The Development of Algorithmic trading in turbulent markets

The main purpose of this study is to develop an algorithm trading in turbulent markets. we define turbulent days as days when the absolute values of market returns are greater than 2%. For this purpose, a sample of 276 companies listed on the Tehran Stock Exchange during 2019 has been studied using multivariate regression and logistics. The results showed that in the bullish days of the market, stocks that demand more algorithmic trades have lower abnormal stock returns and have lower price fluctuations. The results for the downtrends showed that the stocks that are traded mostly by algorithmic trading show more downside fluctuations in the downtrends. The results also showed that accounting news and information influence the decisions of algorithmic traders in turbulent days and lead to fewer stock price fluctuations. The intensity of algorithmic transactions about price fluctuations in companies that publish price-sensitive news and information is higher than other companies. In general, the results showed that, compared to non-algorithmic trading, algorithmic trading does not cause price fluctuations between stocks in turbulent markets.