What is 'Algorithm Trading Strategy'?

A Trading Strategy is a combination of various conditions that define when to buy or sell a particular Symbol (Script or Instrument or securities or Future Contracts).

There are mainly 5 steps to Create and Execute an Algorithm Trading Strategy: 



Step 1: Build Algo Trading Strategy: Building Algorithm Strategy in Keev is quite simple process. Algorithmic Trading strategies are based on technical analysis where user needs to define Entry and Exit conditions using time interval (1 min, 5 min, 1 day etc), type of chart, avail 60+ technical indicators and patterns, stop loss % & target profit % and the stocks for which you want to create strategy. For more details refer How to Build an Algorithm Trading Strategy?  


Step 2: Backtest Of Strategy: Backtest used to validate the strategy that how well it performs on historical data. The backtest engine let you backtest your strategies within a few seconds and cover multiple instruments. For more details refer How do Backtesting works?


Step 3: Optimization of Strategy: The optimization engine is used to improve the accuracy of your strategies to fine tune your parameters such as Stop loss % and Take Profit %. For more details refer How to optimizes your strategy?


Step 4: Virtual Trade of Strategy:  Virtual trading allows users to place hypothetical trades based on real-time stock market prices. This is most helpful if you want to test your strategy in live market without any erosion of their capital. After analyzing the performance of the strategy by virtue of Virtual trade one can then deploy the said strategy in the live market if one finds the results of Virtual Trade satisfactory. For more details refer How to test your strategy in Virtual Trade environment


Step 5: Deployment of Strategy in Live Market: The live trade engine executes and monitor your trading strategies automatically over multiple instruments and multiple strategies in the live stock market.  


Algorithm is a computer program that matches various conditions and accordingly sends buy and sell orders to exchanges.

Users usually combine technical indicators (EMA, SMA, RSI, etc.) used along with comparison (Greater than, Lesser than, Equal to, etc.) and logical (AND, OR) operators  

Below is an example of a simple Algo that a user can create

  • Buy when the EMA(9) Crossover EMA (14) 

  • Sell when the EMA (14) Cross Under EMA(9) 

You can build the above strategy on KEEV Canvas and will look like

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