deep-learning methods have been increasingly used for gold price prediction. For instance, using association rules and the LSTM mode, Boongasame et al. (2022) predicted the price of gold. Vidal and Kristjanpoller (2020) developed a hybrid of convolutional...
Li, Y., et al.: The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning. Int. J. Forecast. 36(4), 1541–1562 (2020) Article Google Scholar Wu, B., et al.: Effective crude oil price forecasting using new text-based and ...
In this work we show that prediction uncertainty estimates gleaned from deep learning models can be useful inputs for influencing the relative allocation of risk capital across trades. In this way, consideration of uncertainty is important because it permits the scaling of investment size across trad...
deep-learning methods have been increasingly used for gold price prediction. For instance, using association rules and the LSTM mode, Boongasame et al. (2022) predicted the price of gold. Vidal and Kristjanpoller (2020) developed a hybrid of convolutional...
Artificial intelligence Artificial rabbits optimization algorithm Deep learning LSTM Stock price prediction 1. Introduction A stock market is a place where people can buy and sell stocks of companies that are publicly traded with the goal of making money. It is an important indicator of a country'...
Analysis of Bitcoin Price Prediction Using Machine Learning 2023, Journal of Risk and Financial Management Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic 2022, Information Systems Frontiers ...
Used multiple optimization methods to improve the performance of deep learning methods. The primary problem of their work is overfitting. The research problem of predicting Bitcoin price trend has some similarities with stock market price prediction. Hidden features and noises embedded in the price ...
Price prediction module The reinforcement learning module based on: the design for 6 actions(sell, short, sell_hold, short_hold, sell, cover) The reinforcement learning module based on: Using the up and down line of VWAP or BBIBOLL to transform the price into (-1,1) ...
(2023). A novel hybrid model based on deep learning and error correction for crude oil futures prices forecast. Resources Policy, 83, 103602. Article Google Scholar Xing, H., Wang, G., Liu, C., & Suo, M. (2021). PM2.5 concentration modeling and prediction by using temperature-based ...
deep learning model architectures the long short-term memory (LSTM), the gated recurrent unit (GRU), the convolutional neural network (CNN), their variants, and hybridizations, to predict the next day’s closing price of the real estate index S &P500-60. We incorporate diverse data sources ...