Some of the trading strategies that we develop are based on recognition of technical chart patterns wherein the chart patterns provide the basic trading set-ups and various statistical, mathematical and physics based indicators provide confirmation of price trends. The objective of this form of strategy development is to capture short term price trends in the market with lowest possible latency
We achieved the next level of automation when after developing strategies using “logic engines” we successfully deployed “Portfolio Builder” for performing risk analytics over huge number of strategies and used them in finalizing a subset of strategies based on the user input. Portfolios created by the Portfolio Builder show better risk-return profile when compared to the entire basket and consequently are activated for live trading.
By leveraging our automated strategy and portfolio development process, we have been able to hugely ramp up the pace of algorithmic strategy development and currently we have developed and deployed thousands of algorithmic strategies that help us in trading the top 100 stock futures (based on intraday trading volume), Index futures (like Nifty and Banknifty), commodity futures (Precious metals, power and base metals) and also USD-INR exchange rate futures.
We have also developed proprietary software utilities for Performance & Risk analysis of our portfolios both on historical datasets as well as on live data. These tools act on the basis of inputs and the algorithms developed by the analyst. We perform a large number of trading simulations to understand the fund level risk for different levels of standing exposures.
Our present style of trading multiple portfolios spanning hundreds of stock futures necessitates efficient execution of thousands of trades on any given day. Also, Due to short term trading, impact cost has a very high influence on our trading.
In view of the above we have developed our own automated trading (Execution) platform. This platform enables us to understand the net tradable position for each security after aggregating the exposure of that security across different products and different portfolios on real time basis. This is followed by a rapid analysis of the current market scenario and leads to suitable adjustment in the various input values associated with a highly tested complex execution algorithm. This finally decides how the aggregate traded exposure needs to be broken up and in what manner the order needs to be spread over multiple bid or ask values for each of the securities.
With the help of a series of sophisticated software programs we are controlling the entire Strategy Development,Execution and Evaluation Lifecycle and thereby protecting the “Asset Under Management” from suboptimal discretionary interference.