Calculating Connor’s RSI (CRSI): A Step-by-Step Guide

The Connor’s RSI (Relative Strength Index) is a popular momentum indicator used in technical analysis to measure the strength of an asset’s price movement. In this article, we will explore how to correctly calculate the Connor’s RSI (CRSI).

What are Connor’s RSI and the Relative Strength Index?

• The Connor’s RSI measures the speed and change in price movement over a given period.

• The Relative Strength Index is a momentum indicator that compares a security’s price movement to its volatility.

How ​​to Calculate Connor’s RSI (CRSI)

To calculate the Connor’s RSI, you need to follow these steps:

• Define a Time Frame: Select a time frame to analyze your data. The most common time frames are 14 days and 50 days.

• Calculate a Simple Moving Average (SMA): Calculate the SMA by adding up all of the asset’s closing prices for the specified period. You can use any type of SMA, but the 9-period simple moving average is a popular choice.

• Calculate the Relative Strength Index (RSI):

• Add the previous SMA value to itself (i.e. RSI = SMA + SMA).

• Divide the result by the previous SMA value (i.e. RSI = (SMA + SMA) / SMA).

• Apply Connor’s RSI formula:

+ Multiply the RSI by 100.

+ If the RSI falls below 30, it means the asset is oversold and you should be cautious.

Here is an example of Python code to illustrate these steps:

import pandas as pd


def get_streaks_rsi(prices, window=14):

    
Calculate the SMA (Simple Moving Average)

    sma = prices.rolling(window).mean()

    

    
Calculate the Relative Strength Index (RSI)

    rsi = (prices - sma) / sma

    

    
Apply Connor's RSI formula

    cross = rsi * 100

    back cross



Usage example:

prices = pd.DataFrame({'Close': [10, 12, 15, 18, 20]})


cros_rsi = get_streaks_rsi(prices)

print (cros_rsi)

What causes inaccurate RSI results on Connor?

Incorrect results can occur for several reasons:

• Data quality issues: If your data contains gaps or is missing values, may not be representative of the entire market.

• Bars

  : The above example uses a moving SMA, which is only effective if there are no gaps in the data. If there are gaps, you can use a moving average to avoid this problem.

• Oversimplification: Connor’s RSI assumes that all price changes are equally significant. This may not be true for all markets or asset classes.

Conclusion

To correctly calculate Connor’s RSI (CRSI), check the following:

• Choose the right timeframe and use the appropriate SMA

• Apply the formula carefully, taking into account any data quality issues or series

• Avoid oversimplification by taking into account other market factors

By following these steps, you can ensure accurate calculations for Connor’s RSI (CRSI) and gain valuable information for your investment decisions.

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