Order Splitting Strategy to Reduce Market Impact in Tehran Stock Exchange

Abstract

Objective: This research is aimed at offering an order splitting strategy to divide a large order into a number of smaller orders to reduce Market Impact cost and imbalances created by Large orders in the market. Methods: Due to the limited access to data and high volume of calculations, for some shares of the Tehran Stock Exchange (TSE), market impact cost function of bought trades were calculated using the I-star model. Then, by using the MI function and based on the investor's trading horizon, we split a large order into a series of small orders to place them at intervals rather than ordering all at once. The goal is to reduce the market impact cost, and avoid creating an imbalance of large orders in the market. Results: According to the intraday patterns of the average trading volumes and the market impact cost, it is observed that the trading volume of shares is low and market impacts cost are high at the beginning of the day, then at the end of the day, as the trading volume and market liquidity increase, the market impact cost incurred by traders reduces. This is mainly because investors will not need to increase trading prices to complete their orders when the stock market experiences an increase in liquidity and trading volumes, and this is also seen in the Tehran Stock Exchange. The market impact cost function for the shares in Tehran Stock Exchange is also concave and investors behave much more aggressively when buying compared to selling. Conclusion: The results show that by examining the intraday patterns of liquidity parameters such as trading volumes and market impact then designing a trading strategy for the splitting of large orders can reduce the additional costs incurred by traders and result in orders being traded in relatively more reasonable prices.

Keywords

• large order splitting strategy
• intraday patterns
• algorithmic trading
• market impact
• transaction costs