Develope a quantittive model of the intra-day volume curve for the Indian market equity instruments: Edelweiss

Abstract

Algorithmic trading involves using advanced mathematical models for making transaction decisions, i.e. deciding timing, price or quantity of an order. In many cases the trading platform is used because it provides the flexibility of trading without human intervention. Most commonly it is used by large institutional investors because of the large amount of shares that they transact every day. These trading algorithms allow them to deploy different strategies during trading so that objectives like least market impact, average price, best price, etc. could be achieved. Volume – weighted average price (VWAP) aims to sell/buy the shares at the average price observed during the trade duration. It is the sum of every transaction price paid weighted by its volume. Because of its intuitive nature it is the most commonly used benchmark for assessing the performance of various algorithms. The algorithm aims to complete the transaction by selling a portion of the total trade volume at regular intervals and thus achieving the average market price. This reduces the market impact of the trade as well. However, the person using VWAP takes on a risk in time. Any price movement against the position will impact the trade. VWAP execution orders represent around 50% of the institutional trades and VWAP trading is a common trading strategy provided by most broking houses to their clients. The objective of the summer internship was to develop a quantitative model of the intra-day volume curve for the Indian market equity instruments. This model is one of the input models used for generating a VWAP transaction algorithm.