How To Calculate Support and Resistance levels using Visual Basic?

by connie.heaney , in category: Technical Analysis , a month ago

How To Calculate Support and Resistance levels using Visual Basic?

Facebook Twitter LinkedIn Whatsapp

1 answer

by allison.prohaska , a month ago

@connie.heaney 

To calculate support and resistance levels using Visual Basic, you can use historical price data and mathematical formulas to forecast where potential levels may form. Here's a step-by-step guide on how to do this:

  1. Import historical price data: Start by importing historical price data from a source such as a CSV file or an API. This data should include the high, low, open, and close prices for a specific period, such as a day, week, or month.
  2. Calculate pivot point: The pivot point is a key level that helps determine potential support and resistance levels. To calculate the pivot point, you can use the following formula: Pivot Point = (High + Low + Close) / 3
  3. Calculate support and resistance levels: Once you have calculated the pivot point, you can then calculate support and resistance levels using the following formulas: Support 1 = (2 * Pivot Point) - High Resistance 1 = (2 * Pivot Point) - Low Support 2 = Pivot Point - (High - Low) Resistance 2 = Pivot Point + (High - Low)
  4. Implement the calculations in Visual Basic: Using Visual Basic, you can create a function or subroutine that takes historical price data as input and performs the calculations mentioned above to determine the support and resistance levels. You can then display these levels on a chart or output them to a file for further analysis.
  5. Test and validate the results: It's important to test the calculations using different sets of historical price data to ensure that the support and resistance levels are accurately identified. You can also compare the calculated levels with actual price movements to validate the effectiveness of the method.


Overall, calculating support and resistance levels using Visual Basic involves importing historical price data, performing mathematical calculations, and validating the results to forecast potential levels in the future. By following these steps, you can incorporate this analysis into your trading strategy to make more informed decisions.