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Journal articles on the topic 'Multivariate Lévy models'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Jacod, Jean, and Mark Podolskij. "On the minimal number of driving Lévy motions in a multivariate price model." Journal of Applied Probability 55, no. 3 (2018): 823–33. http://dx.doi.org/10.1017/jpr.2018.52.

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Abstract In this paper we consider the factor analysis for Lévy-driven multivariate price models with stochastic volatility. Our main aim is to provide conditions on the volatility process under which we can possibly reduce the dimension of the driving Lévy motion. We find that these conditions depend on a particular form of the multivariate Lévy process. In some settings we concentrate on nondegenerate symmetric α-stable Lévy motions.

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2

Ballotta, Laura, and Efrem Bonfiglioli. "Multivariate asset models using Lévy processes and applications." European Journal of Finance 22, no. 13 (2014): 1320–50. http://dx.doi.org/10.1080/1351847x.2013.870917.

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3

Panov, Vladimir. "Series Representations for Multivariate Time-Changed Lévy Models." Methodology and Computing in Applied Probability 19, no. 1 (2015): 97–119. http://dx.doi.org/10.1007/s11009-015-9461-8.

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4

Avanzi, Benjamin, Jamie Tao, Bernard Wong, and Xinda Yang. "Capturing non-exchangeable dependence in multivariate loss processes with nested Archimedean Lévy copulas." Annals of Actuarial Science 10, no. 1 (2015): 87–117. http://dx.doi.org/10.1017/s1748499515000135.

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AbstractThe class of spectrally positive Lévy processes is a frequent choice for modelling loss processes in areas such as insurance or operational risk. Dependence between such processes (e.g. between different lines of business) can be modelled with Lévy copulas. This approach is a parsimonious, efficient and flexible method which provides many of the advantages akin to distributional copulas for random variables. Literature on Lévy copulas seems to have primarily focussed on bivariate processes. When multivariate settings are considered, these usually exhibit an exchangeable dependence stru

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5

Fasen, Vicky. "Limit Theory for High Frequency Sampled MCARMA Models." Advances in Applied Probability 46, no. 3 (2014): 846–77. http://dx.doi.org/10.1239/aap/1409319563.

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We consider a multivariate continuous-time ARMA (MCARMA) process sampled at a high-frequency time grid {hn, 2hn,…, nhn}, where hn ↓ 0 and nhn → ∞ as n → ∞, or at a constant time grid where hn = h. For this model, we present the asymptotic behavior of the properly normalized partial sum to a multivariate stable or a multivariate normal random vector depending on the domain of attraction of the driving Lévy process. Furthermore, we derive the asymptotic behavior of the sample variance. In the case of finite second moments of the driving Lévy process the sample variance is a consistent estimator.

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Moser, Martin, and Robert Stelzer. "Tail behavior of multivariate lévy-driven mixed moving average processes and supOU Stochastic Volatility Models." Advances in Applied Probability 43, no. 4 (2011): 1109–35. http://dx.doi.org/10.1239/aap/1324045701.

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Multivariate Lévy-driven mixed moving average (MMA) processes of the type Xt = ∬f(A, t - s)Λ(dA, ds) cover a wide range of well known and extensively used processes such as Ornstein-Uhlenbeck processes, superpositions of Ornstein-Uhlenbeck (supOU) processes, (fractionally integrated) continuous-time autoregressive moving average processes, and increments of fractional Lévy processes. In this paper we introduce multivariate MMA processes and give conditions for their existence and regular variation of the stationary distributions. Furthermore, we study the tail behavior of multivariate supOU pr

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Moser, Martin, and Robert Stelzer. "Tail behavior of multivariate lévy-driven mixed moving average processes and supOU Stochastic Volatility Models." Advances in Applied Probability 43, no. 04 (2011): 1109–35. http://dx.doi.org/10.1017/s0001867800005322.

