Works matching IS 02776693 AND DT 2023 AND VI 42 AND IP 8
Results: 21
Forecasting base metal prices with exchange rate expectations.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2341, doi. 10.1002/for.3018
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Forecasting the different influencing factors of household food waste behavior in China under the COVID‐19 pandemic.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2322, doi. 10.1002/for.3017
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Policy uncertainty and stock market volatility revisited: The predictive role of signal quality.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2307, doi. 10.1002/for.3016
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Time‐varying partial‐directed coherence approach to forecast global energy prices with stochastic volatility model.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2292, doi. 10.1002/for.3015
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The battle of the factors: Macroeconomic variables or investor sentiment?
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2280, doi. 10.1002/for.3014
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Optimal out‐of‐sample forecast evaluation under stationarity.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2249, doi. 10.1002/for.3013
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Regularized Poisson regressions predict regional innovation output.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2197, doi. 10.1002/for.3012
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The benefit of the Covid‐19 pandemic on global temperature projections.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2079, doi. 10.1002/for.3011
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Multiobjective portfolio optimization: Forecasting and evaluation under investment horizon heterogeneity.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2167, doi. 10.1002/for.3010
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Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2139, doi. 10.1002/for.3009
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Variable selection for classification and forecasting of the family firm's socioemotional wealth.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2063, doi. 10.1002/for.3008
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Daily tourism forecasting through a novel method based on principal component analysis, grey wolf optimizer, and extreme learning machine.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2121, doi. 10.1002/for.3007
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Large covariance estimation using a factor model with common and group‐specific factors.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2217, doi. 10.1002/for.3006
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Uncertainty analysis–forecasting system based on decomposition–ensemble framework for PM<sub>2.5</sub> concentration forecasting in China.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2027, doi. 10.1002/for.3005
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Analyzing and forecasting electricity price using regime‐switching models: The case of New Zealand market.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2011, doi. 10.1002/for.3004
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Deep learning on mixed frequency data.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2099, doi. 10.1002/for.3003
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Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 2045, doi. 10.1002/for.3002
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Forecasting global solar radiation using a robust regularization approach with mixture kernels.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 1989, doi. 10.1002/for.3001
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Forecasting intraday financial time series with sieve bootstrapping and dynamic updating.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 1973, doi. 10.1002/for.3000
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Mixed‐frequency predictive regressions with parameter learning.
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- Journal of Forecasting, 2023, v. 42, n. 8, p. 1955, doi. 10.1002/for.2999
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Issue Information.
- Published in:
- Journal of Forecasting, 2023, v. 42, n. 8, p. 1953, doi. 10.1002/for.2868
- Publication type:
- Article