In nuclear power plants, the loss-of-coolant accident (LOCA) stands out as the most prevalent and consequential incident. Accurate breach size diagnosis is crucial for the mitigation of LOCAs, and identifying the caus...
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In nuclear power plants, the loss-of-coolant accident (LOCA) stands out as the most prevalent and consequential incident. Accurate breach size diagnosis is crucial for the mitigation of LOCAs, and identifying the cause of an accident can prevent catastrophic consequences. Traditional methods mostly focus on combining model algorithms and utilize intricate composite model neural network architectures. However, it is crucial to investigate whether greater complexity necessarily leads to better performance. In addition, the consideration of the impact of dataset construction and data preprocessing on model performance is also needed for model building. This paper proposes a framework named DeepLOCA-lattice to experiment with different preprocessing approaches to fundamental deep learning models for a comprehensive analysis of the diagnosis of LOCA breach size. The DeepLOCA-lattice involves data preprocessing via the lattice algorithm and equal-interval partitioning and deep-learning-based models, including the multi-layer perceptron (MLP), recurrent neural networks (RNNs), convolutional neural networks (CNNs), and the transformer model in LOCA breach size diagnosis. After conducting rigorous ablation experiments, we have discovered that even rudimentary foundational models can achieve accuracy rates that exceed 90%. This is a significant improvement when compared to the previous models, which yield an accuracy rate of lower than 50%. The results interestingly demonstrate the superior performance and efficacy of the fundamental deep learning model, with an effective dataset construction approach. It elucidates the presence of a complex interplay among diagnostic scales, sliding window size, and sliding stride. Furthermore, our investigation reveals that the model attains its highest accuracy within the discussed range when utilizing a smaller sliding stride size and a longer sliding window length. This study could furnish valuable insights for constructing models for LO
In this study, we consider option pricing under a Markov regime-switching GARCH-jump (RS-GARCH-jump) model. More specifically, we derive the risk neutral dynamics and propose a lattice algorithm to price European and ...
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In this study, we consider option pricing under a Markov regime-switching GARCH-jump (RS-GARCH-jump) model. More specifically, we derive the risk neutral dynamics and propose a lattice algorithm to price European and American options in this framework. We also provide a method of parameter estimation in our RS-GARCH-jump setting using historical data on the underlying time series. To measure the pricing performance of the proposed algorithm, we investigate the convergence of the tree-based results to the true option values and show that this algorithm exhibits good convergence. By comparing the pricing results of RS-GARCH-jump model with regime-switching GARCH (RS-GARCH) model, GARCH-jump model, GARCH model, Black-Scholes (BS) model, and Regime-Switching (RS) model, we show that accommodating jump effect and regime switching substantially changes the option prices. The empirical results also show that the RS-GARCH-jump model performs well in explaining option prices and confirm the importance of allowing for both jump components and regime switching.
Recent development of medical information technology uses personal health record (PHR) system, which allows the patients to create, store and share their own health information with doctors, nurses, health insurance p...
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Recent development of medical information technology uses personal health record (PHR) system, which allows the patients to create, store and share their own health information with doctors, nurses, health insurance providers, and family members. However, it has the security and privacy issues. The secret key generation is the major task by performing different algorithms on attribute based encryption (ABE) technique. This method helps to identify the trusted authority using secret key verification on the decryption process. The revocation scheme is performed to reduce the attributes for improving the performance. The drawback of existing method is overcome by the proposed system in which the PHR file is securely accessed by performing enhanced encryption and decryption of ABE technique. Here the matrix based lattice algorithm is proposed with bit plane transformation of decomposition matrices. Attribute reduction and secret key encryption is performed to improve the result of reliability, security, and scalability. The plain text is created to cipher text as key and it holds the encrypted PHR file on the cloud storage, which is retrieved only by the trusted authority. The proposed method is analyzed and compared with the existing work and achieves greater results than most of the recent related literature.
In this paper an efficient stochastic lattice approach is developed to price the American-style volatility options on the general stochastic volatility models. The stochastic volatility diffusion models are first disc...