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Multivariate Lévy-driven mixed moving average (MMA) processes of the type X t = ∬f(A, t - s)Λ(dA, ds) cover a wide range of well known and extensively used processes such as Ornstein-Uhlenbeck processes, superpositions of Ornstein-Uhlenbeck (supOU) processes, (fractionally integrated) continuous-time autoregressive moving average processes, and increments of fractional Lévy processes. In this paper we introduce multivariate MMA processes and give conditions for their existence and regular variation of the stationary distributions. Furthermore, we study the tail behavior of multivariate supOU p

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8

Fasen, Vicky. "Limit Theory for High Frequency Sampled MCARMA Models." Advances in Applied Probability 46, no. 03 (2014): 846–77. http://dx.doi.org/10.1017/s0001867800007400.

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We consider a multivariate continuous-time ARMA (MCARMA) process sampled at a high-frequency time grid {h n , 2h n ,…, nh n }, where h n ↓ 0 and nh n → ∞ as n → ∞, or at a constant time grid where h n = h. For this model, we present the asymptotic behavior of the properly normalized partial sum to a multivariate stable or a multivariate normal random vector depending on the domain of attraction of the driving Lévy process. Furthermore, we derive the asymptotic behavior of the sample variance. In the case of finite second moments of the driving Lévy process the sample variance is a consistent e

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9

JEVTIĆ, PETAR, MARINA MARENA, and PATRIZIA SEMERARO. "MULTIVARIATE MARKED POISSON PROCESSES AND MARKET RELATED MULTIDIMENSIONAL INFORMATION FLOWS." International Journal of Theoretical and Applied Finance 22, no. 02 (2019): 1850058. http://dx.doi.org/10.1142/s0219024918500589.

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The class of marked Poisson processes and its connection with subordinated Lévy processes allow us to propose a new interpretation of multidimensional information flows and their relation to market movements. The new approach provides a unified framework for multivariate asset return models in a Lévy economy. In fact, we are able to recover several processes commonly used to model asset returns as subcases. We consider a first application example using the normal inverse Gaussian specification.

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10

Fink, Holger. "Conditional Characteristic Functions of Molchan-Golosov Fractional Lévy Processes with Application to Credit Risk." Journal of Applied Probability 50, no. 4 (2013): 983–1005. http://dx.doi.org/10.1239/jap/1389370095.

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Molchan-Golosov fractional Lévy processes (MG-FLPs) are introduced by way of a multivariate componentwise Molchan-Golosov transformation based on an n-dimensional driving Lévy process. Using results of fractional calculus and infinitely divisible distributions, we are able to calculate the conditional characteristic function of integrals driven by MG-FLPs. This leads to important predictions concerning multivariate fractional Brownian motion, fractional subordinators, and general fractional stochastic differential equations. Examples are the fractional Lévy Ornstein-Uhlenbeck and Cox-Ingersoll

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11

Fink, Holger. "Conditional Characteristic Functions of Molchan-Golosov Fractional Lévy Processes with Application to Credit Risk." Journal of Applied Probability 50, no. 04 (2013): 983–1005. http://dx.doi.org/10.1017/s0021900200013759.

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Molchan-Golosov fractional Lévy processes (MG-FLPs) are introduced by way of a multivariate componentwise Molchan-Golosov transformation based on ann-dimensional driving Lévy process. Using results of fractional calculus and infinitely divisible distributions, we are able to calculate the conditional characteristic function of integrals driven by MG-FLPs. This leads to important predictions concerning multivariate fractional Brownian motion, fractional subordinators, and general fractional stochastic differential equations. Examples are the fractional Lévy Ornstein-Uhlenbeck and Cox-Ingersoll-

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12

Ballotta, Laura, Gianluca Fusai, Angela Loregian, and M. Fabricio Perez. "Estimation of Multivariate Asset Models with Jumps." Journal of Financial and Quantitative Analysis 54, no. 5 (2018): 2053–83. http://dx.doi.org/10.1017/s0022109018001321.

