Ralph Rudd
University of Cape Town
17 Papers
63 Citations
Ralph Rudd is an academic researcher from University of Cape Town. The author has contributed to research in topics: Quantization (signal processing) & Stochastic differential equation. The author has an hindex of 4, co-authored 16 publications.
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Papers
Recursive marginal quantization of higher-order schemes
TL;DR: In this paper, the authors apply quantization techniques in many challenging finance applications, including pricing claims with path dependence and early exercise features, stochastic optimal control, filtering filtering, and stochastically optimal control.
Recursive Marginal Quantization of Higher-Order Schemes
TL;DR: Recursive Marginal Quantization of the Euler scheme is proposed as an efficient numerical method for evaluating functionals of solutions of stochastic differential equations and recursively quantizing the conditional marginals of the discrete-time Euler approximation of the underlying process.
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Dynamic Initial Margin Estimation Based on Quantiles of Johnson Distributions
Thomas A. McWalter,Thomas A. McWalter,Joerg Kienitz,Joerg Kienitz,Nikolai Nowaczyk,Ralph Rudd,Sarp Kaya Acar +6 more
TL;DR: In this paper, Johnson-type distributions are fitted to conditional moments estimated using least-squares Monte Carlo simulation (the JLSMC approach) to estimate the dynamic initial margin (DIM) for general portfolios.
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Appendix: Recursive Marginal Quantization of Higher-Order Schemes
TL;DR: This document provides efficient matrix implementations for both vector quantization and the generalized recursive marginal quantization, which allows for the implementation of the higher-order discretization schemes presented in the main paper.
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•Posted Content
Fast Quantization of Stochastic Volatility Models
TL;DR: A new algorithm is proposed that allows RMQ to be applied to two-factor stochastic volatility models, which retains the efficiency of gradient-descent techniques, and a significant decrease in computational effort is achieved.
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