Measuring Interest Rate Risk with Embedded Option Using HPL-MC Method in Fuzzy and Stochastic Environment by Enlin Tang, Wei Du

“…Under the premise that the fluctuation of interest rate follows fuzzy stochastic process, based on the option characteristics of financial instruments with embedded option, this paper takes effective duration and effective convexity as tools to measure interest rate risk when embedded options exist, tries to choose CIR extended model as term structure model, and uses the Monte Carlo method for hybrid low deviation sequences (HPL-MC) to analyze the prepayment characteristics of MBS, a representative financial instrument with embedded options, when interest rates fluctuate; on this basis, the effectiveness of effective duration management of interest rate risk is demonstrated with asset liability management cases of commercial banks.…”
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Optimal time to intervene: The case of measles child immunization by Zuzana Chladná

“…We represent immunization rate of newborns as a stochastic process and intervention as a one-period jump of this process. …”
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Evaluation Formulas for Generalized Conditional Wiener Integrals with Drift on a Function Space by Dong Hyun Cho

“…Let C[0,t] denote a generalized Wiener space, the space of real-valued continuous functions on the interval [0,t] and define a stochastic process Y:C[0,t]×[0,t]→ℝ by Y(x,s)=∫0s‍h(u)dx(u)+a(s) for x∈C[0,t] and s∈[0,t], where h∈L2[0,t] with h≠0 a.e. and a is continuous on [0,t]. …”
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Effects of elongation delay in transcription dynamics by Xuan Zhang, Huiqin Jin, Zhuoqin Yang, Jinzhi Lei

“…This paper studies the transcription dynamics that involved the elongation delay and effects of cell division and DNA replication. The stochastic process of gene expression is modeled with delay chemical master equation with periodic coefficients, and is studied numerically through the stochastic simulation algorithm with delay. …”
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Markov Switching Model Analysis of Implied Volatility for Market Indexes with Applications to S&P 500 and DAX by Luca Di Persio, Samuele Vettori

“…In particular the volatility parameter is treated as an unobserved state variable whose value in time is given as the outcome of an unobserved, discrete-time and discrete-state, stochastic process represented by a suitable Markov chain. …”
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Evolution of Bounded Confidence Opinion in Social Networks by Hui Xie, Guangjian Li, Yongjie Yan, Sihui Shu

“…We investigate opinion dynamics as a stochastic process in social networks. We introduce the stubborn agent in order to determine the impact of network structure on the emergence of consensus. …”
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Gene function revealed at the moment of stochastic gene silencing by Shreyan Gupta, James J. Cai

“…Abstract Gene expression is a dynamic and stochastic process characterized by transcriptional bursting followed by periods of silence. …”
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A Statistical Channel Model for Stochastic Antenna Inclination Angles by Gang Liu, Ming Zhang, Yaming Bo

“…The actions of a person holding a mobile device are not a static state but can be considered as a stochastic process since users can change the way they hold the device very frequently in a short time. …”
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Analogues of Conditional Wiener Integrals with Drift and Initial Distribution on a Function Space by Dong Hyun Cho

“…Let C[0,T] denote a generalized Wiener space, the space of real-valued continuous functions on the interval [0,T], and define a stochastic process Z:C[0,T]×[0,T]→R by Z(x,t)=∫0t‍h(u)dx(u)+x(0)+a(t), for x∈C[0,T] and t∈[0,T], where h∈L2[0,T] with h≠0 a.e. and a is a continuous function on [0,T]. …”
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Analytic-Numerical Solution of Random Boundary Value Heat Problems in a Semi-Infinite Bar by M.-C. Casabán, J.-C. Cortés, B. García-Mora, L. Jódar

“…Using previous results about random ordinary differential equations, a closed form solution stochastic process is firstly obtained. Then, expectation and variance are computed. …”
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Analysis of Exchange Rates as Time-Inhomogeneous Markov Chain with Finite States by Felix O. Mettle, Lydia Pomaa Boateng, Enoch N. B. Quaye, Emmanuel Kojo Aidoo, Issah Seidu

