Multivariate time series forecasting

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A Multi-Scale Residual Graph Convolution Network with hierarchical attention for predicting traffic flow in urban mobility

Complex & Intelligent Systems
Accurate prediction of traffic flow is essential for optimizing transportation resource allocation and enhancing urban mobility efficiency. However, traffic data generated daily are vast and complex, involving dynamic and intricate changes in the traffic
Jiahao Ling +3 more
doaj +1 more source

Forecasting Equicorrelation [PDF]

We study the out-of-sample forecasting performance of several time-series models of equicorrelation, which is the average pairwise correlation between a number of assets.
Adam E Clements +2 more
core

FORECAST EVALUATION FOR MULTIVARIATE TIME-SERIES MODELS: THE U.S. CATTLE MARKET [PDF]

A set of rigorous diagnostic techniques is used to evaluate the forecasting performance of five multivariate time-series models for the U.S. cattle sector.
Park, Timothy A.
core +1 more source

A nonparametric approach to forecasting realized volatility [PDF]

A well developed literature exists in relation to modeling and forecasting asset return volatility. Much of this relate to the development of time series models of volatility. This paper proposes an alternative method for forecasting volatility that does
Adam Clements, Ralf Becker
core

Unsupervised Pre-training of a Deep LSTM-based Stacked Autoencoder for Multivariate Time Series Forecasting Problems. [PDF]