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In this paper an efficient stochastic lattice approach is developed to price the American-style volatility options on the general stochastic volatility models. The stochastic volatility diffusion models are first discretized into forms that are amenable for designing the lattice approach, then the paths of the underlying volatility are generated by the lattice, and finally the valuation of the American volatility options is realized by the backward processes. One of the keys to the designing of the lattice approach is to derive the probability distributions of the underlying volatility on the lattice-nodes. Numerical analysis is given to confirm the accuracy of the pricing methods. Also some empirical applications are provided in the paper. (C) 2015 Elsevier B.V. All rights reserved.
This paper presents a lattice algorithm for pricing both European- and American-style moving average barrier options (MABOs). We develop a finite-dimensional partial differential equation (PDE) model for discretely mo...
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This paper presents a lattice algorithm for pricing both European- and American-style moving average barrier options (MABOs). We develop a finite-dimensional partial differential equation (PDE) model for discretely monitored MABOs and solve it numerically by using a forward shooting grid method. The modeling PDE for continuously monitored MABOs has infinite dimensions and cannot be solved directly by any existing numerical method. We find their approximate values indirectly by using an extrapolation technique with the prices of discretely monitored MABOs. Numerical experiments show that our algorithm is very efficient. (C) 2009 Elsevier B.V. All rights reserved.
We approximate d-variate functions from weighted Korobov spaces with the error of approximation defined in the L (a) sense. We study lattice algorithms and consider the worst-case setting in which the error is defined...
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We approximate d-variate functions from weighted Korobov spaces with the error of approximation defined in the L (a) sense. We study lattice algorithms and consider the worst-case setting in which the error is defined by its worst-case behavior over the unit ball of the space of functions. A lattice algorithm is specified by a generating (integer) vector. We propose three choices of such vectors, each corresponding to a different search criterion in the component-by-component construction. We present worst-case error bounds that go to zero polynomially with n (-1), where n is the number of function values used by the lattice algorithm. Under some assumptions on the weights of the function space, the worst-case error bounds are also polynomial in d, in which case we have (polynomial) tractability, or even independent of d, in which case we have strong (polynomial) tractability. We discuss the exponents of n (-1) and stress that we do not know if these exponents can be improved.
Ritchken and Trevor (1999) proposed a lattice approach for pricing American options under discrete time-varying volatility GARCH frameworks. Even though the lattice approach worked well for the pricing of the GARCH op...
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Ritchken and Trevor (1999) proposed a lattice approach for pricing American options under discrete time-varying volatility GARCH frameworks. Even though the lattice approach worked well for the pricing of the GARCH options, it was inappropriate when the option price was computed on the lattice using standard backward recursive procedures, even if the concepts of Cakici and Topyan (2000) were incorporated. This paper shows how to correct the deficiency and that with our adjustment, the lattice method performs properly for option pricing under the GARCH process.
This paper addresses the stochastic differential utility (SDU) version of the issue raised by Barrieu and El Karoui (Quantitative Finance, 2: 181-188, 2002a) in which optimal risk transfer from a bank to an investor, ...
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This paper addresses the stochastic differential utility (SDU) version of the issue raised by Barrieu and El Karoui (Quantitative Finance, 2: 181-188, 2002a) in which optimal risk transfer from a bank to an investor, realized by transacting well-designed derivatives written on relevant illiquid assets, was mainly studied in two cases with and without an available financial market. From a stochastic maximum principle as described in Yong and Zhou (Stochastic controls: Hamiltonian systems and HJB equations. Springer-Verlag, New York, 1999) we shall derive necessary and sufficient conditions for optimality in several SDU-based maximization problems. It is also shown that the optimal risk transfer, consumptions, investment policies of both agents are characterized by a forward-backward stochastic differential equation (FBSDE) system.
作者：
Nakamura, NobuhiroHitotsubashi University
Graduate School of International Corporate Strategy National Center of Sciences Chiyoda-ku Tokyo 101-8439 2-1-2 Hitotsubashi Japan
In this paper employing two heuristic numerical schemes, we study the asset pricing models with stochastic differential utility (SDU), which is formulated by either of backward stochastic differential equations (BSDEs...
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