Are missing values important for earnings forecasts? : a machine learning perspective
Year of publication: |
2022
|
---|---|
Authors: | Uddin, Ajim ; Tao, Xinyuan ; Chou, Chia-Ching ; Yu, Dantong |
Subject: | Machine learning | Analysts' earnings forecast | Coupled matrix factorization | Firm earnings prediction | Missing value estimation | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Finanzanalyse | Financial analysis | Prognose | Forecast | Gewinnprognose | Earnings announcement | Gewinn | Profit |
-
Forecasting earnings and returns : a review of recent advancements
Green, Jeremiah, (2022)
-
Man vs. machine learning : the term structure of earnings expectations and conditional biases
Binsbergen, Jules H. van, (2020)
-
The measurement of analysts' earnings forecast uncertainty
Hu, Chun, (2015)
- More ...
-
Are Missing Values Important for Earnings Forecast? A Machine Learning Perspective
Uddin, Ajim, (2022)
-
Attention based dynamic graph neural network for asset pricing
Uddin, Ajim, (2023)
-
The network factor of equity pricing : a signed graph Laplacian approach
Uddin, Ajim, (2024)
- More ...