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An Innovative Approach to Financial Market Analysis: Hybrid ARFIMA with Sieve and Moving Block Bootstrap

Sains Malaysiana
This paper aims to develop the field of financial time series analysis by focusing on the Egyptian stock market, EGX 30 in particular, using innovative modeling and forecasting techniques.
Alshaimaa Elwasify, Zaidi Isa
semanticscholar   +1 more source

Penerapan Model ARFIMA-LSTM Menggunakan Variasi Estimasi Parameter Pembeda Dalam Meramalkan data IHPBI

Jurnal Riset Mahasiswa Matematika
Indeks Harga Perdagangan Besar Indonesia (IHPBI) merupakan indikator penting dalam mengukur perkembangan ekonomi, khususnya pada sektor pertanian yang memiliki pengaruh besar terhadap daya beli masyarakat. Fluktuasi harga di sektor ini berdampak langsung
Trieke Nurfadilah Harun   +4 more
semanticscholar   +1 more source

A BIBLIOMETRIC ANALYSIS OF THE ARFIMA MODEL DURING 1993 – 2022

Advanced International Journal of Business Entrepreneurship and SMEs
The Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is the best choice for the long-term memory data series. In this research, we review and evaluate the literature on ARFIMA models.
Amirah Hazwani Abdul Rahim   +2 more
semanticscholar   +1 more source

Predicting Waste Volume Using ARIMA and ARFIMA Models

International Research Journal of Multidisciplinary Scope
The final waste processing facility plays a crucial role in waste management. The growing amount of waste in landfills is causing significant harm to the surrounding environment and the health of nearby residents.
Hedi   +3 more
semanticscholar   +1 more source

Arfima-Figarch vs. Arfima-Hygarch: Case Study ETF Returns of Emerging Asian Countries

Asian Journal of Finance & Accounting, 2014
This research investigate the long memory returns for ETF returns index of seven Asian countries in Emerging Markets Equities during 2008-2013 periods. Those ETFs are Wisdom Tree Indian Rupee Fund (ICN), Market Vectors Indonesia Index (IDX), iShares MSCI Malaysia Index Fund (EWM), Market Vectors Russia ETF (RSX), and iShares MSCI Thailand Investable ...
openaire   +1 more source

ASSESSING THE PERFORMANCE OF ARIMA AND ARFIMA MODELS IN FORECASTING INTERNALLY GENERATED REVENUE OF KADUNA STATE

FUDMA Journal of Sciences
Internally generated revenue (IGR) is an important source of revenue that can be used to fund public services and infrastructure projects. Accurate forecasting of IGR is essential for effective budgeting and financial planning.
M.I. Usman, T. Musa, Auwalu Ibrahim
semanticscholar   +1 more source

Pemodelan Return Harga Emas Dengan Pendekatan Inferensi Bayesian ARFIMA

Lattice Journal Journal of Mathematics Education and Applied
Volatility in stock and commodity prices, such as gold, plays a crucial role in investment decisions because high price fluctuations increase risk but also create opportunities for higher returns. The Autoregressive Fractionally Integrated Moving Average
Vivin Acnesya, Dodi Devianto, Maiyastri
semanticscholar   +1 more source

Bayesian model selection in ARFIMA models

Expert Systems with Applications, 2010
Various model selection criteria such as Akaike information criterion (AIC; Akaike, 1973), Bayesian information criterion (BIC; Akaike, 1979) and Hannan-Quinn criterion (HQC; Hannan, 1980) are used for model specification in autoregressive fractional integrated moving average (ARFIMA) models. Classical model selection criteria require to calculate both
Eǧrïoǧlu, Erol, Günay, Süleyman
openaire   +2 more sources

Penerapan Hybrid Metode ARFIMA-ANN Menggunakan Algoritma Backpropagation pada Peramalan Indeks Harga Saham Gabungan

Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
The Composite Stock Price Index (IHSG) is a of the key indicator a country uses to assess its economic condition. The fluctuating movements of stock prices create uncertainly in the stock market, complicating decision-making for investors and government ...
Rayhanul Jannah Buhungo   +2 more
semanticscholar   +1 more source

Indirect Inference for ARFIMA Processes

IFAC Proceedings Volumes, 1998
Abstract Inference for ARFIMA processes is more complicated than that for ordinary ARMA models. This has limited the application of these processes in the practice of modelling economic time series. In this paper, a procedure of indirect estimation for fractionally integrated processes is proposed and discussed.
openaire   +1 more source

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