Algorithmic and Non-Algorithmic Trading Activity in the BSE Using Limit Order Book of Select Stocks

Title

Algorithmic and Non-Algorithmic Trading Activity in the BSE Using Limit Order Book of Select Stocks

Creator

Acharya, Shubhashree P K

Contributor

P S, Anuradha.

Description

With the existence of a heterogeneous market compounded by asymmetric information, technology has become one of the major newlineenablers in stock market development. Introduction of algorithms for trading gave a fillip to many stock market participants and allowed them to trade rapidly and profitably. In the present day in Indian stock market, newlinewe have two types of market players; algorithmic traders and nonalgorithmic traders. The algorithmic traders are playing a dominant role in order placement, order modification and order execution while the newlinenon-algorithmic traders still continue to use their intuition. This study aims to understand the trading activity of both the market participants. The study uses the Limit Order Book data from Bombay Stock Exchange. newlineThe LOB data of selected nine stocks is considered for the study whose variables namely Order Added, Order Updated and Order Deleted data along with the Bid Ask Quotes are considered for measurement. Based on newlinethe Limit Orders it is observed that there is a statistically significant difference in the trading behavior of algorithmic and non-algorithmic traders based on stock market session timings and market capitalization. newlineThe market making ability of the algorithmic traders was examined using Order-to trade Ratio and it is observed that large number of orders are not executed indicating that there is no significant Market Making happening. newlineThe algorithmic traders possess an edge over the non-algorithmic traders in Order Modification resulting in dominance in the Stock market. The Mann Kendal Trend test indicates upward and downward trend in newlinevolume adjusted spread indicating that market making is happening especially in the stocks where algorithmic activity is high. This study enables regulatory authorities to monitor stock market activity especially during pre- open session. This study provides sufficient scope for further research on future of algorithmic trading activity and its ramifications on non-algorithmic trading activity in the future.

Source

Author's Submission

Date

2022-01-01

Publisher

Christ(Deemed to be University)

Subject

Commerce

Rights

Open Access

Relation

61000249

Format

PDF

Language

English

Type

PhD

Identifier

http://hdl.handle.net/10603/519584