Results 71 to 80 of about 23,794,745 (244)
A comparative analysis of alternative univariate time series models in forecasting Turkish inflation
Journal of Business Economics and Management, 2012 This paper analyses inflation forecasting power of artificial neural networks with alternative univariate time series models for Turkey. The forecasting accuracy of the models is compared in terms of both static and dynamic forecasts for the period ...
A. Nazif Çatık, Mehmet Karaçuka
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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
Time series with infinite-order partial copula dependence
Dependence Modeling, 2022 Stationary and ergodic time series can be constructed using an s-vine decomposition based on sets of bivariate copula functions. The extension of such processes to infinite copula sequences is considered and shown to yield a rich class of models that ...
Bladt Martin, McNeil Alexander J.
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, 2016 In this paper, we show that the central limit theorem (CLT) satisfied by the data-driven Multidimensional Increment Ratio (MIR) estimator of the memory parameter d established in Bardet and Dola (2012) for d $\in$ (--0.5, 0.5) can be extended to a ...
Bardet, Jean-Marc, Dola, Béchir
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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
Is there Long Memory in Stock Markets, or Does it Depend on the Model, Period or Frequency?
Ensayos Revista de Economía, 2017 This paper analyses the existence of long memory in the major stock markets in the world, and if this is the case, whether it’s due to the type of econometric models used, the period of study or the frequency of data (intraday, daily, weekly, etc.)?
Héctor F. Salazar-Núñez +2 more
doaj +1 more source
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
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
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 +10 more sources
Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models [PDF]
We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular emphasis of this paper is on assessing the performance of long memory time series models in comparison to their short-memory ...
Kaizoji, Taisei, Lux, Thomas
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