AIMC Topic: Investments

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Improving stock trading decisions based on pattern recognition using machine learning technology.

PloS one Aug 6, 2021
PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of dail...
Investments Models, Economic Commerce Neural Networks, Computer Machine Learning Forecasting Decision Making
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Impact of chart image characteristics on stock price prediction with a convolutional neural network.

PloS one Jun 23, 2021
Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as AN...
Humans Forecasting Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Probability Commerce Models, Economic Investments
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Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms.

PloS one Jun 22, 2021
The aims are to improve the efficiency in analyzing the regional economic changes in China's high-tech industrial development zones (IDZs), ensure the industrial structural integrity, and comprehensively understand the roles of capital, technology, a...
Industry Economic Development China Models, Economic Machine Learning Investments Data Analysis Industrial Development Algorithms Technology
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Diversity-driven knowledge distillation for financial trading using Deep Reinforcement Learning.

Neural networks : the official journal of the International Neural Network Society Mar 17, 2021
Deep Reinforcement Learning (RL) is increasingly used for developing financial trading agents for a wide range of tasks. However, optimizing deep RL agents is notoriously difficult and unstable, especially in noisy financial environments, significant...
Deep Learning Financial Management Investments
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Dynamics of fractional order nonlinear system: A realistic perception with neutrosophic fuzzy number and Allee effect.

Journal of advanced research Dec 3, 2020
INTRODUCTION: The fusion of fractional order differential equations and fuzzy numbers has been widely used in modelling different engineering and applied sciences problems. In addition to these, the Allee effect, which is of high importance in field ...
Investments Uncertainty Perception Economic Development Humans Algorithms Fuzzy Logic Models, Theoretical Employment
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Innovative deep matching algorithm for stock portfolio selection using deep stock profiles.

PloS one Nov 4, 2020
Construction of a reliable stock portfolio remains an open issue in quantitative investment. Multiple machine learning models have been trained for stock portfolio selection, but their practical applicability remains limited due to the challenges pos...
Investments Deep Learning Models, Economic
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Robo-investment aversion.

PloS one Sep 17, 2020
In five experiments (N = 3,828), we investigate whether people prefer investment decisions to be made by human investment managers rather than by algorithms ("robos"). In all of the studies we investigate morally controversial companies, as it is pla...
Robotics Humans Economics, Behavioral Investments Attitude to Computers
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Action-specialized expert ensemble trading system with extended discrete action space using deep reinforcement learning.

PloS one Jul 27, 2020
Despite active research on trading systems based on reinforcement learning, the development and performance of research methods require improvements. This study proposes a new action-specialized expert ensemble method consisting of action-specialized...
Reinforcement, Psychology Deep Learning Time Factors Neural Networks, Computer Algorithms Commerce Investments Models, Economic Databases as Topic
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Recurrent convolutional neural kernel model for stock price movement prediction.

PloS one Jun 12, 2020
Stock price movement prediction plays important roles in decision making for investors. It was usually regarded as a binary classification task. In this paper, a recurrent convolutional neural kernel (RCNK) model was proposed, which learned complemen...
China Models, Economic Public Opinion Investments Neural Networks, Computer Databases, Factual Humans
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Effectively training neural networks for stock index prediction: Predicting the S&P 500 index without using its index data.

PloS one Apr 10, 2020
We propose a novel method for training neural networks to predict the future prices of stock indexes. Unlike previous works, we do not use target stock index data for training neural networks for index prediction. Instead, we use only the data of ind...
Models, Economic Neural Networks, Computer Investments Forecasting
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