Search Results - "International journal of forecasting"

Forecasting: theory and practice by Petropoulos, Fotios, Apiletti, Daniele, Assimakopoulos, Vassilios, Babai, Mohamed Zied, Barrow, Devon K., Ben Taieb, Souhaib, Bergmeir, Christoph, Bessa, Ricardo J., Bijak, Jakub, Boylan, John E., Browell, Jethro, Carnevale, Claudio, Castle, Jennifer L., Cirillo, Pasquale, Clements, Michael P., Cordeiro, Clara, Cyrino Oliveira, Fernando Luiz, De Baets, Shari, Dokumentov, Alexander, Ellison, Joanne, Fiszeder, Piotr, Franses, Philip Hans, Frazier, David T., Gilliland, Michael, Gönül, M. Sinan, Goodwin, Paul, Grossi, Luigi, Grushka-Cockayne, Yael, Guidolin, Mariangela, Guidolin, Massimo, Gunter, Ulrich, Guo, Xiaojia, Guseo, Renato, Harvey, Nigel, Hendry, David F., Hollyman, Ross, Januschowski, Tim, Jeon, Jooyoung, Jose, Victor Richmond R., Kang, Yanfei, Koehler, Anne B., Kolassa, Stephan, Kourentzes, Nikolaos, Leva, Sonia, Li, Feng, Litsiou, Konstantia, Makridakis, Spyros, Martin, Gael M., Martinez, Andrew B., Meeran, Sheik, Modis, Theodore, Nikolopoulos, Konstantinos, Önkal, Dilek, Paccagnini, Alessia, Panagiotelis, Anastasios, Panapakidis, Ioannis, Pavía, Jose M., Pedio, Manuela, Pedregal, Diego J., Pinson, Pierre, Ramos, Patrícia, Rapach, David E., Reade, J. James, Rostami-Tabar, Bahman, Rubaszek, Michał, Sermpinis, Georgios, Shang, Han Lin, Spiliotis, Evangelos, Syntetos, Aris A., Talagala, Priyanga Dilini, Talagala, Thiyanga S., Tashman, Len, Thomakos, Dimitrios, Thorarinsdottir, Thordis, Todini, Ezio, Trapero Arenas, Juan Ramón, Wang, Xiaoqian, Winkler, Robert L., Yusupova, Alisa, Ziel, Florian

“…Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with…”
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Temporal Fusion Transformers for interpretable multi-horizon time series forecasting by Lim, Bryan, Arık, Sercan Ö., Loeff, Nicolas, Pfister, Tomas

“…Multi-horizon forecasting often contains a complex mix of inputs – including static (i.e. time-invariant) covariates, known future inputs, and other exogenous…”
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DeepAR: Probabilistic forecasting with autoregressive recurrent networks by Salinas, David, Flunkert, Valentin, Gasthaus, Jan, Januschowski, Tim

“…Probabilistic forecasting, i.e., estimating a time series’ future probability distribution given its past, is a key enabler for optimizing business processes…”
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Recurrent Neural Networks for Time Series Forecasting: Current status and future directions by Hewamalage, Hansika, Bergmeir, Christoph, Bandara, Kasun

“…Recurrent Neural Networks (RNNs) have become competitive forecasting methods, as most notably shown in the winning method of the recent M4 competition…”
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The M4 Competition: 100,000 time series and 61 forecasting methods by Makridakis, Spyros, Spiliotis, Evangelos, Assimakopoulos, Vassilios

“…The M4 Competition follows on from the three previous M competitions, the purpose of which was to learn from empirical evidence both how to improve the…”
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Forecasting for COVID-19 has failed by Ioannidis, John P.A., Cripps, Sally, Tanner, Martin A.

“…Epidemic forecasting has a dubious track-record, and its failures became more prominent with COVID-19. Poor data input, wrong modeling assumptions, high…”
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A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting by Smyl, Slawek

“…This paper presents the winning submission of the M4 forecasting competition. The submission utilizes a dynamic computational graph neural network system that…”
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Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond by Hong, Tao, Pinson, Pierre, Fan, Shu, Zareipour, Hamidreza, Troccoli, Alberto, Hyndman, Rob J.

“…The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply,…”
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Probabilistic electric load forecasting: A tutorial review by Hong, Tao, Fan, Shu

“…Load forecasting has been a fundamental business problem since the inception of the electric power industry. Over the past 100 plus years, both research…”
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Retail forecasting: Research and practice by Fildes, Robert, Ma, Shaohui, Kolassa, Stephan

“…This paper reviews the research literature on forecasting retail demand. We begin by introducing the forecasting problems that retailers face, from the…”
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The M4 Competition: Results, findings, conclusion and way forward by Makridakis, Spyros, Spiliotis, Evangelos, Assimakopoulos, Vassilios

“…The M4 competition is the continuation of three previous competitions started more than 45 years ago whose purpose was to learn how to improve forecasting…”
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The impact of sentiment and attention measures on stock market volatility by Audrino, Francesco, Sigrist, Fabio, Ballinari, Daniele

“…We analyze the impact of sentiment and attention variables on the stock market volatility by using a novel and extensive dataset that combines social media,…”
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A new metric of absolute percentage error for intermittent demand forecasts by Kim, Sungil, Kim, Heeyoung

“…The mean absolute percentage error (MAPE) is one of the most widely used measures of forecast accuracy, due to its advantages of scale-independency and…”
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M5 accuracy competition: Results, findings, and conclusions by Makridakis, Spyros, Spiliotis, Evangelos, Assimakopoulos, Vassilios

“…In this study, we present the results of the M5 “Accuracy” competition, which was the first of two parallel challenges in the latest M competition with the aim…”
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Kaggle forecasting competitions: An overlooked learning opportunity by Bojer, Casper Solheim, Meldgaard, Jens Peder

“…We review the results of six forecasting competitions based on the online data science platform Kaggle, which have been largely overlooked by the forecasting…”
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The impact of the COVID-19 pandemic on business expectations by Meyer, Brent H., Prescott, Brian, Sheng, Xuguang Simon

“…We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a…”
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Electricity price forecasting: A review of the state-of-the-art with a look into the future by Weron, Rafał

“…A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the last 15 years, with varying degrees of success. This review…”
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Principles and algorithms for forecasting groups of time series: Locality and globality by Montero-Manso, Pablo, Hyndman, Rob J.

“…Global methods that fit a single forecasting method to all time series in a set have recently shown surprising accuracy, even when forecasting large groups of…”
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Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants by Chen, Wei, Xu, Huilin, Jia, Lifen, Gao, Ying

“…In recent years, Bitcoin exchange rate prediction has attracted the interest of researchers and investors. Some studies have used traditional statistical and…”
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FFORMA: Feature-based forecast model averaging by Montero-Manso, Pablo, Athanasopoulos, George, Hyndman, Rob J., Talagala, Thiyanga S.

“…We propose an automated method for obtaining weighted forecast combinations using time series features. The proposed approach involves two phases. First, we…”
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