Machine learningBig data analysisPractitioners allocate substantial resources to technical analysis whereas academic theories of market efficiency rule out technical trading profitability. We sdoi:10.2139/ssrn.3233119Brogaard, JonathanZareei, Abalfazl
Predicting a stock market by using a machine learning technique is among the popular strategies for any investor or trader. For this process, it all starts with data gathering as wide as past stock prices, trading volumes, economical indicators, and even the news sentiment. All this data is t...
Markus Leippold, Qian Wang, Wenyu Zhou, Machine learning in the Chinese stock market, Journal of Financial Economics, Volume 145, Issue 2, Part A, 2022, Pages 64-82, ISSN 0304-405X, https://doi.org/10.1016/j.jfineco.2021.08.017. ...
Applying machine learning algorithms to predict the stock price trend in the stock market – The case of Vietnam Tran Phuoc, Pham Thi Kim Anh, Phan Huy Tam & Chien V. Nguyen Humanities and Social Sciences Communications volume 11, Article number: 393 (2024) Cite this article 78k Accesses...
We add to the emerging literature on empirical asset pricing in the Chinese stock market by building and analyzing a comprehensive set of return prediction factors using various machine learning algorithms. Contrasting previous studies for the US market, liquidity emerges as the most important predictor...
A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data Article 04 January 2021 Introduction The relation between the company market value and company events attracted the research community’s attention from the very moment it became technically possible...
Recently there has been much development and interest in machine learning, with the most promising results in speech and image recognition. This research paper analyzes the performance of a deep learning method, long short-term memory neural networks (LSTM’s), applied to the ...
Explore the intersection of AI and finance. Learn how machine learning algorithms can revolutionize stock market prediction, giving you a competitive edge in trading.
Multiple Linear Regression (MLR) is a statistical modeling technique that has been commonly used in predicting the behavior of a target variable, such as stock prices, based on the values of several predictor variables, such as open, low, and high prices. The MLR model attempts to fit a lin...
Financial time series prediction is a very important economical problem but the data available is very noisy. In this thesis, we explain the use of statistical and machine learning methods for stock market prediction and we evaluate the performance of these methods on data from the S&P/TSX 60 ...