Standard deviation 1
Support = 22194.05
Resistance = 22508.20
Standard deviation 2
Support = 22039.50
Resistance = 22666.25
Normal Distribution and Stock Prices:
The underlying assumption when using standard deviation to measure risk in the stock market is that the majority of price activity follows the pattern of a normal distribution (also known as a Gaussian distribution).
In a normal distribution:
Approximately 68% of individual stock price values fall within one standard deviation of the mean (above or below).
About 95% of stock prices lie within two standard deviations from the mean.
Nearly 99.7% of stock prices are within three standard deviations from the mean123.
This distribution model helps us understand the typical behavior of stock prices and assess their relative risk.
Standard Deviation and Volatility:
Standard deviation measures the volatility or spread of asset prices from their average price.
High standard deviation indicates high volatility, meaning prices swing significantly.
Low standard deviation implies calm prices, with less wild price fluctuations.
Investors use standard deviation to assess the risk associated with an investment.
When stock prices exhibit wild swings, the standard deviation is high, indicating higher risk.
Conversely, when stock prices remain stable, the standard deviation is low, suggesting lower risk.
Calculating Standard Deviation:
Standard deviation is calculated by:
Subtracting the mean from each value.
Squaring the differences.
Averaging the squared differences to produce the variance.
Variance is then converted to standard deviation by taking its square root.
Standard deviation brings the measurement back to the original unit (e.g., dollars for stock prices).
In summary, understanding standard deviation helps investors gauge the risk associated with different stocks. It provides insights into how much stock prices typically deviate from their average, allowing informed decision-making in the dynamic world of stock markets.
#stockmarket
#stockmarkets
#thestockmarket
#stockmarketnews
#stocks
#stockmarkettips
#stockmarketinvesting
#stockstobuy
Support = 22194.05
Resistance = 22508.20
Standard deviation 2
Support = 22039.50
Resistance = 22666.25
Normal Distribution and Stock Prices:
The underlying assumption when using standard deviation to measure risk in the stock market is that the majority of price activity follows the pattern of a normal distribution (also known as a Gaussian distribution).
In a normal distribution:
Approximately 68% of individual stock price values fall within one standard deviation of the mean (above or below).
About 95% of stock prices lie within two standard deviations from the mean.
Nearly 99.7% of stock prices are within three standard deviations from the mean123.
This distribution model helps us understand the typical behavior of stock prices and assess their relative risk.
Standard Deviation and Volatility:
Standard deviation measures the volatility or spread of asset prices from their average price.
High standard deviation indicates high volatility, meaning prices swing significantly.
Low standard deviation implies calm prices, with less wild price fluctuations.
Investors use standard deviation to assess the risk associated with an investment.
When stock prices exhibit wild swings, the standard deviation is high, indicating higher risk.
Conversely, when stock prices remain stable, the standard deviation is low, suggesting lower risk.
Calculating Standard Deviation:
Standard deviation is calculated by:
Subtracting the mean from each value.
Squaring the differences.
Averaging the squared differences to produce the variance.
Variance is then converted to standard deviation by taking its square root.
Standard deviation brings the measurement back to the original unit (e.g., dollars for stock prices).
In summary, understanding standard deviation helps investors gauge the risk associated with different stocks. It provides insights into how much stock prices typically deviate from their average, allowing informed decision-making in the dynamic world of stock markets.
#stockmarket
#stockmarkets
#thestockmarket
#stockmarketnews
#stocks
#stockmarkettips
#stockmarketinvesting
#stockstobuy