“…Based on the assumption that, for each point in time in the future, a stochastic process will be subjected to a randomly selected transition matrix from an ergodic set of transition matrices the process was subjected to in the recent past, a methodology was proposed for analysing the long-run behaviours of time-inhomogeneous Markov chains. …”
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Evaluation of Wind-Induced Response Bounds of High-Rise Buildings Based on a Nonrandom Interval Analysis Method by Xianglei Wei, An Xu, Ruohong Zhao

“…The traditional wind-induced response analysis of high-rise buildings conventionally considers the wind load as a stationary stochastic process. That is, for a certain wind direction angle, the reference wind speed (usually refers to the mean wind speed at the building height) is assumed to be a constant corresponding to a certain return period. …”
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High-resolution fleezers reveal duplex opening and stepwise assembly by an oligomer of the DEAD-box helicase Ded1p by Eric M. Patrick, Rajeev Yadav, Kasun Senanayake, Kyle Cotter, Andrea A. Putnam, Eckhard Jankowsky, Matthew J. Comstock

“…Using high-resolution optical tweezers and fluorescence, we reveal a highly dynamic and stochastic process of multiple Ded1p protomers assembling on and unwinding an RNA duplex. …”
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Stochastic Control of Inertial Sea Wave Energy Converter by Mattia Raffero, Michele Martini, Biagio Passione, Giuliana Mattiazzo, Ermanno Giorcelli, Giovanni Bracco

“…The response of the WEC (wave energy converter) is driven by the sea-surface elevation, which is modeled by a stationary and homogeneous zero mean Gaussian stochastic process. System equations are linearized thus simplifying the numerical model of the device. …”
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Inference of a Susceptible–Infectious stochastic model by Giuseppina Albano, Virginia Giorno, Francisco Torres-Ruiz

“…Such a model was well suited to describe some classes of micro-parasitic infections in which individuals never acquired lasting immunity and over the course of the epidemic everyone eventually became infected. The stochastic process related to the deterministic model was transformable into a nonhomogeneous Wiener process so the probability distribution could be obtained. …”
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Quantitative Diagnosis of Rotor Vibration Fault Using Process Power Spectrum Entropy and Support Vector Machine Method by Cheng-Wei Fei, Guang-Chen Bai, Wen-Zhong Tang, Shuang Ma

“…To improve the diagnosis capacity of rotor vibration fault in stochastic process, an effective fault diagnosis method (named Process Power Spectrum Entropy (PPSE) and Support Vector Machine (SVM) (PPSE-SVM, for short) method) was proposed. …”
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Multiobjective Optimization Approach for Robust Bridge Damage Identification against Sensor Noise by Seung-Yong Ok, Sungmoon Jung, Junho Song

“…A major finding from this study is that the stochastic process of Pareto optimal solutions obtained in a single run not only captures the actual damage locations successfully but also provides useful information such as damage-detected ratio on the potential candidates for damage to be inspected on site. …”
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Specificity and tunability of efflux pumps: A new role for the proton gradient? by Matthew Gerry, Duncan Kirby, Boian S Alexandrov, Dvira Segal, Anton Zilman

“…We developed a set of mathematical models describing operation of efflux pumps as a discrete cyclic stochastic process across a network of states characterizing pump conformations and the presence/absence of bound ligands and protons. …”
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A Novel Mechanism-Equivalence-Based Tweedie Exponential Dispersion Process for Adaptive Degradation Modeling and Life Prediction by Jiayue Wu, Yujie Liu, Han Wang, Xiaobing Ma, Yu Zhao

“…Accurately predicting the remaining useful life (RUL) of critical mechanical components is a central challenge in reliability engineering. Stochastic processes, which are capable of modeling uncertainties, are widely used in RUL prediction. …”
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Distributed delays in a hybrid model of tumor-Immune system interplay by Giulio Caravagna, Alex Graudenzi, Alberto d’Onofrio

“…By its nature, tumor growth is an ideal object of hybrid modeling where discrete stochastic processes model low-numbers entities, and mean-field equations model abundant chemical signals. …”
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