The role of big data research methodologies in describing investor risk attitudes and predicting stock market performance : deep learning and risk tolerance
Year of publication: |
2022
|
---|---|
Authors: | Heo, Wookjae ; Kwak, Eun Jin ; Grable, John E. |
Published in: |
Handbook of research on new challenges and global outlooks in financial risk management. - Hershey, PA, USA : IGI Global, Business Science Reference, ISBN 978-1-7998-8609-9. - 2022, p. 293-315
|
Subject: | Börsenkurs | Share price | Finanzanalyse | Financial analysis | Prognoseverfahren | Forecasting model | Anlageverhalten | Behavioural finance | Risikopräferenz | Risk attitude | Big Data | Big data | Künstliche Intelligenz | Artificial intelligence | Theorie | Theory | Aktienindex | Stock index | USA | United States |
-
Walking down wall street with a tablet : a survey of stock market predictions using the web
Nardo, Michela, (2016)
-
Stock investment strategy combining earnings power index and machine learning
Jun, So Young, (2022)
-
Application of machine learning in algorithmic investment strategies on global stock markets
Grudniewicz, Jan, (2023)
- More ...
-
Kwak, Eun Jin, (2024)
-
Distrust of banks among the unbanked and banked
Grable, John E., (2023)
-
An assessment of the association between political orientation and financial risk tolerance
Grable, John E., (2022)
- More ...