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pro vyhledávání: '"Huh, Jeonggyu"'
Autor:
Huh, Jeonggyu
We present a neural policy optimization framework for Merton's portfolio optimization problem that is rigorously aligned with Pontryagin's Maximum Principle (PMP). Our approach employs a discrete-time, backpropagation-through-time (BPTT)-based gradie
Externí odkaz:
http://arxiv.org/abs/2412.13101
Publikováno v:
Operations Research Letters, 57:107189, 2024
Using the option delta systematically, we derive tighter lower and upper bounds of the Black-Scholes implied volatility than those in Tehranchi [SIAM J. Financ. Math. 7 (2016), 893-916]. As an application, we propose a Newton-Raphson algorithm on the
Externí odkaz:
http://arxiv.org/abs/2302.08758
In finance, implied volatility is an important indicator that reflects the market situation immediately. Many practitioners estimate volatility using iteration methods, such as the Newton--Raphson (NR) method. However, if numerous implied volatilitie
Externí odkaz:
http://arxiv.org/abs/2210.15969
In this study, we generate a large number of implied volatilities for the Stochastic Alpha Beta Rho (SABR) model using a graphics processing unit (GPU) based simulation and enable an extensive neural network to learn them. This model does not have an
Externí odkaz:
http://arxiv.org/abs/2101.09064
Akademický článek
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This study provides a consistent and efficient pricing method for both Standard & Poor's 500 Index (SPX) options and the Chicago Board Options Exchange's Volatility Index (VIX) options under a multiscale stochastic volatility model. To capture the mu
Externí odkaz:
http://arxiv.org/abs/1909.10187
Akademický článek
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Autor:
Huh, Jeonggyu
In this paper, we measure systematic risk with a new nonparametric factor model, the neural network factor model. The suitable factors for systematic risk can be naturally found by inserting daily returns on a wide range of assets into the bottleneck
Externí odkaz:
http://arxiv.org/abs/1809.04925
Autor:
Huh, Jeonggyu
In this paper, we propose the exponential Levy neural network (ELNN) for option pricing, which is a new non-parametric exponential Levy model using artificial neural networks (ANN). The ELNN fully integrates the ANNs with the exponential Levy model,
Externí odkaz:
http://arxiv.org/abs/1802.06520
Publikováno v:
In Expert Systems With Applications 1 October 2022 203
