Results 61 to 70 of about 21,636,733 (224)
Forecasting West Texas Intermediate Crude Oil Price: Stochastic Differential Approach [PDF]
Uncertainty in oil markets has led economic researchers to the use of stochastic processes. The purpose of this paper, is the use of stochastic differential models to predict the crude oil price of West Texas Intermediate (WTI) and compare the ...
ramin khochiani, younes nademi
doaj +1 more source
Gold price modeling in Indonesia using ARFIMA method
Abstract Gold investment is the best choice to control finance. Gold is easy to resell if there is a financial need at the unpredictable moment. The data of gold price in Indonesia is a long-term memory data series or a time series data that has a long-term dependency.
D Safitri +3 more
openaire +1 more source
Improved Trend Analysis With EOFs and Application to Warming of Polar Regions
Introducing a variation of EOF analysis, we obtain an insignificant Antarctic trend between 1979 and 2023 of (0.13 ± 0.17) K/decade. The first principal component completely captures the trend for land regions of the order of the size of most countries.
Ewan T. Phillips, Holger Kantz
wiley +1 more source
THE IMPACT OF THE FINANCIAL CRISIS ON LONG MEMORY: EVIDENCE FROM EUROPEAN BANKING INDICES [PDF]
We have analyzed the impact of the financial crisis on the existence of the long term dependency for European banking indices. By estimating Hurst Exponent, ARFIMA and FIGARCH models we found that major financial crisis such as, Mexican, Asian and ...
Pece Andreea Maria +3 more
doaj
Network traffic prediction based on ARFIMA model
ARFIMA is a time series forecasting model, which is an improved ARMA model, the ARFIMA model proposed in this article is demonstrated and deduced in detail. combined with network traffic of CERNET backbone and the ARFIMA model,the result shows that,compare to the ARMA model, the prediction efficiency and accuracy has increased significantly, and not ...
Zhou, Dingding +2 more
openaire +2 more sources
Identifying influential individuals and predicting future demand of chronic kidney disease patients
ABSTRACT To ensure high service quality, managers need to personalize treatment options and meet their customer demands. Our research is motivated by the need to better anticipate and prepare for that. We develop a generalizable framework that is the first to address two healthcare risk management goals: (1) identifying high risk and stable‐demand ...
Zlatana D. Nenova, Valerie L. Bartelt
wiley +1 more source
Stock market volatility simulation with the LSTM neural network
Introduction. 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
doaj +1 more source
A comparative analysis of alternative univariate time series models in forecasting Turkish inflation
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
doaj +1 more source
Time series with infinite-order partial copula dependence
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.
doaj +1 more source
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
core +2 more sources

