Use of neural networks to accommodate seasonal fluctuations when equalizing time series for the CZK/RMB exchange rate

Z Rowland, G Lazaroiu, I Podhorská - Risks, 2020 - mdpi.com
The global nature of the Czech economy means that quantitative knowledge of the influence
of the exchange rate provides useful information for all participants in the international …

Dependency analysis between bitcoin and selected global currencies

B Szetela, G Mentel, S Gędek - Dynamic econometric models, 2016 - apcz.umk.pl
In this research we have tried to identify the relationship between the exchange rate for
bitcoin to the leading currencies such as Dollar, Euro, British Pound and Chinese Yuan and …

A Kalman filter-based hybridization model of statistical and intelligent approaches for exchange rate forecasting

M Khashei, B Mahdavi Sharif - Journal of Modelling in Management, 2021 - emerald.com
Purpose The purpose of this paper is to propose a comprehensive version of a hybrid
autoregressive integrated moving average (ARIMA), and artificial neural networks (ANNs) in …

Long short-term memory network for predicting exchange rate of the Ghanaian cedi

AF Adekoya, IK Nti, BA Weyori - FinTech, 2021 - mdpi.com
An accurate prediction of the Exchange Rate (ER) serves as the basis for effective financial
management, monetary policies, and long-term strategic decision making worldwide. A …

Prevalence of hemorrhagic fever with renal syndrome in Yiyuan County, China, 2005–2014

T Wang, J Liu, Y Zhou, F Cui, Z Huang, L Wang… - BMC infectious …, 2015 - Springer
Background Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland
China, where human cases account for 90% of the total global cases. Yiyuan County is one …

The volatility mechanism and intelligent fusion forecast of new energy stock prices

GF Fan, RT Zhang, CC Cao, LL Peng, YH Yeh… - Financial Innovation, 2024 - Springer
The new energy industry is strongly supported by the state, and accurate forecasting of stock
price can lead to better understanding of its development. However, factors such as cost and …

[PDF][PDF] Modelling of oil price volatility using ARIMA-GARCH models

F Merabet, H Zeghdoudi, RH Yahia… - Adv …, 2021 - research-publication.com
In this paper, the behavior of the oil price series named OIL is examined. The non-
stationarity on average and variance, with the non-normality of the OIL series distribution …

Predicting the number of visceral leishmaniasis cases in Kashgar, **njiang, China using the ARIMA-EGARCH model

H Li, R Zheng, Q Zheng, W Jiang, X Zhang… - Asian Pacific Journal …, 2020 - journals.lww.com
Objective: To forecast the visceral leishmaniasis cases using autoregress integrated moving
average (ARIMA) and hybrid ARIMA-EGARCH model, which offers a scientific basis to …

Price volatility modelling–wheat: GARCH model application

M Čermák, K Malec, M Maitah - AGRIS on-line Papers in …, 2017 - ageconsearch.umn.edu
This paper is focused on the modelling of volatility in the agricultural commodity market,
specifically on wheat. The aim of this study is to develop an applicable and relevant model of …

An enhanced neural-based bi-component hybrid model for foreign exchange rate forecasting

M Khashei, S Torbat, ZH Rahimi - Turkish Journal of Forecasting, 2017 - dergipark.org.tr
Foreign exchange rates are among the most important economic indices in the international
monetary markets. Applying forecasting models for forecasting in exchange rate markets …