Real-Time Derivative Pricing and Hedging with Consistent Metamodels
Published Online:26 Feb 2024https://doi.org/10.1287/ijoc.2023.0292
References
- (2010) Stochastic kriging for simulation metamodeling. Oper. Res. 58:371–382.Link, Google Scholar
- (2015) Tutorial: Simulation metamodeling. Yilmaz L, Chan WKV, Moon I, Roeder TMK, Macal C, Rossetti MD, eds. Proc. Winter Simulation Conf. (IEEE, Piscataway, NJ), 1765–1779.Google Scholar
- (1973) The pricing of options and corporate liabilities. J. Political Econom. 81:371–382.Crossref, Google Scholar
- (2006) Exact simulation of stochastic volatility and other affine jump diffusion processes. Oper. Res. 54(2):217–231.Link, Google Scholar
- (2017) Exact simulation of the SABR model. Oper. Res. 65(4):931–951.Link, Google Scholar
- (2013) Enhancing stochastic kriging metamodels with gradient estimators. Oper. Res. 61:512–528.Link, Google Scholar
- (2007) Efficient nearly orthogonal and space-filling latin hypercubes. Technometrics 49(1):45–55.Crossref, Google Scholar
- (1993) Statistics for Spatial Data (Wiley, New York).Crossref, Google Scholar
- (2022) Scientific machine learning through physics-informed neural networks: Where we are and what’s next. J. Sci. Comput. 92:88.Crossref, Google Scholar
- (1997) Conditional Monte Carlo: Gradient Estimation and Optimization Applications (Kluwer Academic Publishers, Norwell, MA).Crossref, Google Scholar
- (1991) Gradient Estimation via Perturbation Analysis (Kluwer Academic Publishers, Norwell, MA).Google Scholar
- (2003) Monte Carlo Methods in Financial Engineering (Springer, New York).Crossref, Google Scholar
- (1999) Asymptotically optimal importance sampling and stratification for pricing path-dependent options. Math. Finance 9:117–152.Crossref, Google Scholar
- (1990) Likelihood ratio gradient estimation for stochastic systems. Comm. ACM 33(10):75–84.Crossref, Google Scholar
- (2019) Offline simulation online application: A new framework of simulation-based decision making. Asia-Pacific J. Oper. Res. 36(6):223–236.Crossref, Google Scholar
- (2005) Basic properties of the schur complement. Zhang F, ed. The Schur Complement and Its Applications (Springer, Boston), 17–46.Crossref, Google Scholar
- (2018) miMLHD: Generate the optimal Latin Hypercube Design based on the miniMax criterion. https://search.r-project.org/CRAN/refmans/MOLHD/html/MOLHD-package.html.Google Scholar
- (2020) Online risk monitoring using offline simulation. INFORMS J. Comput. 32(2):356–375.Abstract, Google Scholar
- (2024) Simulation metamodel-based prediction for real-time derivative pricing and risk management. https://dx.doi.org/10.1287/ijoc.2023.0292.cd, https://github.com/INFORMSJoC/2023.0292.Google Scholar
- (1998) Efficient global optimization of expensive black-box functions. J. Global Optim. 13:455–492.Crossref, Google Scholar
- (2021) Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Nature Rev. Physics 3:422–440.Crossref, Google Scholar
- (1990) A pricing method for options based on average asset values. J. Bank. Finance 14:113–129.Crossref, Google Scholar
- (2011) Kernel estimation of the Greeks for options with discontinuous payoffs. Oper. Res. 59(1):96–108.Link, Google Scholar
- (2022) Unifying offline and online simulation for online decision-making. IISE Trans. 54(10):923–935.Crossref, Google Scholar
- (2009) Choosing the sample size of a computer experiment: A practical guide. Technometrics 51:366–376.Crossref, Google Scholar
- (1995) Exploratory designs for computational experiments. J. Statist. Planning Inference 43(3):381–402.Crossref, Google Scholar
- (2010) Stochastic Differential Equations: An Introduction with Applications (Springer, New York).Google Scholar
- (2018) A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters. Oper. Res. 66(2):487–499.Link, Google Scholar
- (2014) Gradient extrapolated stochastic kriging. ACM Trans. Modeling Comput. Simulation 24:23.Crossref, Google Scholar
- (2019) Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J. Comput. Phys. 378:686–707.Crossref, Google Scholar
- (2006) Gaussian Processes for Machine Learning (MIT Press, Cambridge, MA).Google Scholar
- (2003) Lévy Processes in Finance: Pricing Financial Derivatives (John Wiley Sons, Chichester, UK).Crossref, Google Scholar
- (2018) Enhancing stochastic kriging for queueing simulation with stylized models. IISE Trans. 50(11):943–958.Crossref, Google Scholar
- (2021) Ranking and selection with covariates for personalized decision making. INFORMS J. Comput. 32(2):356–375.Google Scholar
- (2003) Kriging for interpolation in random simulation. J. Oper. Res. Soc. 54:255–262.Crossref, Google Scholar
- (2021) Understanding and mitigating gradient flow pathologies in physics-informed neural networks. SIAM J. Sci. Comput. 43(5):3055–3081.Crossref, Google Scholar
- (1998) Orthogonal column latin hypercubes and their application in computer experiments. J. Amer. Statist. Assoc. 93(444):1430–1439.Crossref, Google Scholar
- (1999) High-performance computing in finance: The last 10 years and the next. Parallel Comput. 25:2149–2175.Crossref, Google Scholar