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We propose a consistent and computationally efficient 2-step methodology for the estimation of multidimensional non-Gaussian asset models built using Lévy processes. The proposed framework allows for dependence between assets and different tail behaviors and jump structures for each asset. Our procedure can be applied to portfolios with a large number of assets because it is immune to estimation dimensionality problems. Simulations show good finite sample properties and significant efficiency gains. This method is especially relevant for risk management purposes such as, for example, the compu

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13

MICHAELSEN, MARKUS. "INFORMATION FLOW DEPENDENCE IN FINANCIAL MARKETS." International Journal of Theoretical and Applied Finance 23, no. 05 (2020): 2050029. http://dx.doi.org/10.1142/s0219024920500296.

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In response to empirical evidence, we propose a continuous-time model for multivariate asset returns with a two-layered dependence structure. The price process is subject to multivariate information arrivals driving the market activity modeled by nondecreasing pure-jump Lévy processes. A Lévy copula determines the jump dependence and allows for a generic multivariate information flow with a flexible structure. Conditional on the information flow, asset returns are jointly normal. Within this setup, we provide an estimation framework based on maximum simulated likelihood. We apply novel multiva

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14

Luciano, Elisa, and Patrizia Semeraro. "Multivariate time changes for Lévy asset models: Characterization and calibration." Journal of Computational and Applied Mathematics 233, no. 8 (2010): 1937–53. http://dx.doi.org/10.1016/j.cam.2009.08.119.

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15

MARENA, MARINA, ANDREA ROMEO, and PATRIZIA SEMERARO. "MULTIVARIATE FACTOR-BASED PROCESSES WITH SATO MARGINS." International Journal of Theoretical and Applied Finance 21, no. 01 (2018): 1850005. http://dx.doi.org/10.1142/s021902491850005x.

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We introduce a class of multivariate factor-based processes with the dependence structure of Lévy [Formula: see text]-models and Sato marginal distributions. We focus on variance gamma and normal inverse Gaussian marginal specifications for their analytical tractability and fit properties. We explore if Sato models, whose margins incorporate more realistic moments term structures, preserve the correlation flexibility in fitting option data. Since [Formula: see text]-models incorporate nonlinear dependence, we also investigate the impact of Sato margins on nonlinear dependence and its evolution

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16

GUILLAUME, FLORENCE. "MULTIVARIATE OPTION PRICING MODELS WITH LÉVY AND SATO VG MARGINAL PROCESSES." International Journal of Theoretical and Applied Finance 21, no. 02 (2018): 1850007. http://dx.doi.org/10.1142/s0219024918500073.

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Pricing and hedging of financial instruments whose payoff depends on the joint realization of several underlyings (basket options, spread options, etc.) require multivariate models that are, at the same time, computationally tractable and flexible enough to accommodate the stylized facts of asset returns and of their dependence structure. Among the most popular models one finds models with VG marginals. The aim of this paper is to compare four multivariate models that are characterized by VG laws at unit time and to assess their performance by considering the flexibility they offer to calibrat

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17

MARFÈ, ROBERTO. "A MULTIVARIATE PURE-JUMP MODEL WITH MULTI-FACTORIAL DEPENDENCE STRUCTURE." International Journal of Theoretical and Applied Finance 15, no. 04 (2012): 1250028. http://dx.doi.org/10.1142/s0219024912500288.

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In this work we propose a new approach to build multivariate pure jump processes. We introduce linear and nonlinear dependence, without restrictions on marginal properties, by imposing a multi-factorial structure separately on both positive and negative jumps. Such a new approach provides higher flexibility in calibrating nonlinear dependence than in other comparable Lévy models in the literature. Using the notion of multivariate subordinator, this modeling approach can be applied to the class of univariate Lévy processes which can be written as the difference of two subordinators. A common ex

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18

Ivanov, Roman V., and Katsunori Ano. "On exact pricing of FX options in multivariate time-changed Lévy models." Review of Derivatives Research 19, no. 3 (2016): 201–16. http://dx.doi.org/10.1007/s11147-016-9120-4.

