Call option price function in Bernstein polynomial basis with no-arbitrage inequality constraints
DOI10.1186/s13660-016-1097-xzbMath1338.91160OpenAlexW2409151509WikidataQ59463100 ScholiaQ59463100MaRDI QIDQ295013
Sumit Kumar, Arindam Kundu, Shiv K. Gupta, Nutan Kumar Tomar
Publication date: 17 June 2016
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13660-016-1097-x
quadratic programmingBernstein polynomial basiscall price functionconstrained functional regressionno-arbitrage inequality constraints
Nonparametric regression and quantile regression (62G08) Statistical methods; risk measures (91G70) Quadratic programming (90C20) Derivative securities (option pricing, hedging, etc.) (91G20) Approximation by polynomials (41A10)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The Pricing of Options and Corporate Liabilities
- The Bernstein polynomial basis: a centennial retrospective
- On the convergence of derivatives of Bernstein approximation
- Nonparametric option pricing under shape restrictions
- Unimodal density estimation using Bernstein polynomials
- Shape restricted nonparametric regression with Bernstein polynomials
- Semi-nonparametric estimation with Bernstein polynomials
- Semi-nonparametric estimation of the call-option price surface under strike and time-to-expiry no-arbitrage constraints
- Convex analysis in the semiparametric model with Bernstein polynomials
- Imposing no-arbitrage conditions in implied volatilities using constrained smoothing splines
- Arbitrage-free approximation of call price surfaces and input data risk
- Option Pricing With Model-Guided Nonparametric Methods
- Arbitrage-free smoothing of the implied volatility surface
- Bayesian Survival Analysis Using Bernstein Polynomials