Evidence of algorithmic trading from Indian equity market: Interpreting the transaction velocity element of financialization

Dubey, Ritesh Kumar; Chauhan, Yogesh K.; Syamala, Sudhakara Reddy

doi:10.1016/j.ribaf.2017.05.014

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…While high-frequency trading (HFT), a subset of AT, reduced spreads and increased volume, it also heightened volatility and reduced depth. Similar mixed findings emerged in Dubey et al (2020) and Aggarwal and Thomas (2017), highlighting the need for context-specific analyses.…”

Section: 2supporting

confidence: 52%

Algorithmic Trading And Market Liquidity Dynamics In Indian Energy Futures: A Comprehensive Analysis"

Jain,

Bagrecha

2024

eatp

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Section: 2supporting

confidence: 52%

Algorithmic Trading And Market Liquidity Dynamics In Indian Energy Futures: A Comprehensive Analysis"

Jain,

Bagrecha

2024

eatp

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“…Companies using high-frequency systems trade hundreds or thousands of times a day for their own account, where holding periods are measured in minutes or seconds. A recent research conducted by Indian authors (Dubey, Chauhan, & Syamala, 2017) confirms that in the first five years of the automated trading system implementation in 2009, due to the high speed of transfer, the volume of trading in financial markets increased by 60%.…”

Section: Empirical Evidence Related To Automated Trading Systemsmentioning

confidence: 89%

“…The application of automated trading systems to an increasing number of markets is owed to some of their key features. The speed of order execution as one of main features has been increasing significantly from year to year (Jones, 2013;Carrion, 2013;Dubey, Chauhan, & Syamala, 2017). In addition to this, the key advantage is considered to be real-time decision making, along with the observation of a large number of parameters.…”

Section: Empirical Evidence Related To Automated Trading Systemsmentioning

confidence: 99%

The Impact of Automated Trading Systems on Financial Market Stability

2019

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The way in which financial markets operate has substantially been changed by the development of information technology. Automation of trading systems in financial markets represents the last phase of depersonalizing activities previously done by traders. Algorithmic trading development enabled computers to determine the moment and the way of executing sales orders. Computers still do not make autonomous decisions regarding the choice of instruments to be traded or trading criteria. They implement the strategy a trader has decided on, choosing a favorable moment. This reduces the impact of human emotions on decision making and enables overcoming possible problems which arise due to neglecting or lack of concentration. High-frequency trading enables the execution of algorithmic operations at a high speed. The main goal of the paper is to determine advantages and dangers produced by algorithmic stock trading.

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“…Lower transactional expenses [13] with automated tests running simultaneously on various market situations. To determine whether algorithmic trading is a feasible trading method, available historical and real-time data can be used for back testing with less possibility of human error when placing trades [14]. It decreases the likelihood that human traders would make errors based on emotional and psychological reasons.…”

Section: Introductionmentioning

confidence: 99%

Algorithm trading and its application in stock broking services

Vedapradha¹,

Hariharan

Praveenraj

et al. 2023

E3S Web of Conf.

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Purpose: Algorithmic trading provides a more systematic approach to active trading than methods based on trader intuition or instinct. The aim of the study is to examine the level of awareness among the brokers when integrated with technology for the purpose of executing the trades. Design/Methodology: A self-administered and structured 350 questionnaires were designed and circulated to collect the preliminary information from the stock brokers operating in NSE and BSE within the geographical limits of Bangalore district using the Systematic Sampling method to obtain a sample size of 235. Awareness, Automated trading, Elimination of human error, portfolio management, tracking order, order placement were the critical variables observed to validate the hypothesis using Simple Percentage Analysis & Chi-Square Analysis using Statistical Analysis Software (SAS). Findings: It was found that there is robust association between the level of awareness of the mentioned technology in its application by the stock brokers of NSE and BSE operating in Bangalore. Portfolio management and automated trading are the highly associated application of Algorithmic trading among the stock brokerage services. Originality: Algorithmic trading makes use of complex formulas, combined with mathematical models and human oversight, to make decisions to buy or sell financial securities on an exchange. It can be used in a wide variety of situations including order execution, arbitrage, and trend trading strategies. Algorithmic traders often make use of high-frequency trading technology, which can enable a firm to make tens of thousands of trades per second.

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Evidence of algorithmic trading from Indian equity market: Interpreting the transaction velocity element of financialization

Cited by 11 publications

References 14 publications

Algorithmic Trading And Market Liquidity Dynamics In Indian Energy Futures: A Comprehensive Analysis"

Algorithmic Trading And Market Liquidity Dynamics In Indian Energy Futures: A Comprehensive Analysis"

The Impact of Automated Trading Systems on Financial Market Stability

Algorithm trading and its application in stock broking services

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