Results 31 to 40 of about 111,952 (197)
Trend and Volatility Analysis of Shanghai Composite Index Returns Based on ARMA and LSTM Model
Journal of Applied Science and EngineeringThis paper takes the daily return rate of the Shanghai Composite Index as a sample to establish the ARMA-LSTM (Long Short-Term Memory) model for the Shanghai Composite Index.
Wenting Ma
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Predicting Annual Tigris River Streamflow at Kut Barrage using SAMS Program
Wasit Journal of Engineering SciencesForecasting synthetic hydrologic data is the primary goal of the Stochastic Analysis, Modeling, and Simulation (SAMS) program. This research examined yearly data on the streamflow of the Kut Barrage on the Tigris River spanning 21 years, from 2003 to ...
Ghufran R. AL-Youdawi +1 more
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A methodology for stochastic inventory modelling with ARMA triangular distribution for new products
Cogent Business & Management, 2017 This paper proposes a stochastic inventory policy of continuous review with random demand described with temporal dependence through an autoregressive moving average (ARMA) model with explicative variables, of usefulness in new products without a history
Fernando Rojas
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Using R/S analysis for forecasting stock quotes with ARMA and ARIMA methods [PDF]
ITM Web of ConferencesThe article observes the methods of forecasting time series Autoregressive Moving Average Model (ARMA) and Integrated Autoregressive Moving Average Model (ARIMA).
Stupina Alena, Zinenko Anna
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Intrusion Detection Technology for Wireless Sensor Networks Based on Autoregressive Moving Average
Advances in Multimedia, 2022 In wireless sensor networks (WSNs), aiming at the problems that internal attacks such as network congestion and high energy consumption seriously threaten the network security and normal operation, an intrusion detection technology based on traffic ...
Ju-zhen Yu
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ROBUST FREQUENCY DOMAIN ARMA MODELLING
IFAC Proceedings Volumes, 2006 In this paper a method for the rejection of frequency domain outliers is proposed. The algorithm is based on the work by Huber on M-estimators and the concept of influence function introduced by Ha ...
Gillberg, Jonas +2 more
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Online Learning for Time Series Prediction [PDF]
, 2013 In this paper we address the problem of predicting a time series using the ARMA (autoregressive moving average) model, under minimal assumptions on the noise terms. Using regret minimization techniques, we develop effective online learning algorithms for
Anava, Oren +3 more
core
International Journal of Research in Business and Social Science (2147- 4478), 2021 This paper employs the R software in identifying the most suitable ARMA model for forecasting the growth rate of the exchange rate between the US dollar and a unit of the British pound. The data is systematically split into two distinct periods identified as the in-sample period and the out of sample period.
Abdulaleem Isiaka +2 more
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Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition
Discrete Dynamics in Nature and Society, 2012 This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition (MEMD) is employed here for multiband representation of multichannel financial time series together. Autoregressive moving average (ARMA)
Md. Rabiul Islam +3 more
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Literature review on the application of ARMA model in stock price prediction [PDF]
SHS Web of ConferencesPredicting stock prices is a perennial quest in finance, yet price series are famously noisy, volatile and nonlinear. Among the many tools on offer, the autoregressive-moving-average (ARMA) model remains a surprisingly resilient workhorse.
Zhang Bowen
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