Relevant bibliographies by topics / Continuous-time stochastic models

Academic literature on the topic 'Continuous-time stochastic models'

Author: Grafiati
Published: 10 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Continuous-time stochastic models.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Continuous-time stochastic models"

1

SÖDERSTROM, TORSTEN. "Computing stochastic continuous-time models from ARMA models." International Journal of Control 53, no. 6 (June 1991): 1311–26. http://dx.doi.org/10.1080/00207179108953677.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Comte, F., and E. Renault. "Noncausality in Continuous Time Models." Econometric Theory 12, no. 2 (June 1996): 215–56. http://dx.doi.org/10.1017/s0266466600006575.

Full text
Abstract:
In this paper, we study new definitions of noncausality, set in a continuous time framework, illustrated by the intuitive example of stochastic volatility models. Then, we define CIMA processes (i.e., processes admitting a continuous time invertible moving average representation), for which canonical representations and sufficient conditions of invertibility are given. We can provide for those CIMA processes parametric characterizations of noncausality relations as well as properties of interest for structural interpretations. In particular, we examine the example of processes solutions of stochastic differential equations, for which we study the links between continuous and discrete time definitions, find conditions to solve the possible problem of aliasing, and set the question of testing continuous time noncausality on a discrete sample of observations. Finally, we illustrate a possible generalization of definitions and characterizations that can be applied to continuous time fractional ARMA processes.
APA, Harvard, Vancouver, ISO, and other styles
3

Cvitanić, Jakša, Xuhu Wan, and Jianfeng Zhang. "Optimal contracts in continuous-time models." Journal of Applied Mathematics and Stochastic Analysis 2006 (July 12, 2006): 1–27. http://dx.doi.org/10.1155/jamsa/2006/95203.

Full text
Abstract:
We present a unified approach to solving contracting problems with full information in models driven by Brownian motion. We apply the stochastic maximum principle to give necessary and sufficient conditions for contracts that implement the so-called first-best solution. The optimal contract is proportional to the difference between the underlying process controlled by the agent and a stochastic, state-contingent benchmark. Our methodology covers a number of frameworks considered in the existing literature. The main finance applications of this theory are optimal compensation of company executives and of portfolio managers.
APA, Harvard, Vancouver, ISO, and other styles
4

Ercolani, Joanne S. "CYCLICAL TRENDS IN CONTINUOUS TIME MODELS." Econometric Theory 25, no. 4 (August 2009): 1112–19. http://dx.doi.org/10.1017/s0266466608090440.

Full text
Abstract:
It is undoubtedly desirable that econometric models capture the dynamic behavior, like trends and cycles, observed in many economic processes. Building models with such capabilities has been an important objective in the continuous time econometrics literature, for instance, the cyclical growth models of Bergstrom (1966); the economy-wide macroeconometric models of, for example, Bergstrom and Wymer (1976); unobserved stochastic trends of Harvey and Stock (1988 and 1993) and Bergstrom (1997); and differential-difference equations of Chambers and McGarry (2002). This paper considers continuous time cyclical trends, which complement the trend-plus-cycle models in the unobserved components literature but could also be incorporated into Bergstrom type systems of differential equations, as were stochastic trends in Bergstrom (1997).
APA, Harvard, Vancouver, ISO, and other styles
5

Knopov, P. S. "Some models of continuous-time stochastic approximation." Cybernetics and Systems Analysis 31, no. 6 (November 1995): 863–68. http://dx.doi.org/10.1007/bf02366623.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Wälde, Klaus. "Production technologies in stochastic continuous time models." Journal of Economic Dynamics and Control 35, no. 4 (April 2011): 616–22. http://dx.doi.org/10.1016/j.jedc.2010.10.005.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Zipkin, Paul. "Stochastic leadtimes in continuous-time inventory models." Naval Research Logistics Quarterly 33, no. 4 (November 1986): 763–74. http://dx.doi.org/10.1002/nav.3800330419.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Bergstrom, A. R. "The History of Continuous-Time Econometric Models." Econometric Theory 4, no. 3 (December 1988): 365–83. http://dx.doi.org/10.1017/s0266466600013359.

