/fut.21961

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their results are robust in that they only depend on the no-arbitrage principle. Based on the same trading strategy, Du, Xue, and Liu (2019) and Xue et al (2022) develop robust upper bounds for American options and various exotic options, respectively. Since robust option pricing only requires the no-arbitrage principle, the robust bounds are usually not very tight.…”

Section: Introductionmentioning

confidence: 99%

Tighter Robust Upper Bounds for Options via No-Regret Learning

Xue

2023

AAAI

View full text Add to dashboard Cite

Classic option pricing models, such as the Black-Scholes formula, often depend on some rigid assumptions on the dynamics of the underlying asset prices. These assumptions are inevitably violated in practice and thus induce the model risk. To mitigate this, robust option pricing that only requires the no-arbitrage principle has attracted a great deal of attention among researchers. In this paper, we give new robust upper bounds for option prices based on a novel η-momentum trading strategy. Our bounds for European options are tighter for most common moneyness, volatility, and expiration date setups than those presented in the existing literature. Our bounds for average strike Asian options are the first closed-form robust upper bounds for those options. Numerical simulations demonstrate that our bounds significantly outperform the benchmarks for both European and Asian options.

show abstract

Section: Introductionmentioning

confidence: 99%

Tighter Robust Upper Bounds for Options via No-Regret Learning

Xue

2023

AAAI

View full text Add to dashboard Cite

show abstract

Robust upper bounds for American put options

Cited by 1 publication

References 24 publications

Tighter Robust Upper Bounds for Options via No-Regret Learning

Tighter Robust Upper Bounds for Options via No-Regret Learning

Contact Info

Product

Resources

About