Results 91 to 100 of about 2,441 (205)
TESTING THE LONG RANGE-DEPENDENCE FOR THE CENTRAL EASTERN EUROPEAN AND THE BALKANS STOCK MARKETS [PDF]
Annals of the University of Oradea: Economic Science, 2013 In this study we tested the existence of long memory in the the return series for major Central Eastern European and Balkans stock markets, using the following statistical methods: Hurst Exponent, GPH method, Andrews and Guggenberger method, Reisen ...
Pece Andreea Maria +3 more
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Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model
, 2016 Recent research argues that if the cause of confusion between long memory and regime switching were properly controlled for, they could be effectively distinguished.
Shi, Yanlin, Ho, Kin-Yip
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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
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Modelos de memoria larga para series económicas y financieras [PDF]
, 2001 En este trabajo se hace una revisión de los modelos de series temporales con memoria larga para la media y la varianza condicionada, con especial atención a los modelos ARMA fraccionalmente integrados (ARFIMA) y a los modelos GARCH y SV fraccionalmente ...
Pérez, Ana +3 more
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A guide to Whittle maximum likelihood estimator in MATLAB. [PDF]
Front Netw Physiol, 2023 Roume C.
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Analysing CPI inflation by the fractionally integrated ARFIMA-STVGARCH model [PDF]
, 2008 The aim of this paper is to study the dynamic evolution of inflation rate. The model is constructed by extending the ARFIMA-GARCH to ARFIMA with a time varying GARCH model where the transition from one regime to another is evolving smoothly over time. We
Mootamri, Imene +2 more
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Stock market volatility simulation with the LSTM neural network
Вестник Пермского университета: Серия ЭкономикаIntroduction. Stock market volatility simulation and forecast are relevant issues which could contribute into lower risks and higher revenues of the market transactions.
Dmitry Aleksandrovich Patlasov +1 more
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SaPt-CNN-LSTM-AR-EA: a hybrid ensemble learning framework for time series-based multivariate DNA sequence prediction. [PDF]
PeerJ, 2023 Yan W +5 more
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PENERAPAN ARFIMA PADA PERAMALAN KASUS POSITIF COVID-19 DI INDONESIA
, 2022 Penyebaran virus Covid-19 yang melanda dunia terjadi sejak akhir Desember 2019 sangat berdampak di berbagai bidang, seperti pendidikan, kesehatan, ekonomi, dan bidang lainnya.
KHAIRUL HUDA
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Predicción mediante modelos AFIRMA y FOU de energía afluente
Memoria Investigaciones en Ingeniería, 2017 En este trabajo se estudian predicciones a partir de modelos ARFIMA y FOU para la serie de datos semanales de energía afluente generada por las represas hidroeléctricas de Uruguay entre 1909 y 2012. Se describe la serie de datos, y mediante la estimación
Juan Kalemkerian
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