Full text
Abstract:
Although it is only during the last decade that continuous-time models have been extensively used in applied econometric work, the development of statistical methods applicable to such models commenced over 40 years ago. The first significant contribution to the problem of estimating the parameters of continuous-time stochastic models from discrete data was made by the British statistician Bartlett [1946] only three years after the pioneering contribution of Haavelmo [1943] on simultaneous equations models. Moreover, by this time the fundamental mathematical theory of continuous-time stochastic models was already well developed, major contributions having been made by some of the leading mathematicians of the twentieth century, including Einstein, Weiner, and Kolmogorov.
APA, Harvard, Vancouver, ISO, and other styles
9

Pollock, D. Stephen G. "Linear Stochastic Models in Discrete and Continuous Time." Econometrics 8, no. 3 (September 4, 2020): 35. http://dx.doi.org/10.3390/econometrics8030035.

Full text
Abstract:
The econometric data to which autoregressive moving-average models are commonly applied are liable to contain elements from a limited range of frequencies. If the data do not cover the full Nyquist frequency range of [0,π] radians, then severe biases can occur in estimating their parameters. The recourse should be to reconstitute the underlying continuous data trajectory and to resample it at an appropriate lesser rate. The trajectory can be derived by associating sinc fuction kernels to the data points. This suggests a model for the underlying processes. The paper describes frequency-limited linear stochastic differential equations that conform to such a model, and it compares them with equations of a model that is assumed to be driven by a white-noise process of unbounded frequencies. The means of estimating models of both varieties are described.
APA, Harvard, Vancouver, ISO, and other styles
10

Comte, Fabienne, and Eric Renault. "Long memory in continuous-time stochastic volatility models." Mathematical Finance 8, no. 4 (October 1998): 291–323. http://dx.doi.org/10.1111/1467-9965.00057.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Continuous-time stochastic models"

1

Parra, Rojas César. "Intrinsic fluctuations in discrete and continuous time models." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/intrinsic-fluctuations-in-discrete-and-continuous-time-models(d7006a2b-1496-44f2-8423-1f2fa72be1a5).html.

Full text
Abstract:
This thesis explores the stochastic features of models of ecological systems in discrete and in continuous time. Our interest lies in models formulated at the microscale, from which a mesoscopic description can be derived. The stochasticity present in the models, constructed in this way, is intrinsic to the systems under consideration and stems from their finite size. We start by exploring a susceptible-infectious-recovered model for epidemic spread on a network. We are interested in the case where the connectivity, or degree, of the individuals is characterised by a very broad, or heterogeneous, distribution, and in the effects of stochasticity on the dynamics, which may depart wildly from that of a homogeneous population. The model at the mesoscale corresponds to a system of stochastic differential equations with a very large number of degrees of freedom which can be reduced to a two-dimensional model in its deterministic limit. We show how this reduction can be carried over to the stochastic case by exploiting a time-scale separation in the deterministic system and carrying out a fast-variable elimination. We use simulations to show that the temporal behaviour of the epidemic obtained from the reduced stochastic model yields reasonably good agreement with the microscopic model under the condition that the maximum allowed degree that individuals can have is not too close to the population size. This is illustrated using time series, phase diagrams and the distribution of epidemic sizes. The general mesoscopic theory used in continuous-time models has only very recently been developed for discrete-time systems in one variable. Here, we explore this one-dimensional theory and find that, in contrast to the continuous-time case, large jumps can occur between successive iterates of the process, and this translates at the mesoscale into the need for specifying `boundary' conditions everywhere outside of the system. We discuss these and how to implement them in the stochastic difference equation in order to obtain results which are consistent with the microscopic model. We then extend the theoretical framework to make it applicable to systems containing an arbitrary number of degrees of freedom. In addition, we extend a number of analytical results from the one-dimensional stochastic difference equation to arbitrary dimension, for the distribution of fluctuations around fixed points, cycles and quasi-periodic attractors of the corresponding deterministic map. We also derive new expressions, describing the autocorrelation functions of the fluctuations, as well as their power spectrum. From the latter, we characterise the appearance of noise-induced oscillations in systems of dimension greater than one, which have been previously observed in continuous-time systems and are known as quasi-cycles. Finally, we explore the ability of intrinsic noise to induce chaotic behaviour in the system for parameter values for which the deterministic map presents a non-chaotic attractor; we find that this is possible for periodic, but not for quasi-periodic, states.
APA, Harvard, Vancouver, ISO, and other styles
2

Elerian, Ola. "Simulation estimation of continuous-time models with applications to finance." Thesis, University of Oxford, 1999. https://ora.ox.ac.uk/objects/uuid:9538382d-5524-416a-8a95-1b820dd795e1.

