Is R Good For Designing Quant Trading Strategies?

r trading strategies

This article is to discuss on the efficiency of the tool R in designing and back testing the trading strategies. But before getting in to the concepts of designing and back testing using R, we will have a simple introduction for this tool. What is R? R is nothing but the open source that has about 18,000 members in the Linkedln’s groups and 80 R meet up groups are there in existence now. This open source provides about 4000 packages for an efficient designing of strategies. This is a tool that perfectly matches the needs of data analysis, which is a must in strategy designing.

What are the steps involved in trading strategy designing?

The ‘Comprehensive R Archive Network’, also known to the world as CRAN will be providing you with the ‘add on packages’ and also the base installation of R. Also there are several packages available and they can be availed from the CRAN based on the requirements. For the implementation of trading strategy, the Quant package will be used. There are four steps involved in the process of designing a trading strategy.

  • Hypothesis formation
  • Testing
  • Refining
  • Production

The hypothesis of R is prepared as the “market is mean reverting”. The theory of mean reversion suggests the prices will eventually be moving back to their own average values. The next step is nothing but the hypothesis will be tested, for which we are going to formulate the strategy and compute the signals, performance metrics and also indicators. Now further the testing phase will be divided into three steps.

  • Getting data
  • Writing strategy
  • Analyzing output

Refining is a step in which the changes for the strategy will be made based on the results of the testing phase and at last comes the production phase where the live market environment will be faced.

Coding section of R

It is important in a data analysis to check out for the fluctuations in stock prices. The R will be updating the user with the threshold column, whenever there is a change in the price. Whether the price decreases or increases, the R will update the user with the threshold column. Also the closing price will be compared with lower band price and upper band price. Whenever the upper price band is touched, then the R will be sending a sell signal to the user. Also it will repeat the same when the lower price band is touched.

The coding section of the R can be summarized as follows.

  • Adding the indicators
  • Adding the signals
  • Adding the rules

By taking the volatility as a major factor, using the Bayseian approach and choosing more data for the back testing, an efficient strategy can be made. Once the designer is satisfied with the performance of the strategy in the back testing, the strategy can get in to the production phase which is all about the live market environment. The live trading involves so much in it, which cannot be discussed in a single article at all. To learn more on this, choosing a r trading strategies and a right automated trading programs will be a better option. please follow us at


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