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Applications of Intelligent Model to Analyze the Green Finance for Environmental Development in the Context of Artificial Intelligence.

Computational intelligence and neuroscience
Green finance can be referred to as financial investments made on sustainable projects and policies that focus on a sustainable economy. The procedures include promoting renewable energy sources, energy efficiency, water sanitation, industrial pollut...

Application of Deep Learning Model in the Avoidance of Investment Risk of Multinational Enterprises.

Computational intelligence and neuroscience
With the continuous improvement and development of the socialist market economic system, China's economic development has full momentum, but the domestic market is no longer sufficient to meet the needs of enterprise development. China has always foc...

Monitoring and Analysis of Venture Capital and Corporate Fraud Based on Deep Learning.

Computational intelligence and neuroscience
With the continuous expansion of global investment institutions, the development of the investment industry is gradually accelerating, but the risks behind the investment are also constantly increasing. Using the data of A-share companies in China's ...

Exploration of Stock Portfolio Investment Construction Using Deep Learning Neural Network.

Computational intelligence and neuroscience
To study the intelligent and efficient stock portfolio in China's financial market, based on the relevant theories such as deep learning (DL) neural network (NN) and stock portfolio, this study selects 111 stable stocks from the constituent stocks of...

The Application of Artificial Intelligence Technology in the Asset Management of Start-Ups in the Context of Deep Learning.

Computational intelligence and neuroscience
With the coninuous improvement and development of artificial intelligence (AI) technology, this technology has been used in the asset management of companies. To improve the asset management level of Chinese start-ups, firstly, back-propagation neura...

Using Kernel Method to Include Firm Correlation for Stock Price Prediction.

Computational intelligence and neuroscience
In this work, we propose AGKN (attention-based graph learning kernel network), a novel framework to incorporate information of correlated firms of a target stock for its price prediction in an end-to-end way. We first construct a stock-axis attention...

Empirical Analysis for Stock Price Prediction Using NARX Model with Exogenous Technical Indicators.

Computational intelligence and neuroscience
Stock price prediction is one of the major challenges for investors who participate in the stock markets. Therefore, different methods have been explored by practitioners and academicians to predict stock price movement. Artificial intelligence model...

Construction of a Fundamental Quantitative Evaluation Model of the A-Share Listed Companies Based on the BP Neural Network.

Computational intelligence and neuroscience
Quantitative investment has attracted much attention, along with the vigorous development of Fintech. Fundamentals are one of the most important reference factors for investment. Before quantitative trading, evaluation of fundamentals may have been m...

Deep reinforcement learning stock market trading, utilizing a CNN with candlestick images.

PloS one
Billions of dollars are traded automatically in the stock market every day, including algorithms that use neural networks, but there are still questions regarding how neural networks trade. The black box nature of a neural network gives pause to entr...

Deep Neural Networks Applied to Stock Market Sentiment Analysis.

Sensors (Basel, Switzerland)
The volume of data is growing exponentially and becoming more valuable to organizations that collect it, from e-commerce data, shipping, audio and video logs, text messages, internet search queries, stock market activity, financial transactions, the ...