Full text
Abstract:
Over recent years, we have witnessed a rapid development in the body of economic theory with applications to finance. It has had great success in finding theoretical explanations to economic phenomena. Typically, theories are employed that are defined by mathematical models. Finance in particular has drawn upon and developed the theory of stochastic differential equations. These produce elegant and tractable frameworks which help us to better understand the world. To directly apply such theories, the models must be assessed and their parameters estimated. Implementation requires the estimation of the model's elements using statistical techniques. These fit the model to the observed data. Unfortunately, existing statistical methods do not work satisfactorily when applied to many financial models. These methods, when applied to complex models often yield inaccurate results. Consequently, simpler analytical models are often preferred, but these are typically unrealistic representations of the underlying process, given the stylised facts reported in the literature. In practical applications, data is observed at discrete intervals and a discretisation is typically used to approximate the continuous-time model. This can lead to biased estimates, since the true underlying model is assumed continuous. This thesis develops new methods to estimate these types of models, with the objective of obtaining more accurate estimates of the underlying parameters present. The methods are applicable to general models. As the solution to the true continuous process is rarely known for these applications, the methods developed rely on building an Euler-Maruyama approximate model and using simulation techniques to obtain the distribution of the unknown quantities of interest. We propose to simulate the missing paths between the observed data points to reduce the bias from the approximate model. Alternatively, one could use a more sophisticated scheme to discretise the process. Unfortunately, their implementation with simulation methods require us to simulate from the density and evaluate the density at any given point. This has until now only been possible for the Euler-Maruyama scheme. One contribution of the thesis is to show the existence of a closed form solution from use of the higher order Milstein scheme. The likelihood based method is implemented within the Bayesian paradigm, as in the context of these models, Bayesian methods are often analytically easier. Concerning the estimation methodology, emphasis is placed on simulation efficiency; design and implementation of the method directly affects the accuracy and stability of the results. In conjunction with estimation, it is important to provide inference and diagnostic procedures. Meaningful information from simulation results must be extracted and summarised. This necessitates developing techniques to evaluate the plausibility and hence the fit of a particular model for a given dataset. An important aspect of model evaluation concerns the ability to compare model fit across a range of possible alternatives. The advantage with the Bayesian framework is that it allows comparison across non-nested models. The aim of the thesis is thus to provide an efficient estimation method for these continuous-time models, that can be used to conduct meaningful inference, with their performance being assessed through the use of diagnostic tools.
APA, Harvard, Vancouver, ISO, and other styles
3

Casas, Villalba Isabel. "Statistical inference in continuous-time models with short-range and/or long-range dependence." University of Western Australia. School of Mathematics and Statistics, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0133.

Full text
Abstract:
The aim of this thesis is to estimate the volatility function of continuoustime stochastic models. The estimation of the volatility of the following wellknown international stock market indexes is presented as an application: Dow Jones Industrial Average, Standard and Poor’s 500, NIKKEI 225, CAC 40, DAX 30, FTSE 100 and IBEX 35. This estimation is studied from two different perspectives: a) assuming that the volatility of the stock market indexes displays shortrange dependence (SRD), and b) extending the previous model for processes with longrange dependence (LRD), intermediaterange dependence (IRD) or SRD. Under the efficient market hypothesis (EMH), the compatibility of the Vasicek, the CIR, the Anh and Gao, and the CKLS models with the stock market indexes is being tested. Nonparametric techniques are presented to test the affinity of these parametric volatility functions with the volatility observed from the data. Under the assumption of possible statistical patterns in the volatility process, a new estimation procedure based on the Whittle estimation is proposed. This procedure is theoretically and empirically proven. In addition, its application to the stock market indexes provides interesting results.
APA, Harvard, Vancouver, ISO, and other styles
4

Stelzer, Robert Josef. "Multivariate continuous time stochastic volatility models driven by a Lévy process." kostenfrei, 2007. http://mediatum2.ub.tum.de/doc/624065/document.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Tingström, Victor. "Sequential parameter and state learning in continuous time stochastic volatility models using the SMC² algorithm." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177104.

