Python Script for Profitable Trading Strategy

I would like a script that will analyse the dataset and return  Open_range, Long_trade and Sell_trade profit to an Excel file. First, you need to define variables: Start_time = 17:05 End_time = 18:00 Open_range_high = High (at Start_time)  Open_range_low = Low (at Start_time) Long_trade_stop_loss = Open_range_high Sell_trade_stop_loss = Open_range_low Stop_loss_to_be= Open_range_high or Open_range_low + Open_range Time range: 17:05–18:00 for every day To calculate open_range, use high and low (at 17:05) and return the difference in points. Time High Low Open_range 31/05/2023 17:05 1833 1831.5 Start_time 1.5 The CSV file contains price series at a 5-minute interval. Time-High-Low  Time High Low 31/05/2023 17:05 1833 1831.5 Start_time 31/05/2023 17:10 1832.8 1832.1 31/05/2023 17:15 1832.7 1832 31/05/2023 17:20 1833.1 1832.5 31/05/2023 17:25 1832.9 1832.3 31/05/2023 17:30 1833.1 1832.4 31/05/2023 17:35 1832.7 1832.3 31/05/2023 17:40 1833.3 1832.7 31/05/2023 17:45 1833.3 1832.9 31/05/2023 17:50 1833 1832.5 31/05/2023 17:55 1834.3 1832.8 31/05/2023 18:00 1834.5 1834.1 End_time To calculate Long_trade you need to use High column to return the highest profit for Long_trade  and the low column for a Long_trade_stop_loss Starting with the first row of the "time-frame" (17:05), we need to define verifiables: Open_range_high = 1833 Open_range_low = 1831.5 Long_entry_stop_loss = 1831.5 Open_range = 1.5 Then we move to the next row (17:10) and check whether High in this row is greater than Open_range_high if not, we move to the next row until High is greater than Open_range_high (in many instances, this won't be the case and only Sell_trade occurs). If the High is greater then Open_range_high the calculation would look like this: if High > Open_range_high and Low > Long_trade_stop_loss then we return High minus Open_range_High Next, we move to the next row (17:15), and we repeat the process with a change to the stop loss. If the Long_trade result is greater or equal to Open_range then we use Stop_loss_to_be (Stop_loss_to_be = 1833+1.5 = 1834.5 (Open_range_high + Open_range)) In this case, the calculation would look like this:  if High > Open_range_high and Low > Stop_loss_to_be then we return, High minus Open_range_high, and so on untill the End_time or Low is less then one of the stop loss options. The same holds true for Sell_trade, but alternatively: We need to use Low column to return the highest profit and High column for a Sell_trade_stop_loss Starting with the first row of the "time-frame" (17:05), we need to define verifiables: Open_range_high = 1833 Open_range_low = 1831.5 Sell_entry_stop_loss = 1833 Open_range = 1.5 Then we move to the next row (17:10) and check whether Low in this row is less then Open_range_low if not we move to the next row, until Low is less then Open_range_low (in many instances, this won't be the case and only Long_trade occurs). If the Low is less than Open_range_low the calculation would look like this: if Low < Open_range_low and High  < Sell_entry_stop_loss then we return Open_range_low minus Low (to return a positive value) Next, we move to the next row (17:15), and we repeat the process with a change to the stop loss. If the Sell_trade profit is greater or equal to Open_range then we use Stop_loss_to_be (Stop_loss_to_be = 1831.5-1.5 = 1830 (Open_range_low +-Open_range)) In this case, the calculation would look like this:  If Low < Open_range_low and High < Stop_loss_to_be then we return Open_range_low minus Low, and so on untill the End_time or High is greater than one of the stop_loss options. The purpose of this exercise is to return the highest profit for Long trade and Sell  trade, applying stop loss calculations for every day from the dataset between time- frames. The resoults should look like this: Time Open range Highest value 08/06/2023 6.6 -1.5 09/06/2023 4.1 4.1 09/06/2023 4.1 12.1 12/06/2023 4.2 4.8 12/06/2023 4.2 5.6 13/06/2023 3.7 12.8 Notice that in many instances, there are two outcomes for one date, which are Long_trade and Sell_trade