The Experts below are selected from a list of 10059 Experts worldwide ranked by ideXlab platform
Markus Leippold - One of the best experts on this subject based on the ideXlab platform.
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The Valuation of American Options with Stochastic Stopping Time Constraints
Applied Mathematical Finance, 2009Co-Authors: Daniel Egloff, Markus LeippoldAbstract:This paper concerns the pricing of American Options with stochastic stopping time constraints expressed in terms of the states of a Markov process. Following the ideas of Menaldi et al., we transform the constrained into an unconstrained optimal stopping problem. The transformation replaces the original payoff by the value of a generalized Barrier Option. We also provide a Monte Carlo method to numerically calculate the Option value for multidimensional Markov processes. We adapt the Longstaff-Schwartz algorithm to solve the stochastic Cauchy-Dirichlet problem related to the valuation problem of the Barrier Option along a set of simulated trajectories of the underlying Markov process.
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American Options with Stopping Time Constraints
SSRN Electronic Journal, 2005Co-Authors: Daniel Egloff, Markus Leippold, Walter FarkasAbstract:This paper concerns the pricing of American Options with stochastic stopping time constraints expressed in terms of the states of a Markov process. Following the ideas of Menaldi, Robin and Sun [21] we transform the constrained into an unconstrained optimal stopping problem. The transformation replaces the original payoff by the value of a generalized Barrier Option. We suggest a new Monte Carlo method to numerically calculate the Option value also for multidimensional Markov processes. Because of presence of stopping time constraints the classical Longstaff-Schwartz least-square Monte Carlo algorithm or its extension introduced in [7] cannot be directly applied. We adapt the Longstaff-Schwartz algorithm to solve the stochastic Cauchy-Dirichlet problem related to the valuation problem of the Barrier Option along a set of simulated trajectories of the underlying Markov process.
Daniel Egloff - One of the best experts on this subject based on the ideXlab platform.
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The Valuation of American Options with Stochastic Stopping Time Constraints
Applied Mathematical Finance, 2009Co-Authors: Daniel Egloff, Markus LeippoldAbstract:This paper concerns the pricing of American Options with stochastic stopping time constraints expressed in terms of the states of a Markov process. Following the ideas of Menaldi et al., we transform the constrained into an unconstrained optimal stopping problem. The transformation replaces the original payoff by the value of a generalized Barrier Option. We also provide a Monte Carlo method to numerically calculate the Option value for multidimensional Markov processes. We adapt the Longstaff-Schwartz algorithm to solve the stochastic Cauchy-Dirichlet problem related to the valuation problem of the Barrier Option along a set of simulated trajectories of the underlying Markov process.
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American Options with Stopping Time Constraints
SSRN Electronic Journal, 2005Co-Authors: Daniel Egloff, Markus Leippold, Walter FarkasAbstract:This paper concerns the pricing of American Options with stochastic stopping time constraints expressed in terms of the states of a Markov process. Following the ideas of Menaldi, Robin and Sun [21] we transform the constrained into an unconstrained optimal stopping problem. The transformation replaces the original payoff by the value of a generalized Barrier Option. We suggest a new Monte Carlo method to numerically calculate the Option value also for multidimensional Markov processes. Because of presence of stopping time constraints the classical Longstaff-Schwartz least-square Monte Carlo algorithm or its extension introduced in [7] cannot be directly applied. We adapt the Longstaff-Schwartz algorithm to solve the stochastic Cauchy-Dirichlet problem related to the valuation problem of the Barrier Option along a set of simulated trajectories of the underlying Markov process.
Kaixiang Liu - One of the best experts on this subject based on the ideXlab platform.
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american Barrier Option pricing formulas for stock model in uncertain environment
IEEE Access, 2019Co-Authors: Rong Gao, Kaixiang LiuAbstract:In the foundation of uncertainty theory, uncertain stock model has been put forward to portray the price fluctuation of stocks in a market with uncertain information. In this paper, the model is depicted by uncertain differential equations involved by a Liu process that is a sequence of uncertain variables varying with time. According to this model, we mainly investigate the formulas to price the American Barrier Option for rights of buying or selling the stock with a set price in the uncertain financial market. Then, four new types of concepts are introduced that are, respectively, American call Options, including both up-and-in and down-and-out, and American put Options, including both down-and-in and up-and-out. Moreover, several formulas are derived for giving the price of the corresponding four types of Options. At the same time, some examples are given.
Zhongfeng Qin - One of the best experts on this subject based on the ideXlab platform.
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Barrier Option pricing formulas of an uncertain stock model
Fuzzy Optimization and Decision Making, 2020Co-Authors: Kai Yao, Zhongfeng QinAbstract:As applications of the uncertainty theory to finance, uncertain stock models have been presented to describe the prices of stocks strongly influenced by human uncertainty. So far, large progress has been achieved on pricing problems of path-independent Options of the uncertain stock models. This paper investigates a type of path-dependent exotic Options of an uncertain stock model which are named Barrier Options. Pricing formulas are derived based on the structure of the solutions of uncertain differential equations, and numerical algorithms are designed to calculate the prices of the Barrier Options based on these formulas.
Rong Gao - One of the best experts on this subject based on the ideXlab platform.
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geometric asian Barrier Option pricing formulas of uncertain stock model
Chaos Solitons & Fractals, 2020Co-Authors: Rong Gao, Chao Lang, Liying LangAbstract:Abstract In the high-risk modern financial market, Option is an effective tool to hedge the risks caused by uncertain demand, the fluctuation of price and foreign exchange rate, because the Option can provide the holder with an entitlement to sell or purchase an asset with an exercise price. The acquisition of this entitlement requires the investor to pay Option fee, which raises the Option pricing issue. This article analyzes how to price Geometric Asian Barrier Option for uncertain stock model, where Barrier Option becomes activated or inactivated depending on whether a given Barrier level is hit. Here, we suppose that stock price obeys an uncertain differential equation, based on which the pricing formulas of Geometric Asian Barrier Option are discovered. Furthermore, to express how to use the pricing formulas to calculate corresponding Option prices, some numerical examples are given.
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american Barrier Option pricing formulas for stock model in uncertain environment
IEEE Access, 2019Co-Authors: Rong Gao, Kaixiang LiuAbstract:In the foundation of uncertainty theory, uncertain stock model has been put forward to portray the price fluctuation of stocks in a market with uncertain information. In this paper, the model is depicted by uncertain differential equations involved by a Liu process that is a sequence of uncertain variables varying with time. According to this model, we mainly investigate the formulas to price the American Barrier Option for rights of buying or selling the stock with a set price in the uncertain financial market. Then, four new types of concepts are introduced that are, respectively, American call Options, including both up-and-in and down-and-out, and American put Options, including both down-and-in and up-and-out. Moreover, several formulas are derived for giving the price of the corresponding four types of Options. At the same time, some examples are given.