Full text
Abstract:
In this Master’s thesis, joint sequential inference of both parameters and states of stochastic volatility models is carried out using the SMC2 algorithm found in SMC2: an efficient algorithm for sequential analysis of state-space models, Nicolas Chopin, Pierre E. Jacob, Omiros Papaspiliopoulos. The models under study are the continuous time s.v. models (i) Heston, (ii) Bates, and (iii) SVCJ, where inference is based on options prices. It is found that the SMC2 performs well for the simpler models (i) and (ii), wheras filtering in (iii) performs worse. Furthermore, it is found that the FFT option price evaluation is the most computationally demanding step, and it is suggested to explore other avenues of computation, such as GPGPU-based computing.
I denna Masteruppsats estimeras sekventiellt parametrar och tillstånd i stokastiska volatilitetsmodeller nyttjandes SMC2 -algoritmen som återfinns i [1]. Modellerna som studeras är de kontinuerliga s.v.-modellerna (i) Heston, (ii) Bates och (iii) SVCJ, där inferens baseras på optionspriser. Vi finner att SMC2 presterar bra resultat för de enklare modellerna (i) och (ii) emedan filtrering för (iii) presterar sämre. Vi finner ytterligare att det beräkningsmässigt tyngsta steget är optionsprissättning nyttjandes FFT, därför föreslås det att undersöka andra beräkningssätt, såsom GPGPU-beräkning
APA, Harvard, Vancouver, ISO, and other styles
6

Witte, Hugh Douglas. "Markov chain Monte Carlo and data augmentation methods for continuous-time stochastic volatility models." Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/283976.

Full text
Abstract:
In this paper we exploit some recent computational advances in Bayesian inference, coupled with data augmentation methods, to estimate and test continuous-time stochastic volatility models. We augment the observable data with a latent volatility process which governs the evolution of the data's volatility. The level of the latent process is estimated at finer increments than the data are observed in order to derive a consistent estimator of the variance over each time period the data are measured. The latent process follows a law of motion which has either a known transition density or an approximation to the transition density that is an explicit function of the parameters characterizing the stochastic differential equation. We analyze several models which differ with respect to both their drift and diffusion components. Our results suggest that for two size-based portfolios of U.S. common stocks, a model in which the volatility process is characterized by nonstationarity and constant elasticity of instantaneous variance (with respect to the level of the process) greater than 1 best describes the data. We show how to estimate the various models, undertake the model selection exercise, update posterior distributions of parameters and functions of interest in real time, and calculate smoothed estimates of within sample volatility and prediction of out-of-sample returns and volatility. One nice aspect of our approach is that no transformations of the data or the latent processes, such as subtracting out the mean return prior to estimation, or formulating the model in terms of the natural logarithm of volatility, are required.
APA, Harvard, Vancouver, ISO, and other styles
7

Malloch, Hamish Jr. "The valuation of options on traded accounts: continuous and discrete time models." Thesis, The University of Sydney, 2010. http://hdl.handle.net/2123/7239.

Full text
Abstract:
In this thesis we are concerned with valuing options on traded accounts using both continuous and discrete time models. An option on a traded account is a zero strike call on the balance of a trading account which consists of a position of size $\theta$ in a risky asset (which we refer to as a stock) and the remaining wealth in a risk-free account. The choice of trading positions throughout the life of the option are made by the buyer, subject to constraints specified in the contract at the time of purchase. The specification of these trading constraints gives rise to some of the more well known examples including passport options and vacation options. At maturity, the option buyer is entitled to any positive wealth accumulated in the trading account whilst any losses are covered by the option seller. First, we examine the problem of valuing these options in continuous time. A review of some existing methods is presented, including a complete derivation of the pricing formula for the passport option and the option on a traded account following the methods proposed by Hyer et al. (1997) and Shreve and Vecer (2000), though we often use different techniques to those authors. We also present an alternative derivation for the value of a passport option using our own methodology which we believe is simpler than those currently available. Secondly, we consider the valuation problem in a discrete time setting by looking at one specific discrete time model, the binomial tree. This is a new contribution to the literature as binomial models for these options have not been previously examined. Using this approach, the greatest difficulty is the determination of an optimal trading strategy which is required to price this class of option. We show that in general, binomial models and continuous time models do not have the same trading strategy, and in fact that the analytic determination of the trading strategy for an option on a traded account may in fact be impossible to obtain. We then turn to passport options, where we are able to derive an analytic optimal strategy which in this case is identical to that used in the continuous time models, thus the problem of valuing passport options is reduced to the same computational burdens as a binomial valuation without recombining branches. Lastly, we examine some numerical methods which could be used to value options on traded accounts with binomial models. Our problem is shown to be an NP-hard convex maximisation which we convert into both an l1-norm convex maximisation and an indefinite quadratic program. Whilst we present algorithms which are guaranteed to obtain the optimal solution, they are also known to be inefficient and thus inappropriate for any likely application beyond a few time steps. We conclude by summarising our results and give directions for future research in this area.
APA, Harvard, Vancouver, ISO, and other styles
8

