Results 151 to 160 of about 73,625 (339)

Enhancing Volatility Prediction: A Wavelet‐Based Hierarchical Forecast Reconciliation Approach

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting realized volatility (RV) has been widely studied, with numerous techniques developed to enhance predictive accuracy. Among these techniques, the use of RV decompositions based on intraday asset returns has been applied. However, the use of a frequency‐based decomposition, which provides unique insights into the dynamics of RV ...
Adam Clements, Ajith Perera
wiley   +1 more source

Predicting Traffic Load Data: ARIMA and SARIMA Comparison

Engineering Proceedings
The article presents comparison of two statistical methods of data prediction over transport datasets. Autoregressive integrated moving average and its seasonal modification—seasonal autoregressive integrated moving average—are often applied in ...
Todor Peychinov, Adeliya Karaivanova, Teodora Mecheva   +2 more
doaj   +1 more source

Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models. [PDF]

BMC Public Health, 2023
Cheng C, Jiang WM, Fan B, Cheng YC, Hsu YT, Wu HY, Chang HH, Tsou HH.   +7 more
europepmc   +1 more source

Aplikasi Metode Autoregressive Integrated Moving Average (ARIMA)

Tulisan Ini Berisi Aplikasi Metode Autoregressive Integrated Moving Average (ARIMA)
openaire   +1 more source

Coherent Forecasting of Realized Volatility

Journal of Forecasting, EarlyView.
ABSTRACT The QLIKE loss function is the stylized favorite of the literature on volatility forecasting when it comes to out‐of‐sample evaluation and the state of the art model for realized volatility (RV) forecasting is the HAR model, which minimizes the squared error loss for in‐sample estimation of the parameters.
Marius Puke, Karsten Schweikert
wiley   +1 more source

Seasonal autoregressive integrated moving average (SARIMA) time-series model for milk production forecasting in pasture-based dairy cows in the Andean highlands. [PDF]

PLoS One, 2023
Perez-Guerra UH, Macedo R, Manrique YP, Condori EA, Gonzáles HI, Fernández E, Luque N, Pérez-Durand MG, García-Herreros M.   +8 more
europepmc   +1 more source

The Comparative Analysis of Integrated Moving Average and Autoregressive Integrated Moving Average Methods for Predicting Bitcoin Returns

Journal of Mathematics, Computations and Statistics
The rise in popularity of cryptocurrencies such as Bitcoin across various platforms has attracted the attention of young investors, making it easier for them to invest. However, due to the volatile nature of Bitcoin, this type of investment carries a high risk.
null Brigita Tiara Elgityana Melantika, null Kalfin, Bakti Siregar, null Wiwik Wiyanti   +3 more
openaire   +1 more source

Forecasting COVID-19 new cases in Algeria using Autoregressive fractionally integrated moving average Models (ARFIMA) [PDF]

, 2020
Belkacem Balah, Messaoud Djeddou
openalex   +1 more source

Regional employment forecasts with spatial interdependencies [PDF]

"The labour-market policy-mix in Germany is increasingly being decided on a regional level. This requires additional knowledge about the regional development which (disaggregated) national forecasts cannot provide.
Hampel, Katharina, Kunz, Marcus, Schanne, Norbert, Wapler, Rüdiger, Weyh, Antje   +4 more
core  

Forecasting House Prices: The Role of Market Interconnectedness

Journal of Forecasting, EarlyView.
ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen, George Milunovich, Shuping Shi, Ben Wang   +3 more
wiley   +1 more source