Title: Recommendation Engine for Stock Market Trading
Abstract: Investment management is a business problem that is applicable to individuals as well as businesses. Stock market trading can be daunting without the right strategy and tools. Decision making in the stock market is complex as it requires at least some basic understanding of economics, statistics and behavioral science. Due to this, traders face inertia and friction. Automation of the selection of stocks to be considered for trading is an application of computational intelligence, aimed at better discovery of opportunities for buying and selling in a stock market. The automatic selection process to pick stocks from the broad market is something which every trader would desire. In this chapter, a basic stock picking model based on technical analysis strategies is presented. This recommendation engine is proposed with an aim to shift the way one trades by removing some of the biases inherent in the manual process. By employing a few basic technical analysis strategies, the proposed model helps investors discover scrips without performing a detailed study. The resulting baseline list of stocks become choices from which traders can evaluate and determine the actual trades to make. The proposed recommendation engine yields encouraging results, and is practical and easy to implement.
Publication Year: 2021
Publication Date: 2021-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 1
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