FACTORS AFFECTING ALGORITHM TRADING IN NEPAL

Abstract

The primary objective of this study was to investigate the variables that affect algorithmic trading in Nepal and to examine the correlation between the variables and performance metrics. This study uses a causal and descriptive research strategy to study relationship between variables and discover relationships between them. The quantitative data gathered from respondents through questionnaire distribution served as the foundation for the research findings. All parties involved in the financial markets are included in the population. 109 stakeholders of the Nepalese financial markets were selected as a sample from the overall population. The primary data used in the study were gathered through the use of a structured questionnaire technique. The SPSS software version was used to show and analyze the data that had been gathered. The results indicated a strong correlation between performance metric and the factors influencing algorithmic trading, such as market indicator, algorithmic strategy, market microstructure, economic indicators, technological infrastructure and regulatory environment. Every independent variable had a statistically significant effect on the choice of any individual investor. Additionally, market indicator, algorithmic strategy, market microstructure, economic indicators, technological infrastructure and regulatory environment all had a significant role in forecasting the algorithmic trading performance metric. Keywords: Algo trading, HFT, Online Trading, Automated Trading