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19

Gardini, Matteo, Piergiacomo Sabino, and Emanuela Sasso. "Correlating Lévy processes with self-decomposability: applications to energy markets." Decisions in Economics and Finance 44, no. 2 (2021): 1253–80. http://dx.doi.org/10.1007/s10203-021-00352-9.

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AbstractBased on the concept of self-decomposability, we extend some recent multidimensional Lévy models built using multivariate subordination. Our aim is to construct multivariate Lévy processes that can model the propagation of the systematic risk in dependent markets with some stochastic delay instead of affecting all the markets at the same time. To this end, we extend some known approaches keeping their mathematical tractability, study the properties of the new processes, derive closed-form expressions for their characteristic functions and detail how Monte Carlo schemes can be implement

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20

Lee, Mei-Ling Ting, and George A. Whitmore. "Multivariate Threshold Regression Models with Cure Rates: Identification and Estimation in the Presence of the Esscher Property." Stats 5, no. 1 (2022): 172–89. http://dx.doi.org/10.3390/stats5010012.

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The first hitting time of a boundary or threshold by the sample path of a stochastic process is the central concept of threshold regression models for survival data analysis. Regression functions for the process and threshold parameters in these models are multivariate combinations of explanatory variates. The stochastic process under investigation may be a univariate stochastic process or a multivariate stochastic process. The stochastic processes of interest to us in this report are those that possess stationary independent increments (i.e., Lévy processes) as well as the Esscher property. T

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21

MARAZZINA, DANIELE, OLEG REICHMANN, and CHRISTOPH SCHWAB. "hp-DGFEM FOR KOLMOGOROV–FOKKER–PLANCK EQUATIONS OF MULTIVARIATE LÉVY PROCESSES." Mathematical Models and Methods in Applied Sciences 22, no. 01 (2012): 1150005. http://dx.doi.org/10.1142/s0218202512005897.

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We analyze the discretization of nonlocal degenerate integrodifferential equations arising as so-called forward equations for jump-diffusion processes. Such equations arise in option pricing problems when the stochastic dynamics of the markets is modeled by Lévy driven stochastic volatility models. Well-posedness of the arising equations is addressed. We develop and analyze stable discretization schemes, in particular the discontinuous Galerkin Finite Element Methods (DG-FEM). In the DG-FEM, a new regularization of hypersingular integrals in the Dirichlet form of the pure jump part of infinite

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22

Schlemm, Eckhard, and Robert Stelzer. "Quasi maximum likelihood estimation for strongly mixing state space models and multivariate Lévy-driven CARMA processes." Electronic Journal of Statistics 6 (2012): 2185–234. http://dx.doi.org/10.1214/12-ejs743.

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23

Mai, Jan-Frederik. "The de Finetti structure behind some norm-symmetric multivariate densities with exponential decay." Dependence Modeling 8, no. 1 (2020): 210–20. http://dx.doi.org/10.1515/demo-2020-0012.

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AbstractWe derive a sufficient condition on the symmetric norm ||·|| such that the probability distribution associated with the density function f (x) ∝exp(−λ ||x||) is conditionally independent and identically distributed in the sense of de Finetti’s seminal theorem. The criterion is mild enough to comprise the ℓp-norms as special cases, in which f is shown to correspond to a polynomially tilted stable mixture of products of transformed Gamma densities. In another special case of interest f equals the density of a time-homogeneous load sharing model, popular in reliability theory, whose motiv

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24

ALFEUS, MESIAS, and ERIK SCHLÖGL. "ON SPREAD OPTION PRICING USING TWO-DIMENSIONAL FOURIER TRANSFORM." International Journal of Theoretical and Applied Finance 22, no. 05 (2019): 1950023. http://dx.doi.org/10.1142/s0219024919500237.

