Results 51 to 60 of about 7,361 (242)
Upper bounds for superquantiles of martingales
Comptes Rendus. Mathématique, 2021 Let $(M_n)_n$ be a discrete martingale in $L^p$ for $p$ in $]1,2]$ or $p=3$. In this note, we give upper bounds on the superquantiles of $M_n$ and the quantiles and superquantiles of $M_n^* = \max (M_0,M_1,\,\ldots ,\,M_n)$.
Rio, Emmanuel
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On Selection of Cross‐Section Averages in Non‐Stationary Environments
Journal of Time Series Analysis, EarlyView.ABSTRACT Information criteria (ICs) have been widely used in factor models to estimate an unknown number of latent factors. It has recently been shown that ICs perform well in Common Correlated Effects (CCE) and related settings when selecting a set of cross‐section averages (CAs) sufficient for the factor space under stationary factors.
Jan Ditzen, Ovidijus Stauskas
wiley +1 more source
Exponential inequalities for nonstationary Markov chains
Dependence Modeling, 2019 Exponential inequalities are main tools in machine learning theory. To prove exponential inequalities for non i.i.d random variables allows to extend many learning techniques to these variables.
Alquier Pierre +2 more
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Martingale Transforms between Martingale Hardy-amalgam Spaces
Abstract and Applied Analysis, 2021 We discuss martingale transforms between martingale Hardy-amalgam spaces Hp,qs,Qp,q and Pp,q.
Justice Sam Bansah
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Estimation of the Intercept Parameter in Integrated Galton–Watson Processes
Journal of Time Series Analysis, EarlyView.ABSTRACT We study the estimation of the intercept parameter in an integrated Galton–Watson process, an important building block for many count‐valued time series models. In this unit root setting, the ordinary least squares estimator is known to be inconsistent, whereas the existing weighted least squares (WLS) estimator is consistent only in the case ...
Yang Lu
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Penalized Convex Estimation in Dynamic Location Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
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Convergence Theorems for Operators Sequences on Functionals of Discrete-Time Normal Martingales
Journal of Function Spaces, 2018 We aim to investigate the convergence of operators sequences acting on functionals of discrete-time normal martingales M. We first apply the 2D-Fock transform for operators from the testing functional space S(M) to the generalized functional space S⁎(M ...
Jinshu Chen
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Detecting Periodicity of a General Stationary Time Series via AR(2)‐Model Fitting
Journal of Time Series Analysis, EarlyView.ABSTRACT Estimating the periodicity of a stationary time series via fitting a second‐order stationary autoregressive (AR(2)) model has been initiated by the seminal paper of Yule (1927). We investigate properties of this procedure when applied to general stationary processes possessing a spectral density with a dominant peak at some unknown frequency ...
Jens‐Peter Kreiss +2 more
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Measure‐valued processes for energy markets
Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
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ON (sub- super) asymptotic martingales
Tikrit Journal of Pure Science, 2020 In this paper we intoduce a new class of definitions (sub - super) asymptotic martingale through the concept of asymptotic martingale. we investigate and prove some properties of asymptotic martingale and (sub - super) asymptotic martingale .
Hassan H- Ebrahem, Juwan Abbas-Ali
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