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Titlebook: Stochastic Processes and Financial Mathematics; Ludger Rüschendorf Textbook 2023 The Editor(s) (if applicable) and The Author(s), under ex

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楼主: Spouse
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and regression. When operating in generative mode, the memory produces solutions that in many cases allow avoiding costly re-optimizations over time. When operating in regression mode, the memory replaces costly fitness evaluations with Gaussian Mixture Regression (GMR). For proof of concept simula
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Stochastic Integration,. If one interprets . as a trading strategy and . as the price process of a security, then the stochastic integral can be understood to be the accumulated gain. The stochastic integral is constructed in a series of steps and extended to general function classes and process classes.
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Elements of Stochastic Analysis,are the partial integration formula and the Itô formula with numerous applications, e.g., to Lévy’s characterization of Brownian motion. The stochastic exponential is a solution of a fundamental stochastic differential equation and shows its importance in the characterization of equivalent measure changes (Girsanov’s theorem).
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Utility Optimization, Minimum Distance Martingale Measures, and Utility Indifference Pricing,hedging via utility functions. Furthermore, the problem of portfolio optimization is treated. Using exponential Lévy models, these methods are characterized in detail for a number of standard utility functions.
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978-3-662-64710-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE
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Stochastic Processes and Financial Mathematics978-3-662-64711-0Series ISSN 2731-3824 Series E-ISSN 2731-3832
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Mathematics Study Resourceshttp://image.papertrans.cn/s/image/878111.jpg
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Variance-Minimal Hedging,This chapter is devoted to the determination of optimal hedging strategies by the criterion of variance-minimal strategies. In incomplete market models not every claim . is hedgeable. A natural question is, therefore: How good is . hedgeable?
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