The normalized entropy of this set is a reasonable index for formal definition of complexity of a given graph. This property allows us making every day short-term predictions of big crises at stock markets.AlexanderRubchinsky
pythonstock-marketindicatorsalgorithm-trading UpdatedJun 25, 2023 Python Load more… Add a description, image, and links to thealgorithm-tradingtopic page so that developers can more easily learn about it. To associate your repository with thealgorithm-tradingtopic, visit your repo's landing page ...
This paper improves stock market prediction based on genetic algorithms (GA) and wavelet neural networks (WNN) and reports significantly better accuracies compared to existing approaches to stock market prediction, including the hierarchical GA (HGA) WNN. Specifically, we added information such as tr...
Machine learning based stock market analysis: a short survey. In: Innovative data communication technologies and application. Springer International Publishing; 2020. pp. 12–26. Hirchoua B, Ouhbi B, Frikh B. Deep reinforcement learning based trading agents: risk curiosity driven learning for ...
Statistical Analysis and Agent-Based Microstructure Modeling of High-Frequency Financial Trading A simulation of high-frequency market data is performed with the Genoa Artificial Stock Market. Heterogeneous agents trade a risky asset in exchange for ca... L Ponta,E Scalas,M Raberto,... - 《IEEE...
MULTIVERSE: Mining Collective Data Science Knowledge from Code on the Web to Suggest Alternative Analysis Approaches Mike A. Merrill, Ge Zhang, Tim Althoff code 1 Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes Maya Okawa, Tomoh...
All in all, AI has the potential to significantly improve the efficiency and accuracy of stock market analysis and decision-making, which can ultimately lead to better investment outcomes for investors (Ashta and Herrmann, 2021, Milana and Ashta, 2021). Long Short-Term Memory (LSTM) is a ...
Machine Learning Models in Stock Market Prediction The paper focuses on predicting the Nifty 50 Index by using 8 Supervised Machine Learning Models. The techniques used for empirical study are Adaptive Boost (AdaBoost), k-Nearest Neighbors (kNN), Linear Regression (LR), Artificial Neural... G ...
Stock Analysis: This Retail Stocks forecast is designed for investors and analysts who need predictions for the best stocks to invest in the retail estate sector (see Retail Stocks Package). It includes 20 stocks with bullish and bearish signals: Top 10 Retail stocks for the long position Top ...
Technical analysis Machine learning Optimization Stock market COVID-19 1. Introduction The worldwide stock market was globally affected by the COVID-19 pandemic. In most countries, stock markets were negatively influenced by the spread of the COVID-19 disease [[1], [2], [3], [4], [5],...