Back testing script for stock trading strategy

Please include a brief description with your bid explaining strategy, experience etc. A few sentences will do. Such as, if you'd choose R or Python, and if you have any relevant experience in this area such as statistics work. Thank you, and looking forward to working together. Introduction: I need a script to back test stock data so that I can refine a trading strategy. The script can be made in either Python, R, or Matlab. Python would be my first choice, but I recognize that R or Matlab may be better suited for this project. The strategy is based on 4 variables which are each calculated using standard OHLC data (Open, High, Low, Close and Volume). The script will need to back test and calculate the results of the trading strategy using all combinations of the variables in the trading strategy. And, output the results. I will need to be able to reuse the script on other CSV data files in the future to be able to test the overall strategy with historical data from multiple different stocks. Primary Challenge: Each of the 4 variables can be calculated using different “thresholds”. For example, 20-day moving average, versus a 15-day moving average, versus a 10-day moving average. Consequently, the main purpose of the script is to test the trading strategy in each possible scenario and output the results of each (profit vs loss, maximum drawdown, etc). This way, I can deduce what the best possible combination of variables, and their respective calculations, to use in the actual trading strategy that I will eventually implement. There’s a bit more to the calculation of each of these variables then just what type of moving average to use, but I use this as a simple example to explain that each variable has ways that each can be slightly “adjusted” and therefore the purpose of the script is to enable me to refine the final trading strategy. As an FYI - the first two variables have 10 possible ways of being calculated, and the third and fourth each having 6 possible ways of being calculated. Consequently, there’s 3600 possible scenarios (10 x 10 x 6 x 6) to back test and the script will need to undertake each so its possible to see the profitably under each scenario. Output: The script will need to be able to output the following variables for the 10 most profitable scenarios: 1) Win probability - The probability that any given trade will return a positive amount (a number between 0 and 1) 2) Win / Loss Ratio - dividing the average gain of the positive trades by the average loss of the negative trades. 3) Average gain for winning trades 4) Average loss for losing trades 5) Average outcome for all trades 6) Maximum Drawdown 7) Biggest win 8) Calmar Ratio – calculated by taking CAGR divided by the absolute value of the Maximum Drawdown Thank you and looking forward to working together.