Tribastone, Mirco. "Scalable analysis of stochastic process algebra models." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4629.

Full text
Abstract:
The performance modelling of large-scale systems using discrete-state approaches is fundamentally hampered by the well-known problem of state-space explosion, which causes exponential growth of the reachable state space as a function of the number of the components which constitute the model. Because they are mapped onto continuous-time Markov chains (CTMCs), models described in the stochastic process algebra PEPA are no exception. This thesis presents a deterministic continuous-state semantics of PEPA which employs ordinary differential equations (ODEs) as the underlying mathematics for the performance evaluation. This is suitable for models consisting of large numbers of replicated components, as the ODE problem size is insensitive to the actual population levels of the system under study. Furthermore, the ODE is given an interpretation as the fluid limit of a properly defined CTMC model when the initial population levels go to infinity. This framework allows the use of existing results which give error bounds to assess the quality of the differential approximation. The computation of performance indices such as throughput, utilisation, and average response time are interpreted deterministically as functions of the ODE solution and are related to corresponding reward structures in the Markovian setting. The differential interpretation of PEPA provides a framework that is conceptually analogous to established approximation methods in queueing networks based on meanvalue analysis, as both approaches aim at reducing the computational cost of the analysis by providing estimates for the expected values of the performance metrics of interest. The relationship between these two techniques is examined in more detail in a comparison between PEPA and the Layered Queueing Network (LQN) model. General patterns of translation of LQN elements into corresponding PEPA components are applied to a substantial case study of a distributed computer system. This model is analysed using stochastic simulation to gauge the soundness of the translation. Furthermore, it is subjected to a series of numerical tests to compare execution runtimes and accuracy of the PEPA differential analysis against the LQN mean-value approximation method. Finally, this thesis discusses the major elements concerning the development of a software toolkit, the PEPA Eclipse Plug-in, which offers a comprehensive modelling environment for PEPA, including modules for static analysis, explicit state-space exploration, numerical solution of the steady-state equilibrium of the Markov chain, stochastic simulation, the differential analysis approach herein presented, and a graphical framework for model editing and visualisation of performance evaluation results.
APA, Harvard, Vancouver, ISO, and other styles
9

Lo, Chia Chun. "Application of continuous time Markov chain models : option pricing, term structure of interest rates and stochastic filtering." Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.496255.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Murray, Lawrence. "Bayesian learning of continuous time dynamical systems with applications in functional magnetic resonance imaging." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4157.

