A bi‐level ensemble learning approach to complex time series forecasting: Taking exchange rates as an example.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1385, doi. 10.1002/for.2971
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- Article
Works matching IS 02776693 AND DT 2023 AND VI 42 AND IP 6
Results: 15
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Fama–French three versus five, which model is better? A machine learning approach.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1461, doi. 10.1002/for.2970
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- Article
3
Forecasting the 2020 and 2024 U.S. presidential elections.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1519, doi. 10.1002/for.2969
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- Article
4
Analysis of the relevance of sentiment data for the prediction of excess returns in a multiasset framework.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1360, doi. 10.1002/for.2967
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- Article
5
Deep learning model for temperature prediction: A case study in New Delhi.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1445, doi. 10.1002/for.2966
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- Article
6
Modeling and forecasting percent changes in national park visitation using social media.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1502, doi. 10.1002/for.2965
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7
Can Brazilian Central Bank communication help to predict the yield curve?
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1429, doi. 10.1002/for.2964
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8
Meta‐learning how to forecast time series.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1476, doi. 10.1002/for.2963
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9
How media content influences economic expectations: Evidence from a global expert survey.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1295, doi. 10.1002/for.2961
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10
Predicting customer churn using grey wolf optimization‐based support vector machine with principal component analysis.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1329, doi. 10.1002/for.2960
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11
Cross‐sectional return dispersion and stock market volatility: Evidence from high‐frequency data.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1309, doi. 10.1002/for.2959
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12
Forecasting the exchange rate with the Taylor rule model during times of alternative monetary policies.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1341, doi. 10.1002/for.2957
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- Article
13
Using a machine learning approach and big data to augment WASDE forecasts: Empirical evidence from US corn yield.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1370, doi. 10.1002/for.2956
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- Article
14
Bayesian bilinear neural network for predicting the mid‐price dynamics in limit‐order book markets.
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- Journal of Forecasting, 2023, v. 42, n. 6, p. 1407, doi. 10.1002/for.2955
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15
Issue Information.
- Published in:
- Journal of Forecasting, 2023, v. 42, n. 6, p. 1293, doi. 10.1002/for.2866
- Publication type:
- Article