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Spread options are multi-asset options with payoffs dependent on the difference of two underlying financial variables. In most cases, analytically closed form solutions for pricing such payoffs are not available, and the application of numerical pricing methods turns out to be nontrivial. We consider several such nontrivial cases and explore the performance of the highly efficient numerical technique of Hurd & Zhou[(2010) A Fourier transform method for spread option pricing, SIAM J. Financial Math. 1(1), 142–157], comparing this with Monte Carlo simulation and the lower bound approximation

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25

Yoshioka, Hidekazu. "Fitting a superposition of Ornstein–Uhlenbeck process to time series of discharge in a perennial river environment." ANZIAM Journal 63 (June 28, 2022): C84—C96. http://dx.doi.org/10.21914/anziamj.v63.16985.

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Classical Ornstein–Uhlenbeck (ou) processes are Lévy-driven linear stochastic models with exponentially decaying autocorrelation functions which do not always fit more slowly decaying real time series data. A superposition of ou processes (known as a supou process) is proposed to overcome this issue for application to river discharge time series data. The discharge data has a sub-exponential autocorrelation function and this is captured by the supou process based on the mean reversion speed generated by a Gamma distribution. All the parameters of the supou process are identified by matching th

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26

Zhao, Yiming, Shu-Chuan Chu, Ali Riza Yildiz, and Jeng-Shyang Pan. "Optimized Multiple Regression Prediction Strategies with Applications." Symmetry 17, no. 7 (2025): 1085. https://doi.org/10.3390/sym17071085.

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As a classical statistical method, multiple regression is widely used for forecasting tasks in power, medicine, finance, and other fields. The rise of machine learning has led to the adoption of neural networks, particularly Long Short-Term Memory (LSTM) models, for handling complex forecasting problems, owing to their strong ability to capture temporal dependencies in sequential data. Nevertheless, the performance of LSTM models is highly sensitive to hyperparameter configuration. Traditional manual tuning methods suffer from inefficiency, excessive reliance on expert experience, and poor gen

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27

MAI, JAN-FREDERIK, and MATTHIAS SCHERER. "A TRACTABLE MULTIVARIATE DEFAULT MODEL BASED ON A STOCHASTIC TIME-CHANGE." International Journal of Theoretical and Applied Finance 12, no. 02 (2009): 227–49. http://dx.doi.org/10.1142/s0219024909005208.

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A stochastic time-change is applied to introduce dependence to a portfolio of credit-risky assets whose default times are modeled as random variables with arbitrary distribution. The dependence structure of the vector of default times is completely separated from its marginal default probabilities, making the model analytically tractable. This separation is achieved by restricting the time-change to suitable Lévy subordinators which preserve the marginal distributions. Jump times of the Lévy subordinator are interpreted as times of excess default clustering. Relevant for practical implementati

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28

Rüschendorf, Ludger, and Viktor Wolf. "Cost-efficiency in multivariate Lévy models." Dependence Modeling 3, no. 1 (2015). http://dx.doi.org/10.1515/demo-2015-0001.

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AbstractIn this paper we determine lowest cost strategies for given payoff distributions called cost-efficient strategies in multivariate exponential Lévy models where the pricing is based on the multivariate Esscher martingale measure. This multivariate framework allows to deal with dependent price processes as arising in typical applications. Dependence of the components of the Lévy Process implies an influence even on the pricing of efficient versions of univariate payoffs.We state various relevant existence and uniqueness results for the Esscher parameter and determine cost efficient strat

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29

Amici, Giovanni, Paolo Brandimarte, Francesco Messeri, and Patrizia Semeraro. "Multivariate Lévy models: calibration and pricing." OR Spectrum, April 11, 2025. https://doi.org/10.1007/s00291-025-00815-0.

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Abstract The goal of this paper is to investigate how the marginal and dependence structures of a variety of multivariate Lévy models affect calibration and pricing. To this aim, we study the approaches of Luciano and Semeraro (J Comput Appl Math 233:1937–1953, 2010) and Ballotta and Bonfiglioli (Eur J Financ 22:1320–1350, 2016) to construct multivariate processes. We explore several calibration methods that can be used to fine-tune the models, and that deal with the observed trade-off between marginal and correlation fit. We carry out a thorough empirical analysis to evaluate the ability of t

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30

Gonon, Lukas, and Christoph Schwab. "Deep ReLU network expression rates for option prices in high-dimensional, exponential Lévy models." Finance and Stochastics, August 31, 2021. http://dx.doi.org/10.1007/s00780-021-00462-7.