Full text
Abstract:
Temporal phenomena in a range of disciplines are more naturally modelled in continuous-time than coerced into a discrete-time formulation. Differential systems form the mainstay of such modelling, in fields from physics to economics, geoscience to neuroscience. While powerful, these are fundamentally limited by their determinism. For the purposes of probabilistic inference, their extension to stochastic differential equations permits a continuous injection of noise and uncertainty into the system, the model, and its observation. This thesis considers Bayesian filtering for state and parameter estimation in general non-linear, non-Gaussian systems using these stochastic differential models. It identifies a number of challenges in this setting over and above those of discrete time, most notably the absence of a closed form transition density. These are addressed via a synergy of diverse work in numerical integration, particle filtering and high performance distributed computing, engineering novel solutions for this class of model. In an area where the default solution is linear discretisation, the first major contribution is the introduction of higher-order numerical schemes, particularly stochastic Runge-Kutta, for more efficient simulation of the system dynamics. Improved runtime performance is demonstrated on a number of problems, and compatibility of these integrators with conventional particle filtering and smoothing schemes discussed. Finding compatibility for the smoothing problem most lacking, the major theoretical contribution of the work is the introduction of two novel particle methods, the kernel forward-backward and kernel two-filter smoothers. By harnessing kernel density approximations in an importance sampling framework, these attain cancellation of the intractable transition density, ensuring applicability in continuous time. The use of kernel estimators is particularly amenable to parallelisation, and provides broader support for smooth densities than a sample-based representation alone, helping alleviate the well known issue of degeneracy in particle smoothers. Implementation of the methods for large-scale problems on high performance computing architectures is provided. Achieving improved temporal and spatial complexity, highly favourable runtime comparisons against conventional techniques are presented. Finally, attention turns to real world problems in the domain of Functional Magnetic Resonance Imaging (fMRI), first constructing a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed signal in fMRI. This model and the methodological advances of the work culminate in application to the deconvolution and effective connectivity problems in this domain.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Continuous-time stochastic models"

1

Melino, Angelo. Estimation of continuous-time models in finance. Toronto: Dept. of Economics and Institute for Policy Analysis, University of Toronto, 1991.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Jianfeng, Zhang, and SpringerLink (Online service), eds. Contract Theory in Continuous-Time Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Optimal portfolios: Stochastic models for optimal investment and risk management in continuous time. Singapore: World Scientific, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Antonio, Mele, ed. Stochastic volatility in financial markets: Crossing the bridge to continuous time. Boston, Mass: Kluwer Academic Publishers, 2000.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Capasso, V. An introduction to continuous-time stochastic processes: Theory, models, and applications to finance, biology, and medicine. Boston: Birkhäuser, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Fornari, Fabio. A simple approach to the estimation of continuous time CEV stochastic volatility models of the short-term rate. [Roma]: Banca d'Italia, 2001.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

David, Bakstein, and SpringerLink (Online service), eds. An Introduction to Continuous-Time Stochastic Processes: Theory, Models, and Applications to Finance, Biology, and Medicine. 2nd ed. Boston: Birkhäuser Boston, 2012.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Bergstrom, A. R. Gaussian estimation of mixed order continuous time dynamic models with unobservable stochastic trends from mixed stock and flow data. [Colchester]: University of Essex, Department of Economics, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Vladas, Sidoravicius, and Smirnov S. (Stanislav) 1970-, eds. Probability and statistical physics in St. Petersburg: St. Petersburg School in Probability and Statistical Physics : June 18-29, 2012 : St. Petersburg State University, St. Petersburg, Russia. Providence, Rhode Island: American Mathematical Society, 2015.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Zhang, Jianfeng, and Jakša Cvitanic. Contract Theory in Continuous-Time Models. Springer, 2014.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Continuous-time stochastic models"

1

Merton, Robert C. "Continuous-Time Stochastic Models." In The New Palgrave Dictionary of Economics, 2193–98. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_286.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Merton, Robert C. "Continuous-Time Stochastic Models." In The New Palgrave Dictionary of Economics, 1–6. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1057/978-1-349-95121-5_286-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Merton, Robert C. "Continuous-time Stochastic Models." In Finance, 103–9. London: Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-20213-3_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Allen, Linda J. S. "Continuous-Time and Continuous-State Branching Processes." In Stochastic Population and Epidemic Models, 29–35. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21554-9_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Cvitanić, Jakša, and Jianfeng Zhang. "Stochastic Maximum Principle." In Contract Theory in Continuous-Time Models, 183–227. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-14200-0_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kulkarni, V. G. "Continuous-Time Markov Models." In Modeling, Analysis, Design, and Control of Stochastic Systems, 153–213. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4757-3098-2_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Érdi, Péter, and Gábor Lente. "Continuous Time Discrete State Stochastic Models." In Springer Series in Synergetics, 25–70. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0387-0_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Kushner, Harold J., and Paul Dupuis. "Review of Continuous Time Models." In Numerical Methods for Stochastic Control Problems in Continuous Time, 7–34. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0007-6_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Kushner, Harold J., and Paul G. Dupuis. "Review of Continuous Time Models." In Numerical Methods for Stochastic Control Problems in Continuous Time, 7–33. New York, NY: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4684-0441-8_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Allen, Linda J. S. "Continuous-Time and Discrete-State Branching Processes." In Stochastic Population and Epidemic Models, 1–12. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21554-9_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Continuous-time stochastic models"

