Results 1 to 10 of about 23,794,706 (205)
Hybridization of long short-term memory neural network in fractional time series modeling of inflation [PDF]
Frontiers in Big Data, 2023 Inflation is capable of significantly impacting monetary policy, thereby emphasizing the need for accurate forecasts to guide decisions aimed at stabilizing inflation rates.
Erman Arif +4 more
doaj +2 more sources
FORECASTING THE UNEMPLOYMENT RATE IN MALAYSIA DURING COVID-19 PANDEMIC USING ARIMA AND ARFIMA MODELS
Malaysian Journal of Computing, 2022 The unemployment issue is one of the most common problems faced by many countries around the world. The unemployment rates in developed countries often fluctuate throughout time.
Nur Afiqah Ismail +2 more
doaj +2 more sources
Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets [PDF]
Entropy, 2023 The goal of this paper is to highlight considerations and provide recommendations for analytical issues that arise when applying entropy methods, specifically Sample Entropy (SampEn), to temporally correlated stochastic datasets, which are representative
Joshua Liddy, Michael Busa
doaj +2 more sources
FORECASTING FRESH WATER AND MARINE FISH PRODUCTION IN MALAYSIA USING ARIMA AND ARFIMA MODELS
Malaysian Journal of Computing, 2018 Malaysia is surrounded by sea, rivers and lakes which provide natural sources of fish for human consumption. Hence, fish is one source of protein supply to the country and fishery is a sub-sector that contribute to the national gross domestic product ...
P.J.W. Mah, N.N.M. Zali, N.A.M. Ihwal, N.Z. Azizan
doaj +2 more sources
Predicting BRICS stock returns using ARFIMA models [PDF]
Applied Financial Economics, 2014 This article examines the existence of long memory in daily stock market returns from Brazil, Russia, India, China and South Africa (BRICS) countries and also attempts to shed light on the efficacy of autoregressive fractionally integrated moving average (ARFIMA) models in predicting stock returns.
G. Aye +5 more
semanticscholar +3 more sources
Long-Range Dependence in Financial Markets: A Moving Average Cluster Entropy Approach. [PDF]
Entropy (Basel), 2020 A perspective is taken on the intangible complexity of economic and social systems by investigating the underlying dynamical processes that produce, store and transmit information in financial time series in terms of the \textit{moving average cluster ...
Murialdo P, Ponta L, Carbone A.
europepmc +5 more sources
Cumhuriyet Science JournalThe research delved into analysing the stochastic characteristics of Nigeria's Real GDP, the exchange rate of the Naira to US Dollar, and the inflation rate employing Autoregressive fractionally integrated moving average (ARFIMA) and the Autoregressive ...
Ayoade Adewole
doaj +3 more sources
Comparing the bias and misspecification in ARFIMA models [PDF]
Journal of Time Series Analysis, 1997 We investigate the bias in both the short‐term and long‐term parameters for a range of autoregressive fractional integrated moving‐average (ARFIMA) models using both semi‐parametric and maximum likelihood (ML) estimation methods. The results suggest that, provided the correct model is estimated, the ML method outperforms the semi‐parametric methods in ...
Jeremy Smith, N. Taylor, S. Yadav
semanticscholar +3 more sources
Predicting Waste Volume Using ARIMA and ARFIMA Models
International Research Journal of Multidisciplinary ScopeThe 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 +2 more sources
Evaluating the Effectiveness of GARCH Models in the Estimation of Systematic Risk in listed companies of the Tehran Stock Exchange [PDF]
Journal of Asset Management and Financing, 2020 The stock market of each country, in addition to reflecting its economic structure, is considered as an important source of capital Circulation of that country.
nemat rastgoo, Hossein panahian
doaj +1 more source