Stock Market Analysis: Algorithmic Trading Web Application

Stock Market Analysis: Algorithmic Trading Web Application

Tripti Sharma, Rati Goyal, Ayushi Chopra, Samriti Chopra

Department of Computer science and Engineering (Data-Science),

Inderprastha Engineering college Ghaziabad, UttarPradesh ,India

Abstract. Purpose: Algorithmic trading offers a more structured approach to active trading compared to techniques that rely on a trader's intuition or instincts. This study aims to assess the extent of awareness among brokers when they incorporate technology into their trading practices.

Design/Methodology: A series of 350 self-administered questions with a structured format was created and sent to stock brokers who work on the NSE and BSE in the Bangalore district. The Systematic Sampling approach yielded a sample size of 235. To verify the theory, important factors like awareness, automated trading, removing human error, portfolio management, order tracking, and order placement were examined. With the aid of Statistical study Software, the study was carried out utilising Chi-Square and Simple Percentage Analysis (SAS).

Findings: The degree of understanding of the aforementioned technology in its application by the stock brokers of the NSE and BSE operating in Bangalore was shown to have a strong correlation. Among stock brokerage services, automated trading and portfolio management are two closely related uses of algorithmic trading.

Originality: Algorithmic trading uses intricate formulae, mathematical models, and human intervention to determine whether to purchase or sell financial securities on an exchange. It can be applied to many different scenarios, such as trend trading methods, arbitrage, and order execution. High-frequency trading technology, which allows a company to execute tens of thousands of deals per second, is frequently utilised by algorithmic traders.