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Low-frequency historical data, high-frequency historical data and option data are three major sources, which can be used to forecast the underlying security's volatility. In this paper, we propose two econometric models, which integrate…

Statistical Finance · Quantitative Finance 2019-07-08 Huiling Yuan , Yong Zhou , Zhiyuan Zhang , Xiangyu Cui

This paper studies the joint role of long-memory dynamics,rough-volatility behavior, and persistence-based forecasting features in equity volatility modeling. We combine semiparametric long-memory estimation, rough-volatility diagnostics,…

Statistical Finance · Quantitative Finance 2026-05-26 Akash Deep , Nicholas Appiah , Svetlozar T. Rachev

Representation learning on dynamic graphs requires capturing complex dependencies that evolve across both time and structure. Existing approaches typically adopt fixed temporal decay schemes or predetermined structural propagation depths,…

Machine Learning · Computer Science 2026-05-29 Qian Chang , Ciprian Doru Giurcaneanu , Runsong Jia , Xia Li , Guoping Hu , Xiufeng Cheng , Jinqing Yang , Mengjia Wu , Yi Zhang

Dynamical behaviour of discrete dynamical systems has been investigated extensively in the past few decades. However, in several applications, long term memory plays an important role in the evolution of dynamical variables. The definition…

Dynamical Systems · Mathematics 2022-08-30 Sumit S. Pakhare , Varsha Daftardar-Gejji , Dilip S. Badwaik , Amey Deshpande , Prashant M. Gade

Water quantity and quality are vital indices for assessing fluvial environments. These indices are highly variable over time and include sub-exponential memory, where the influences of past events persist over long durations. Moreover,…

Probability · Mathematics 2025-11-24 Hidekazu Yoshioka , Yumi Yoshioka

In this paper we consider a fractional stochastic volatility model, that is a model in which the volatility may exhibit a long-range dependent or a rough/antipersistent behavior. We propose a dynamic sequential Monte Carlo methodology that…

Methodology · Statistics 2017-02-28 Alexandra Chronopoulou , Konstantinos Spiliopoulos

We study the parameter estimation for parabolic, linear, second-order, stochastic partial differential equations (SPDEs) observing a mild solution on a discrete grid in time and space. A high-frequency regime is considered where the mesh of…

Statistics Theory · Mathematics 2019-09-11 Markus Bibinger , Mathias Trabs

We report numerical investigation of the glassy behavior of random-field exchange models in three dimensions. Correlation of energy with the magnetization for different numbers of spin components has been studied. There is a profound…

Statistical Mechanics · Physics 2016-10-18 D. A. Garanin , E. M. Chudnovsky

This paper investigates the continuous-time limit of score-driven models with long memory. By extending score-driven models to incorporate infinite-lag structures with coefficients exhibiting heavy-tailed decay, we establish their weak…

Probability · Mathematics 2025-12-09 Yinhao Wu , Ping He

Analogies between the price dynamics in the foreign exchange market and 3-dimensional fully developed turbulence were recently presented in Nature vol. 381, 767-769 (1996). Independently, we have carried out a study comparing the parallel…

Condensed Matter · Physics 2007-05-23 Rosario N. Mantegna , H. Eugene Stanley

The scope of the paper is the theoretical analysis of the time rate in which a dynamical system reaches a stable stationary state or stable oscillations. The method used for the analysis is based on the so-called iterative time profiles,…

General Mathematics · Mathematics 2026-02-10 Marek Berezowski , Katarzyna Bizon

Time series forecasting represents a significant and challenging task across various fields. Recently, methods based on mode decomposition have dominated the forecasting of complex time series because of the advantages of capturing local…

Methodology · Statistics 2023-11-30 Zhengtao Gui , Haoyuan Li , Sijie Xu , Yu Chen

Wind-speed processes exhibit substantial temporal variability and spatial dependence, yet volatility dynamics across monitoring networks remain relatively unexplored. This study investigates the spatiotemporal behaviour of wind-speed…

Applications · Statistics 2026-05-11 Ariane Nidelle Meli Chrisko , Philipp Otto

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility…

Methodology · Statistics 2022-06-01 Donggyu Kim , Minseok Shin

Hexagonal manganites REMnO3 (RE, rare earths) have attracted significant attention due to their potential applications as multiferroic materials and the intriguing physics associated with the topological defects. The two-dimensional (2D)…

Materials Science · Physics 2018-01-24 Fei Xue , Nan Wang , Xueyun Wang , Yanzhou Ji , Sang-Wook Cheong , Long-Qing Chen

Inspired by the recent literature on aggregation theory, we aim at relating the long range correlation of the stocks return volatility to the heterogeneity of the investors' expectations about the level of the future volatility. Based on a…

Statistical Finance · Quantitative Finance 2008-12-02 Jerome Coulon , Yannick Malevergne

Resistive switching is one of the foremost candidates for building novel types of non-volatile random access memories. Any practical implementation of such a memory cell calls for a strong miniaturization, at which point fluctuations start…

Materials Science · Physics 2017-10-11 Paul K. Radtke , Andrew L. Hazel , Arthur V. Straube , Lutz Schimansky-Geier

Recently, to account for low-frequency market dynamics, several volatility models, employing high-frequency financial data, have been developed. However, in financial markets, we often observe that financial volatility processes depend on…

Applications · Statistics 2021-03-01 Dohyun Chun , Donggyu Kim

Volatility is a quantity of measurement for the price movements of stocks or options which indicates the uncertainty within financial markets. As an indicator of the level of risk or the degree of variation, volatility is important to…

Machine Learning · Computer Science 2018-11-12 Qiang Zhang , Rui Luo , Yaodong Yang , Yuanyuan Liu

A new unsteady flamelet model is developed to be used for sub-grid modeling and coupling with the resolved flow description for turbulent combustion. Difficulties with prior unsteady flamelet models are identified. The model extends the…

Fluid Dynamics · Physics 2024-02-02 William A. Sirignano