1

Wang, Ximei, Hang Zhang, and Yanlong Zhao. "Parameters estimations for continuous-time stochastic volatility models." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8027703.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Fradkov, A. L. "Continuous-time averaged models of discrete-time stochastic systems: Survey and open problems." In 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011). IEEE, 2011. http://dx.doi.org/10.1109/cdc.2011.6160840.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Ahmad, Mohd Ashraf, Shun-ichi Azuma, and Toshiharu Sugie. "Identification of continuous-time Hammerstein models using Simultaneous Perturbation Stochastic Approximation." In 2014 14th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2014. http://dx.doi.org/10.1109/iccas.2014.6987545.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kulikov, Gennady Yu, and Maria V. Kulikova. "Accurate continuous-discrete extended Kalman filtering for stiff continuous-time stochastic models in chemical engineering." In 2016 European Control Conference (ECC). IEEE, 2016. http://dx.doi.org/10.1109/ecc.2016.7810540.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Thomassin, Magalie, and Rachid Malti. "Multivariable Identification of Continuous-Time Fractional System." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86975.

Full text
Abstract:
This paper presents two subspace-based methods, from the MOESP (MIMO output-error state space) family, for state-space identification of continuous-time fractional commensurate models from sampled input-output data. The methodology used in this paper involves a continuous-time fractional operator allowing to reformulate the problem so that the state-space matrices can be estimated with conventional discrete-time subspace techniques based on QR and singular value decompositions. The first method is a deterministic one whereas the second approach takes place in a stochastic context. The performance of both methods is demonstrated using Monte Carlo simulations at various signal-to-noise ratios. The deterministic method leads, as expected, to biased estimates. This bias is removed in the stochastic method by the use of an instrumental variable. As compared to rational systems, the commensurate differentiation order must be estimated besides the state-space matrices which is done using nonlinear programming. This is the first work developed for multi-input multi-output system identification using fractional models.
APA, Harvard, Vancouver, ISO, and other styles
6

Valis, D., J. Gajewski, M. Forbelska, and J. Jonak. "Degradation Assessment of Drilling Head based on Stochastic Growth Models and Continuous Time Diffusion Processes." In 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2022. http://dx.doi.org/10.1109/ieem55944.2022.9989766.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Nakamura, Masato, Hanwei Zhang, Karsten Millrath, and Nickolas J. Themelis. "Modeling of Waste-to-Energy Combustion With Continuous Variation of the Solid Waste Fuel." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-55342.

Full text
Abstract:
A mathematical model of a mass-burn, waste-to-energy combustion chamber has been developed that includes stochastic representation of the variability of the fuel (municipal solid waste, MSW). The drying, pyrolysis, gasification and combustion processes on the moving grate are governed by several factors such as proximate and ultimate analysis, particle size, moisture, heating value, and bulk density, all of which change continuously. This extreme variability has not been considered in past mathematical models of WTE combustion that used mean values of the MSW properties. The Monte Carlo stochastic method has been applied to provide a time series description of the continuous variation of solid wastes at the feed end of the traveling grate. The combustion of the solid particles on the grate is simulated using percolation theory. The feed variation and the percolation theory models are combined with the FLIC two-dimensional bed model developed by Sheffield University to project the transient phenomena in the bed, such as the break-up of waste particles and the channeling of combustion air throughout the bed, and their effects on the combustion process.
APA, Harvard, Vancouver, ISO, and other styles
8

Rincon, Luis F., Yina F. Muñoz Moscoso, Jose Campos Matos, and Stefan Leonardo Leiva Maldonado. "Stochastic degradation model analysis for prestressed concrete bridges." In IABSE Symposium, Prague 2022: Challenges for Existing and Oncoming Structures. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2022. http://dx.doi.org/10.2749/prague.2022.1092.