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AbstractWe study the expression rates of deep neural networks (DNNs for short) for option prices written on baskets of $d$ d risky assets whose log-returns are modelled by a multivariate Lévy process with general correlation structure of jumps. We establish sufficient conditions on the characteristic triplet of the Lévy process $X$ X that ensure $\varepsilon $ ε error of DNN expressed option prices with DNNs of size that grows polynomially with respect to ${\mathcal{O}}(\varepsilon ^{-1})$ O ( ε − 1 ) , and with constants implied in ${\mathcal{O}}(\, \cdot \, )$ O ( ⋅ ) which grow polynomially

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Semeraro, Patrizia. "Multivariate tempered stable additive subordination for financial models." Mathematics and Financial Economics, July 13, 2022. http://dx.doi.org/10.1007/s11579-022-00321-9.

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AbstractWe study a class of multivariate tempered stable distributions and introduce the associated class of tempered stable Sato subordinators. These Sato subordinators are used to build additive inhomogeneous processes by subordination of a multiparameter Brownian motion. The resulting process is additive and time inhomogeneous and it is a generalization of multivariate Lévy processes with good fit properties on financial data. We specify the model to have unit time normal inverse Gaussian distribution and we discuss the ability of the model to fit time inhomogeneous correlations on real dat

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Cuchiero, Christa, Francesca Primavera, and Sara Svaluto-Ferro. "Universal approximation theorems for continuous functions of càdlàg paths and Lévy-type signature models." Finance and Stochastics, February 26, 2025. https://doi.org/10.1007/s00780-025-00557-5.

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Abstract We prove a universal approximation theorem that allows approximating continuous functionals of càdlàg (rough) paths uniformly in time and on compact sets of paths via linear functionals of their time-extended signature. Our main motivation to treat this question comes from signature-based models for finance that allow the inclusion of jumps. Indeed, as an important application, we define a new class of universal signature models based on an augmented Lévy process, which we call Lévy-type signature models. They extend continuous signature models for asset prices as proposed e.g. by Per

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33

Barski, Michał, and Rafał Łochowski. "On the reducibility of affine models with dependent Lévy factors." Modern Stochastics: Theory and Applications, January 1, 2025, 1–37. https://doi.org/10.15559/25-vmsta280.

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The paper is devoted to the study of the short rate equation of the form \[ \text{d}R(t)=F(R(t))\text{d}t+{\sum \limits_{i=1}^{d}}{G_{i}}(R(t-))\text{d}{Z_{i}}(t),\hspace{1em}R(0)={R_{0}}\ge 0,\hspace{3.33333pt}t\gt 0,\] with deterministic functions $F,{G_{1}},\dots ,{G_{d}}$ and a multivariate Lévy process $Z=({Z_{1}},\dots ,{Z_{d}})$ with possibly dependent coordinates. This equation is assumed to have a nonnegative solution which generates an affine term structure model. Under some mild assumptions on the Lévy measure of Z it is shown that the same term structure is generated by an equation

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Casanova Biscarri, Emilio, Sophie Mercier, and Carmen Sangüesa. "A model for stochastic dependence implied by failures among deteriorating components." Applied Stochastic Models in Business and Industry, November 15, 2023. http://dx.doi.org/10.1002/asmb.2831.

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AbstractA system of components is here considered, with component deterioration modeled by non decreasing time‐scaled Lévy processes. When a component fails, a sudden change in the time‐scaling functions of the surviving components is induced, which makes the components stochastically dependent. We compute the reliability function of coherent systems under this new dependence model. We next study the distribution of the ordered failure times, and establish some positive dependence properties. We also provide stochastic comparison results in the usual multivariate stochastic order between failu

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Bianchi, Michele Leonardo, Asmerilda Hitaj, and Gian Luca Tassinari. "A welcome to the jungle of continuous-time multivariate non-Gaussian models based on Lévy processes applied to finance." Annals of Operations Research, September 20, 2022. http://dx.doi.org/10.1007/s10479-022-04970-3.

