Results 41 to 50 of about 223,849 (180)
Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting [PDF]
, 2018 We develop the methodology and a detailed case study in use of a class of Bayesian predictive synthesis (BPS) models for multivariate time series forecasting. This extends the recently introduced foundational framework of BPS to the multivariate setting,
Aastveit, Knut Are +3 more
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, 2016 We discuss Bayesian forecasting of increasingly high-dimensional time series, a key area of application of stochastic dynamic models in the financial industry and allied areas of business.
West, Mike, Xie, Meng, Zhao, Zoey Yi
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GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing [PDF]
Knowledge Discovery and Data MiningMultivariate time series forecasting (MTSF) is crucial for decision-making to precisely forecast the future values/trends, based on the complex relationships identified from historical observations of multiple sequences.
Chengqing Yu +6 more
semanticscholar +1 more source
HUTFormer: Hierarchical U-Net transformer for long-term traffic forecasting
Communications in Transportation ResearchTraffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential component of intelligent transportation.
Zezhi Shao +9 more
doaj +1 more source
Multivariate Financial Time-Series Prediction With Certified Robustness
IEEE Access, 2020 The futures market's forecasts are significant to investors and policymakers, where the application of deep learning approaches to finance has received a great deal of attention.
Hui Li +5 more
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A Combined Model for Multivariate Time Series Forecasting Based on MLP-Feedforward Attention-LSTM
IEEE Access, 2022 Multivariate time series forecasting has very great practical significance for a long time, and it has been attracting the attention of researchers from a diverse range of fields.
Yuntong Liu, Chunna Zhao, Yaqun Huang
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A note on forecasting demand using the multivariate exponential smoothing framework
, 2014 Simple exponential smoothing is widely used in forecasting economic time series. This is because it is quick to compute and it generally delivers accurate forecasts.
Poloni, Federico, Sbrana, Giacomo
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DEformer: Dual Embedded Transformer for Multivariate Time Series Forecasting
IEEE AccessDeep learning models have significantly addressed the challenges of multivariate time series forecasting. Recently, Transformer-based models which have primarily focused on either temporal or inter-variate (spatial) dependencies have demonstrated ...
Minje Kim, Suwon Lee, Sang-Min Choi
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Factor-Based Framework for Multivariate and Multi-step-ahead Forecasting of Large Scale Time Series
Frontiers in Big Data, 2021 State-of-the-art multivariate forecasting methods are restricted to low dimensional tasks, linear dependencies and short horizons. The technological advances (notably the Big data revolution) are instead shifting the focus to problems characterized by a ...
Jacopo De Stefani, Gianluca Bontempi
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Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical ...
Francis X. Diebold +3 more
core +6 more sources