Results 61 to 70 of about 4,901 (213)
Evaluation of Dual Long Memory Properties with Emphasizing the Skewed and Fat-Tail Distribution: Evidence from Tehran Stock Exchange [PDF]
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī, 2014 This paper investigates the presence of long memory in the Tehran stock market, using the ARFIMA, GPH, GSP and FIGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of TEPIX ...
Mohammad Javad Mohagheghnia +3 more
doaj
Revista de Economia e Sociologia Rural, 2007 O presente trabalho tem como objetivo modelar séries temporais para efeito de previsão com diferenciações inteira e fracionária, utilizando dados de preços futuros de commodities agrícolas.
Ricardo Chaves Lima +2 more
doaj +1 more source
Fractional stochastic volatility model
Journal of Time Series Analysis, Volume 46, Issue 2, Page 378-397, March 2025.This article introduces a discrete‐time fractional stochastic volatility model (FSV) based on fractional Gaussian noise. The new model includes the standard stochastic volatility model as a special case and has the same limit as the fractional integrated stochastic volatility (FISV) model, which is the continuous‐time fractional Ornstein–Uhlenbeck ...
Shuping Shi, Xiaobin Liu, Jun Yu
wiley +1 more source
International Journal of Mathematics and Mathematical Sciences, Volume 2025, Issue 1, 2025.Accurate temperature forecasting is of paramount importance across various sectors, influencing decision‐making processes and impacting numerous aspects of daily life. This study analyzes temperature time series data from the Nairobi County in Kenya, aiming to develop accurate hybrid time series forecasting models.
John Kamwele Mutinda +3 more
wiley +1 more source
پژوهشهای ریاضی, 2020 Introduction The data obtained from observing a phenomenon over time is very common. One of the most popular models in time series and signal processing is the Autoregressive moving average model (ARMA).
Mahmod Afshari +2 more
doaj
Physical Review Research, 2022 We introduce a method for reconstructing macroscopic models of one-dimensional stochastic processes with long-range correlations from sparsely sampled time series by combining fractional calculus and discrete-time Langevin equations.
Johannes A. Kassel, Holger Kantz
doaj +1 more source
Computational aspects of Bayesian spectral density estimation
, 2011 Gaussian time-series models are often specified through their spectral density. Such models present several computational challenges, in particular because of the non-sparse nature of the covariance matrix.
Chopin, Nicolas +2 more
core +5 more sources
Earth and Space Science, Volume 11, Issue 12, December 2024.Abstract This study aims to develop an absolute model of contemporary Vertical Crustal Movements (VCM) and Vertical Land Movements (VLM) in an area of Poland based on GNSS solutions. Velocities at permanent stations were subjected to geological, tectonic, hydrological and mineral information analyses.
B. Naumowicz +2 more
wiley +1 more source
Optimal spectral bandwidth for long memory [PDF]
, 1993 For long range dependent time series with a spectral singularity at frequency zero, a theory for optimal bandwidth choice in non-parametric analysis ofthe singularity was developed by Robinson (1991b).
Delgado, Miguel A., Robinson, Peter M.
core +1 more source
Labor market forecasting in unprecedented times: A machine learning approach
Bulletin of Economic Research, Volume 76, Issue 4, Page 893-915, October 2024.Abstract The COVID‐19 pandemic ushered in unprecedented social and economic conditions, alongside unexpected policy responses, challenging the effectiveness of traditional labor market forecasting approaches. This article presents a novel approach that integrates macroeconomic variables, traditional labor market metrics, and Google search data to ...
Johanna M. Orozco‐Castañeda +2 more
wiley +1 more source