Let\u2019s understand how to calculate and graph the RSI indicator. While you can easily calculate the RSI indicator value with the Python code, for explanation purposes we will do it manually.<\/p>\n\n\n\n Step 1: Closing Price<\/strong><\/p>\n\n\n\n We will take the closing price of the stock for 30 days. The closing price is mentioned in column (1).<\/p>\n\n\n\n Step 2: Changes in Closing Price<\/strong><\/p>\n\n\n\n We then compare the closing price of the current day with the previous day\u2019s closing price and note them down. Thus, from the table, for 25-04, we get the change in price as (280.69 \u2013 283.46) = -2.77.<\/p>\n\n\n\n Similarly, for 26-04, Change in price = (Current closing price \u2013 Previous closing price) = (285.48 \u2013 280.6) = 4.79. We will then tabulate the results in the column mentioned as \u201cChange (2)\u201d. In this manner, we calculated the change in price.<\/p>\n\n\n\n Step 3: Gain and Loss<\/strong><\/p>\n\n\n\n We will now create two sections depending on whether the price increased or decreased, with respect to the previous day\u2019s closing price.<\/p>\n\n\n\n If the price has increased, we note down the difference in the \u201cGain\u201d column, and if it\u2019s a loss, then we note it down in the \u201cLoss\u201d column.<\/p>\n\n\n\n For example, on 26-04, the price had increased by 4.79. Thus, this value would be noted in the \u201cGain\u201d column.<\/p>\n\n\n\n If you look at the data for 25-04, there was a decrease in the price by 2.77. Now, while the value is written as negative in the \u201cchange\u201d column, we do not mention the negative sign in the \u201cLoss\u201d column. And only write it as 2.77. In this manner, the table for the columns \u201cGain (3)\u201d and \u201cLoss (4)\u201d is updated.<\/p>\n\n\n\n In the next article, Rekhit will discuss Average Gain and Loss<\/em><\/p>\n","protected":false},"excerpt":{"rendered":" The Relative Strength Index (RSI) indicator, as the name suggests, tells us the relative strength of the asset. RSI is counted as a robust technical indicator.<\/p>\n","protected":false},"author":91,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,349,338,350,341,344],"tags":[595,445],"contributors-categories":[13654],"class_list":{"0":"post-3576","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-data-science","7":"category-python-development","8":"category-ibkr-quant-news","9":"category-quant-asia-pacific","10":"category-quant-development","11":"category-quant-regions","12":"tag-python","13":"tag-rsi","14":"contributors-categories-quantinsti"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"\n![\"\"](\"\/campus\/wp-content\/uploads\/sites\/2\/2023\/03\/RSI-Indicator-1.png\")
<\/figure>\n\n\n\n