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Financial innovation : FIN
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1
Forecasting relative returns for S&P 500 stocks using machine learning
Htet Htet Htun
;
Biehl, Michael
;
Petkov, Nicolai
- In:
Financial innovation : FIN
10
(
2024
),
pp. 1-16
multiple previous relative returns and apply the random forest (RF), support vector machine (SVM), and
long
short-term
memory
…
Persistent link: https://www.econbiz.de/10014547210
Saved in:
2
A hybrid econometrics and machine learning based modeling of realized volatility of natural gas
Kristjanpoller Rodríguez, Werner
- In:
Financial innovation : FIN
10
(
2024
),
pp. 1-32
best forecasting from heterogeneous autoregressive and
long
short-term
memory
models are used to determine the infuence of …
Persistent link: https://www.econbiz.de/10014535318
Saved in:
3
An efficient stock market prediction model using hybrid feature reduction method based on variational autoencoders and recursive feature elimination
Gunduz, Hakan
- In:
Financial innovation : FIN
7
(
2021
),
pp. 1-24
In this study, the hourly directions of eight banking stocks in Borsa Istanbul were predicted using linear-based, deep-learning (LSTM) and ensemble learning (LightGBM) models. These models were trained with four different feature sets and their performances were evaluated in terms of accuracy...
Persistent link: https://www.econbiz.de/10012510234
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