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Fasen‐Hartmann, Vicky, and Lea Schenk. "Mixed orthogonality graphs for continuous‐time state space models and orthogonal projections." Journal of Time Series Analysis, October 30, 2024. http://dx.doi.org/10.1111/jtsa.12787.

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In this article, we derive (local) orthogonality graphs for the popular continuous‐time state space models, including in particular multivariate continuous‐time ARMA (MCARMA) processes. In these (local) orthogonality graphs, vertices represent the components of the process, directed edges between the vertices indicate causal influences and undirected edges indicate contemporaneous correlations between the component processes. We present sufficient criteria for state space models to satisfy the assumptions of Fasen‐Hartmann and Schenk (2024a) so that the (local) orthogonality graphs are well‐de

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Brück, Florian, Jan-Frederik Mai, and Matthias Scherer. "Exchangeable min-id sequences: Characterization, exponent measures and non-decreasing id-processes." Extremes, December 17, 2022. http://dx.doi.org/10.1007/s10687-022-00450-w.

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AbstractWe establish a one-to-one correspondence between (i) exchangeable sequences of random variables whose finite-dimensional distributions are minimum (or maximum) infinitely divisible and (ii) non-negative, non-decreasing, infinitely divisible stochastic processes. The exponent measure of an exchangeable minimum infinitely divisible sequence is shown to be the sum of a very simple “drift measure” and a mixture of product probability measures, which uniquely corresponds to the Lévy measure of a non-negative and non-decreasing infinitely divisible process. The latter is shown to be supporte

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He, Zengxiang, Yihua Hu, Kanjian Zhang, Haikun Wei, and Mohammed Alkahtani. "Robust parameter identification based on nature‐inspired optimization for accurate photovoltaic modelling under different operating conditions." IET Renewable Power Generation, August 2, 2024. http://dx.doi.org/10.1049/rpg2.13057.

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AbstractAccurate parameter identification plays a crucial role in realizing precise modelling, design optimization, condition monitoring, and fault diagnosis of photovoltaic systems. However, due to the nonlinear, multivariate, and multistate characteristics of PV models, it is difficult to identify perfect model parameters using traditional analytical and numerical methods. Besides, some existing methods may stick in local optimum and have slow convergence speed. To address these challenges, this paper proposes an enhanced nature‐inspired OLARO algorithm for PV parameter identification under

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39

Parodi, Pietro, Derek Thrumble, Peter Watson, et al. "Loss modelling from first principles." British Actuarial Journal 29 (2024). https://doi.org/10.1017/s1357321724000163.

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Abstract A common statistical modelling paradigm used in actuarial pricing is (a) assuming that the possible loss model can be chosen from a dictionary of standard models; (b) selecting the model that provides the best trade-off between goodness of fit and complexity. Machine learning provides a rigorous framework for this selection/validation process. An alternative modelling paradigm, common in the sciences, is to prove the adequacy of a statistical model from first principles: for example, Planck’s distribution, which describes the spectral distribution of blackbody radiation empirically, w

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Gálvez, Akemi, Iztok Fister, Suash Deb, Iztok Fister, and Andrés Iglesias. "Particle swarm optimization with local search for height-map surface reconstruction from point clouds in reverse engineering." Neural Computing and Applications, December 10, 2024. https://doi.org/10.1007/s00521-024-10636-x.

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AbstractSurface reconstruction is a classical process in industrial engineering and manufacturing, particularly in reverse engineering, where the goal is to obtain a digital model from a physical object. For that purpose, the real object is typically scanned or digitized and the resulting point cloud is then fitted to mathematical surfaces through numerical optimization. The choice of the approximating functions is crucial for the accuracy of the process. Real-world objects such as manufactured workpieces often require complex nonlinear approximating functions, which are not well suited for st

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