The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index
Thi Thu Giang Nguyen, Robert Ślepaczuk
| Year of publication: |
2022
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|---|---|
| Authors: | Thi Thu Giang Nguyen ; Ślepaczuk, Robert |
| Publisher: |
Warsaw : University of Warsaw, Faculty of Economic Sciences |
| Subject: | algorithmic investment strategies | machine learning | testing architecture | deep learning | recurrent neural networks | LSTM | technical indicators | forecasting financial-time series | hyperparameter tuning S&P 500 Index | Finanzanalyse | Financial analysis | Neuronale Netze | Neural networks | Prognoseverfahren | Forecasting model | Theorie | Theory | Portfolio-Management | Portfolio selection | Aktienindex | Stock index | Wirtschaftsindikator | Economic indicator |
freely available
| Extent: | 1 Online-Ressource (circa 34 Seiten) Illustrationen |
|---|---|
| Series: | Working papers. - Warsaw : [Faculty of Economic Sciences, University of Warsaw], ISSN 2957-0506, ZDB-ID 2890271-3. - Vol. no. 2022, 29 = 405 |
| Type of publication: | Book / Working Paper |
| Type of publication (narrower categories): | Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper |
| Language: | English |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013474013