Results 51 to 60 of about 5,691 (212)
Fractional Gaussian Noise: Spectral Density and Estimation Methods
Journal of Time Series Analysis, Volume 46, Issue 6, Page 1146-1174, November 2025.The fractional Brownian motion (fBm) process, governed by a fractional parameter H∈(0,1)$$ H\in \left(0,1\right) $$, is a continuous‐time Gaussian process with its increment being the fractional Gaussian noise (fGn). This article first provides a computationally feasible expression for the spectral density of fGn.
Shuping Shi, Jun Yu, Chen Zhang
wiley +1 more source
S&P 500 microstructure noise components: empirical inferences from futures and ETF prices
Journal of Time Series Analysis, Volume 46, Issue 6, Page 1032-1063, November 2025.By studying the differences between futures prices and exchange‐traded fund prices for the S&P 500 index, original results are obtained about the distribution and persistence of the microstructure noise component created by positive bid‐ask spreads and discrete price scales.
Stephen J. Taylor
wiley +1 more source
INTERNATIONAL TOURISTS’ EXPENDITURES IN THAILAND: A MODELLING OF THE ARFIMA-FIGARCH APPROACH [PDF]
Annals of the University of Petrosani: Economics, 2010 Forecasting is an essential analytical tool for tourism policy andplanning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q).
KANCHANA CHOKETHAWORN +5 more
doaj
نمذجة وتحليل أسعار الموز في مدينة الموصل باستخدام نموذج ARFIMA "دراسة تنبؤيه للسوق [PDF]
المجلة العراقية للعلوم الاحصائيةتناولت هذه الدراسة استخدام نماذج ARFIMA للتنبؤ بأسعار الموز المستورد في مدينه الموصل وذلك بالاعتماد على البيانات التي تم الحصول عليها من مديريه زراعه نينوى للفترة من سنه 2018 لغايه 2023 حيث استخدم في البحث عده طرق لتقدير الذاكرة الطويلة وتحديد قيمه معلمه
{حاب طلال, عمر سالم
doaj +1 more source
Data & Policy, 2022 The aim of the present article is to evaluate the use of the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model in predicting spatially and temporally localized political violent events using the Integrated Crisis Early Warning System ...
Tamir Libel
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Detrended Cross-Correlation Analysis: A New Method for Analyzing Two Non-stationary Time Series
, 2007 Here we propose a method, based on detrended covariance which we call detrended cross-correlation analysis (DXA), to investigate power-law cross-correlations between different simultaneously-recorded time series in the presence of non-stationarity.
Podobnik, Boris, Stanley, H. Eugene
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Local powers of least‐squares‐based test for panel fractional Ornstein–Uhlenbeck process
Journal of Time Series Analysis, Volume 46, Issue 5, Page 997-1023, September 2025.In recent years, significant advancements have been made in the field of identifying financial asset price bubbles, particularly through the development of time‐series unit‐root tests featuring fractionally integrated errors and panel unit‐root tests.
Katsuto Tanaka, Weilin Xiao, Jun Yu
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Jurnal LebesgueThe Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is a development of the ARIMA model with the differencing values being fractional numbers.
Muhammad Reja Sinaga +2 more
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Forecasting Digital Asset Return: An Application of Machine Learning Model
International Journal of Finance &Economics, Volume 30, Issue 3, Page 3169-3186, July 2025.ABSTRACT In this study, we aim to identify the machine learning model that can overcome the limitations of traditional statistical modelling techniques in forecasting Bitcoin prices. Also, we outline the necessary conditions that make the model suitable.
Vito Ciciretti +4 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.
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