"Preferences in Algorithmic Trading: Current Practices and Future Innovations"

Abstract

Introduction
Algorithmic trading is a process that involves executing a large number of orders using electronically automated and pre-programmed trading instructions. These instructions account for various factors such as price, timing, and volume. The study aims to explore the impact and preferences for algorithmic trading among investors.

Objectives
To understand the operational processes and mechanics of algorithmic trading.
To assess the reasons for the preference for algorithmic trading among investors.
To analyse the impact of demographic variables on the frequency of trading and awareness of algorithmic trading.

Research Methodology
The research utilized a descriptive research design. Data collection was conducted through questionnaires and interviews. A non-probability sampling method was employed, and responses were gathered from 124 participants in Ahmedabad.

Findings
Algorithmic trading allows investors to use predefined strategies or create their own, which is a key factor in its preference.
The study found that algorithmic trading is preferred due to its reduced human error and perceived safety.
It was revealed that 55% of individuals are aware of algorithmic trading.
Demographic variables were found to have a 34% impact on the frequency of trades conducted using algorithmic trading and a 29.2% impact on the awareness of algorithmic trading.
The research indicates that investors are likely to prefer algorithmic trading in the future due to its safety, security, and the availability of various trading strategies.