Deep neural networks, gradient-boosted trees, random forests : statistical arbitrage on the S&P 500
Year of publication: |
1 June 2017
|
---|---|
Authors: | Krauss, Christopher ; Do, Xuan Anh ; Huck, Nicolas |
Published in: |
European journal of operational research : EJOR. - Amsterdam : Elsevier, ISSN 0377-2217, ZDB-ID 243003-4. - Vol. 259.2017, 2 (1.6.), p. 689-702
|
Subject: | Finance | Deep learning | Gradient-boosting | Random Forests | Ensemble learning | Neuronale Netze | Neural networks | Forstwirtschaft | Forestry | Theorie | Theory | Lernprozess | Learning process | Arbitrage | Stochastischer Prozess | Stochastic process |
-
Deep neural networks, gradient-boosted trees, random forests : statistical arbitrage on the S&P 500
Krauss, Christopher, (2016)
-
Accelerated share repurchase and other buyback programs : what neural networks can bring
Guéant, Olivier, (2020)
-
Machine learning advances for time series forecasting
Masini, Ricardo P., (2020)
- More ...
-
Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500
Krauss, Christopher, (2016)
-
Deep neural networks, gradient-boosted trees, random forests : statistical arbitrage on the S&P 500
Krauss, Christopher, (2016)
-
From wheel of fortune to wheel of misfortune : Financial crises, cycles, and consumer predation
Mesly, Olivier, (2020)
- More ...