AIMC Topic: Investments

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Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

PloS one
In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. ...

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

PloS one
Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning mod...

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PloS one
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market tech...

A novel approach to prioritizing health technology investments using integrated AI-based ranking model.

Journal of health organization and management
PURPOSE: Health technologies are an issue that directly affects the sustainability and quality of health services. Due to budget constraints, it is not financially possible for businesses to apply comprehensive improvement strategies to all these cri...

Bridging sustainable finance, AI, and clean technology amid economic shocks: How are they connected in median and extreme conditions?

Journal of environmental management
We investigate the intricate relationships between sustainable markets, artificial intelligence (AI), and clean technology, focusing on their contributions to investment and risk management. Employing the Quantile-on-Quantile (QQ) connectedness frame...

A two-stage forecasting model using random forest subset-based feature selection and BiGRU with attention mechanism: Application to stock indices.

PloS one
The heteroscedastic and volatile characteristics of stock price data have attracted the interest of researchers from various disciplines, particularly in the realm of price forecasting. The stock market's non-stationary and volatile nature, driven by...

Stock price forecasting based on Hausdorff fractional grey model with convolution and neural network.

Mathematical biosciences and engineering : MBE
Forecast of stock prices can guide investors' investment decisions. Due to the high-dimensional and long-memory characteristics of stock data, it is difficult to predict. The fractional grey model with convolution (FGMC (1, m)) can be used to predict...

An Intelligent Future for Medical Imaging: A Market Outlook on Artificial Intelligence for Medical Imaging.

Journal of the American College of Radiology : JACR
Radiologists today are under increasing work pressure. We surveyed radiologists in the United States across practice settings, and the overwhelming majority reported an increased workload. Artificial intelligence (AI), which includes machine learning...

Should You Trust Your Money to a Robot?

Big data
Financial markets emanate massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans. I contrast human and machine strengths and weaknesses in making investment decisions. The analysis rev...