Results 291 to 300 of about 429,127 (323)

Threshold MIDAS Forecasting of Canadian Inflation Rate

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We propose several threshold mixed data sampling (TMIDAS) autoregressive models to forecast the Canadian inflation rate using predictors observed at different frequencies. These models take two low‐frequency variables and a high‐frequency index as threshold variables.
Chaoyi Chen, Yiguo Sun, Yao Rao
wiley   +1 more source

Forecasting With Machine Learning Shadow‐Rate VARs

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Interest rates are fundamental in macroeconomic modeling. Recent studies integrate the effective lower bound (ELB) into vector autoregressions (VARs). This paper studies shadow‐rate VARs by using interest rates as a latent variable near the ELB to estimate their shadow‐rate values.
Michael Grammatikopoulos
wiley   +1 more source

Deep Learning and Econometric Time Series Analysis: An Assessment of Daily Return Forecasts

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT We provide an in‐depth assessment of univariate financial time series analysis via machine learning followed by a thorough discussion beyond the discussion on daily return predictability. We simulate economic time series and present an in‐depth assessment of relevant hyperparameter tuning and study the ability of competing deep learning ...
Theo Berger
wiley   +1 more source

Forecasting Carbon Prices: A Literature Review

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Carbon emissions trading is utilized by a growing number of states as a significant tool for addressing greenhouse gas emissions (GHG), global warming problem and the climate crisis. Accurate forecasting of carbon prices is essential for effective policy design and investment strategies in climate change mitigation.
Konstantinos Bisiotis   +2 more
wiley   +1 more source

Scaling‐Aware Rating of Poisson‐Limited Demand Forecasts

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecast quality should be assessed in the context of what is possible in theory and what is reasonable to expect in practice. Often, one can identify an approximate upper bound to a probabilistic forecast's sharpness, which sets a lower, not necessarily achievable, limit to error metrics.
Malte C. Tichy   +4 more
wiley   +1 more source

Stock Portfolio Management Based on AI Technology

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecasting stock performance is crucial for formulating a profitable trading approach aimed at achieving significant gains. In addition, prediction results serve as essential prerequisites for creating and optimizing active investment portfolios.
Alejandro Moreno Alonso   +1 more
wiley   +1 more source

A Two‐Stage NLP‐Driven Framework for Interval‐Valued Carbon Price Prediction Using Sentiment Analysis and Error Correction

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Accurate predictions of carbon prices are essential for efficient administration and stable operation of carbon markets. Previous studies have mostly focused on point or interval predictions based on point‐valued data. These approaches insufficiently capture the full extent of market volatility.
Di Sha   +4 more
wiley   +1 more source

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