This project involved using R to implement a toy algorithmic trading system. Using neuralnet and quantmod packages ... 1), x7=Lag(as.numeric(EM10), 1)) We were experimenting with neural nets on this ...

e.g. │ generated with `pip freeze > requirements.txt` │ ├── setup.cfg <- Configuration file for flake8 │ └── neural_network_trading_algo <- Source code for use in this project. │ ├── __init__.py <- ...

In this work we propose a trading agent based on a neural network ensemble that predicts if one stock is going to raise or fall instead of predicting its future values. To show the efficiency of our ...

Abstract: The optimization of algorithmic trading models ... of market trends and the optimization of trading decisions. This study examines the effects of optimizing technical analyses with neural ...

Faster, more powerful graphics processing units (GPUs) have the potential to transform algorithmic ... automated trading? Mature electronic markets disseminate new information at high speed. Trading ...

The development of a predictive system that correctly forecasts trading signals is crucial for algorithmic trading and investment ... These TIs are used as inputs for an artificial neural network and ...