Version 1
: Received: 17 September 2024 / Approved: 18 September 2024 / Online: 20 September 2024 (03:35:31 CEST)
How to cite:
Gottimukkala, S. R. Automating Portfolio Replication with Stock Market Algorithms. Preprints2024, 2024091388. https://doi.org/10.20944/preprints202409.1388.v1
Gottimukkala, S. R. Automating Portfolio Replication with Stock Market Algorithms. Preprints 2024, 2024091388. https://doi.org/10.20944/preprints202409.1388.v1
Gottimukkala, S. R. Automating Portfolio Replication with Stock Market Algorithms. Preprints2024, 2024091388. https://doi.org/10.20944/preprints202409.1388.v1
APA Style
Gottimukkala, S. R. (2024). Automating Portfolio Replication with Stock Market Algorithms. Preprints. https://doi.org/10.20944/preprints202409.1388.v1
Chicago/Turabian Style
Gottimukkala, S. R. 2024 "Automating Portfolio Replication with Stock Market Algorithms" Preprints. https://doi.org/10.20944/preprints202409.1388.v1
Abstract
This study aims to explore methods for automating the replication of correlated portfolios across shares using various algorithms. The goal is to select one algorithm for implementation in a visualization tool that will facilitate portfolio building. The dynamics of the stock market provide a comprehensive view of the global economy, acting as a catalyst for stakeholders to participate and benefit various sectors financially, primarily through investments in companies that yield returns and contribute to the economy. The evaluation and comparison of these algorithms are crucial for making well-informed decisions regarding the core objectives of the study. Ultimately, a determination will be made as to whether the program can effectively analyse data from Yahoo finance to provide a quick overview of the financial market state of companies in the S&P 500 US stock prices.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
