AIMC Topic: Investments

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Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks.

PloS one
Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversaria...

Heteroscedasticity effects as component to future stock market predictions using RNN-based models.

PloS one
Heteroscedasticity effects are useful for forecasting future stock return volatility. Stock volatility forecasting provides business insight into the stock market, making it valuable information for investors and traders. Predicting stock volatility ...

The role of artificial intelligence and fintech in promoting eco-friendly investments and non-greenwashing practices in the US market.

Journal of environmental management
This study explores the intricate connections among financial technology (FinTech), artificial intelligence (AI), and eco-friendly markets in the US, shedding light on their dynamic interplay and implications for sustainable investment and policy str...

Regional economic forecast using Elman neural networks with wavelet function.

PloS one
Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible t...

A multinational study on artificial intelligence adoption: Clinical implementers' perspectives.

International journal of medical informatics
BACKGROUND: Despite substantial progress in AI research for healthcare, translating research achievements to AI systems in clinical settings is challenging and, in many cases, unsatisfactory. As a result, many AI investments have stalled at the proto...

Evaluation and screening of technology start-ups based on PCA and GA-BPNN.

PloS one
PURPOSE: Due to the existence of information opacity, there is a common problem of adverse selection in the process of screening alternative technology start-ups (TSs) and determining investment targets by venture capital institutions, which does not...

Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.

Environmental science and pollution research international
Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon pri...

Modeling of Machine Learning-Based Extreme Value Theory in Stock Investment Risk Prediction: A Systematic Literature Review.

Big data
The stock market is heavily influenced by global sentiment, which is full of uncertainty and is characterized by extreme values and linear and nonlinear variables. High-frequency data generally refer to data that are collected at a very fast rate bas...

The Impact of the COVID-19 Pandemic on Stock Market Performance in G20 Countries: Evidence from Long Short-Term Memory with a Recurrent Neural Network Approach.

Big data
In light of developing and industrialized nations, the G20 economies account for a whopping two-thirds of the world's population and are the largest economies globally. Public emergencies have occasionally arisen due to the rapid spread of COVID-19 g...