Convergence, non-negativity and stability of a new lobatto IIIC-Milstein method for a pricing option approach based on stochastic volatility model
DOI10.1007/S13160-020-00443-XzbMath1469.60179OpenAlexW3087294031MaRDI QIDQ2044133
Publication date: 4 August 2021
Published in: Japan Journal of Industrial and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13160-020-00443-x
stabilityconvergencestochastic differential equationsBlack-Scholes modelnon-negativityMilstein methods
Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Applications of stochastic analysis (to PDEs, etc.) (60H30) Numerical solutions to stochastic differential and integral equations (65C30)
Uses Software
Cites Work
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- The Pricing of Options and Corporate Liabilities
- Convergence, nonnegativity and stability of a new Milstein scheme with applications to finance
- Exponential mean square stability of numerical methods for systems of stochastic differential equations
- A boundary preserving numerical algorithm for the Wright-Fisher model with mutation
- Output feedback stabilization of stochastic feedforward systems with unknown control coefficients and unknown output function
- \(A\)-stability and stochastic mean-square stability
- Convergence and stability of two classes of theta-Milstein schemes for stochastic differential equations
- Mean-square stability of split-step theta Milstein methods for stochastic differential equations
- Choice of \({\theta}\) and mean-square exponential stability in the stochastic theta method of stochastic differential equations
- Analysis of non-negativity and convergence of solution of the balanced implicit method for the delay Cox-Ingersoll-Ross model
- Double-implicit and split two-step Milstein schemes for stochastic differential equations
- Numerical Solution of Stochastic Differential Equations in Finance
- Solving Ordinary Differential Equations I
- Boundary Preserving Semianalytic Numerical Algorithms for Stochastic Differential Equations
- Approximate Integration of Stochastic Differential Equations
- Mean-Square and Asymptotic Stability of the Stochastic Theta Method
- Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
- Exponential Mean-Square Stability of Numerical Solutions to Stochastic Differential Equations
- Convergence and stability of split-step theta methods with variable step-size for stochastic pantograph differential equations
- Real Options Valuation
- Preserving exponential mean square stability and decay rates in two classes of theta approximations of stochastic differential equations
- Split-step Adams–Moulton Milstein methods for systems of stiff stochastic differential equations
- Stability Analysis of Numerical Schemes for Stochastic Differential Equations
- Balanced Milstein Methods for Ordinary SDEs
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