# Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets

@article{Calabuig2020DreamingML, title={Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets}, author={J. M. Calabuig and Herv{\'e} Falciani and Enrique Alfonso S{\'a}nchez-P{\'e}rez}, journal={ArXiv}, year={2020}, volume={abs/1907.05697} }

## 14 Citations

A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading Rules

- Computer ScienceArXiv
- 2021

A novel end-to-end model based on the neural encoder-decoder framework combined with DRL is proposed to learn single instrument trading strategies from a long sequence of raw prices of the instrument.

Semi-Lipschitz functions and machine learning for discrete dynamical systems on graphs

- Mathematics, Computer ScienceMach. Learn.
- 2022

The main objective is to explain the role of the lack of symmetry of quasi-metrics in the proposal: the irreversibility of dynamical processes is reflected in the asymmetry of their definition.

Analysing Stock Market Trend Prediction using Machine & Deep Learning Models: A Comprehensive Review

- Business2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)
- 2020

The applications of intelligent financial forecasting play an utmost important role in facilitating the investment decisions activities of many investors. With the right insight information, the…

Self-defined information indices: application to the case of university rankings

- Computer ScienceScientometrics
- 2020

A new and simple algorithm is presented to calculate an approximation of these indices using some standard bibliometric variables, such as the number of citations from the scientific output of universities and thenumber of articles per quartile.

Design Trend Forecasting by Combining Conceptual Analysis and Semantic Projections: New Tools for Open Innovation

- Computer Science
- 2021

A new trend analysis and forecasting method (Deflexor) is described, which is intended to help inform decisions in almost any field of human social activity, including, for example, business, art and design.

Evaluation Optimal Prediction Performance of MLMs on High-volatile Financial Market Data

- Computer ScienceInternational Journal of Advanced Computer Science and Applications
- 2022

The findings of study concludes that the algorithm of RF is most appropriate for nonlinear approximation/evaluation and the algorithms of SVR is most useful for high-frequency time-series data estimation.

Index spaces and standard indices in metric modelling

- Mathematics, EconomicsNonlinear Analysis: Modelling and Control
- 2022

We analyze the basic structure of certain metric models, which are constituted by an index I acting on a metric space (D; d) representing a relevant property of the elements of D. We call such a…

A Data Slicing Method to Improve Machine Learning Model Accuracy in Bankruptcy Prediction

- Computer ScienceICDLT
- 2021

According to the findings in this research, the most related metric and the best variable to slice on to get a predictable sliced dataset turn out to be “Solvency Ratio” both in Chinese and Polish data.

McShane-Whitney extensions for fuzzy Lipschitz maps

- Mathematics, Computer ScienceFuzzy Sets Syst.
- 2021

Enhanced Food Safety Through Deep Learning for Food Recalls Prediction

- Computer ScienceDS
- 2020

A set of deep and machine learning techniques employing time series forecasting to provide insights regarding the risk associated with each product category concerning potential food recalls and an approach based on reinforcement learning which utilizes historical recall announcements for predicting future recalls that leads to timely recalls and contributes to enhanced food safety across the supply chain are introduced.

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