Automated Passive Income from Stock Market Using Machine Learning and Big Data Analytics with Security Aspects

Author:

Sharma Gaurav,Vidalis Stilianos,Mankar Pranjal,Kumar Somesh,Anand Niharika

Abstract

With the evolution of Machine Learning, the Internet of Things (IoT), and Big Data Technologies, digital data has increased exponentially. To handle and process such a large bunch of data, high-performance computers are used across various fields. One of the fields has been the financial capital market of stocks, bonds, commodities, foreign exchange, and cryptocurrencies, where supercomputers essentially trade securities with high computational ability and intelligent algorithms. Large financial institutions with significant capital spend a lot of money on programmers and data analysts to develop the best accuracy trading algorithms to drive the overall market. A novice trader or investor with less to no experience in financial markets feels it difficult to search for good trades or stocks to invest their hard-earned money on a short to long-term time horizon. They rely on expert advice for stock recommendations and sometimes end up making significant losses. This paper focuses on developing a universal trend trading indicator that can analyze and predict the overall future trend of any stock, bond, commodity, forex, or cryptocurrency with the highest possible profitability. The historically traded extensive dataset of stock prices and investment reports of large financial institutions worldwide are gathered. Various machine learning and decision-making models are employed to perform technical and fundamental analysis across multiple securities. The output of the trend trading indicator is displayed on charting platforms, which can provide entry-exit levels at which even novice investors can decide where to invest their money. Multi timeframe analysis is deployed to predict short-term, mediumterm, and long-term overall trends, thus increasing the output accuracy. The indicator is helpful for all kinds of retail traders and investors worldwide who struggle to earn profits from financial markets. Our proposed system was able to achieve a profitability of 86.28% annual returns. The entire system, along with the trading orders, is automated so that anyone can earn extra passive income every month from the stock market.

Publisher

International Consortium of Academic Professionals for Scientific Research

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3