Full text
Abstract:
<p>Bridges in the road infrastructure represent a critical and strategic asset, due to their functionality, is vital for the economic and social development of the countries. Currently, approximately 50% of construction industry expenditures in most developed countries are associated with repairs, maintenance, and rehabilitation of existing structures, and are expected to increase in the future. In this sense, it is necessary to monitor the behaviour of bridges and obtain indicators that represent the evolution of the state of service over time.</p><p>Therefore, degradation models play a crucial role in determining asset performance that will define cost-effective and efficient planned maintenance solutions to ensure continuous and correct operation. Of these models, Markov chains stand out for being stochastic models that consider the uncertainty of complex phenomena and are the most used for structures in general due to their practicality, easy implementation, and compatibility. In this context, this research develops degradation models of a database of 414 prestressed concrete bridges continuously monitored from 2000 to 2016 in the state of Indiana, USA. Degradation models were developed from a rating system of the state of the deck, the superstructure, and the substructure. Finally, the database is identified and divided from cluster analysis, into classes that share similar deterioration trends to obtain a more accurate prediction that can facilitate the decision processes of bridge management systems.</p>
APA, Harvard, Vancouver, ISO, and other styles
9

Marcal, Pedro V., and Jeffrey T. Fong. "Continuous NDE Monitoring via Web Technology." In ASME 2008 Pressure Vessels and Piping Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/pvp2008-61574.

Full text
Abstract:
For safe operation of high-consequence structures such as airplanes, ships, trains, chemical plants, electricity-generating units, nuclear reactors, oil and gas pipelines, and pressure vessels, periodic inspection using nondestructive evaluation (NDE) technology and a deterministic approach to modeling fatigue crack growth has been mandated by government in the energy and transportation sectors of the nation’s economy since the 1970s. Recent advances in web-based computing, direct measurement-based NDE, and a stochastic approach to remaining fatigue life cycle prediction model have made it possible to not only enhance the credibility of fatigue life prediction but also shorten the turn-around time between field-based NDE and office-based modeling, analysis, verification and integrity assessment back to the field for decision making. To illustrate this new concept in preventing structural failure and extending useful life of high-consequence systems, we first recount a lesson learned in the history of the deployment of the U.S. nuclear submarine fleet, where the emphasis was on the continuous monitoring of 100% of pipe and vessel welds from their initial placement to the discovery of tangible signs of fatigue damage way before the onset of service disruption. Using two crack length vs. fatigue life cycle plots, one being based on the deterministic and the other a stochastic model, we summarize the contrast between the two models in their ability to deliver a credible prediction of the remaining fatigue life cycle based on a periodic or continuous inspection mode. In conjunction with that summary, we answer an important question in designing an NDE-based inspection strategy, namely, whether the inspection should be periodic or continuous. We show in this paper that the key to the success of a continuous monitoring system for aging structure is an NDE capability in measuring not only the initial crack length and the initial crack growth rate, but also their standard deviations. We conclude with a remark that a continuous direct-measurement-based NDE inspection system, when coupled with a finite element modeling and analysis capability, is capable of monitoring not only surface but also subsurface cracks.
APA, Harvard, Vancouver, ISO, and other styles
10

Lipowsky, Justus, and Martin Sommerfeld. "Time-Dependent Simulation of a Swirling Two Phase Flow Using an Anisotropic Turbulent Dispersion Model." In ASME 2005 Fluids Engineering Division Summer Meeting. ASMEDC, 2005. http://dx.doi.org/10.1115/fedsm2005-77210.

Full text
Abstract:
Time-dependent simulations of a particle-laden swirl flow in a pipe expansion based on the Euler-Lagrange approach are presented. Two equation and Reynolds Stress Models were used in the calculation of turbulent quantities in the continuous phase. Additional attention was payed to the influence of particle dispersion. The instantaneous fluid velocities seen by the particles was reconstructed by different dispersion models. To come to a time dependant solution for the Euler-Lagrange approach, a quasi-unsteady approach is taken. This results in a calculational scheme where one Eulerian time-step is divided in a number of Lagrangian steps. Particle source term are sampled which represent the influence of the disperse phase on the flow field. which call for additional coupling within one Eulerian time step. The effect of inter-particle collisions on the movement of the disperse phase is accounted for using a stochastic inter-particle collision model. Special interest of this study was the formation of dust ropes which are observed in such flows.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Continuous-time stochastic models' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography