TeslaEducation
Beta is not right indicator to pick high volatile stocks
I have done extensive analysis on lot of stocks to see, which group of stocks gives more returns compared to market, index or any other household branded companies.
Before i get into alternative to beta, here i will try to get into the details of beta calculation to understand ourselves why beta may not represent true nature or momentum of a stock.
How is beta calculated?
Beta is multiplication of two numbers, Correlation and volatility. If any one number out of these two are less, the result will be a low beta number.
Correlation: If a stock moves in same +ve or -ve direction as that of market, it will have good correlation. On a given window of 48 prior days from now, how many days(or whatever timeframe) the stock matches up/down movement with respect to market, will give us correlation number. This value will be in the range +1 to -1. If price moves as per market direction, it will be 0 to +1. If price moves in opposite direction of market( that is stock goes up when market goes down or stock goes down when market goes up), the correlation will be 0 to -1.
Usually in practice, all stocks are mostly positively correlate with market, so they end up having values between 0 and +1. This means, stocks with close to +1 correlation will have high beta and low correlation( say 0.5) will result in low beta.
So correlation will play big role in beta value of a stock.
However there will be few stocks, which doesn't move exactly as that of market but still are high volatile. I will explain volatility in short. If one is filtering stocks based on beta, they will loose out gains on these high volatile stocks.
Instead of measuring an expected amount of return on a stock with respect to beta, we could simply use volatility to monitor a list of high volatile stocks to reap good returns over time.
Volatility: If market moves +0.5%, say stock x moves 1%, conversely if market moves -0.5%, stock x moves -1%, it is safe to say stock x is high volatile. In statistics/math terms, how much the stock is deviating from its mean compared to market, gives a relative value of volatility with respect to market. Standard deviation of stock versus market gives the volatility of the stock.
Higher the volatility, higher the gains or losses on the stock. Expecting returns on a stock based on the standard deviation is difficult. Instead, I will simply use a different calculation(explained below), that helps you easily see the expected returns in layman terms.
Say, if you buy a stock at the lowest price on a specific month, and sell at highest price in that same month, the profit can be measured in percentage wise. That same number averaged over 12 months gives a rough idea of how much profit one can expect if timed properly every month.
Selecting and timing on these high percentage profit returning stocks will amplify the returns over long time, compared to investing or trading in the low volatile stocks.
The indicator(free) of mine sangana beta table will list the stocks sector wise, how much percentage a stock moves low to high in a month.
It works for S&P500 and Nifty 500 stocks.
Happy trading !!!
Before i get into alternative to beta, here i will try to get into the details of beta calculation to understand ourselves why beta may not represent true nature or momentum of a stock.
How is beta calculated?
Beta is multiplication of two numbers, Correlation and volatility. If any one number out of these two are less, the result will be a low beta number.
Correlation: If a stock moves in same +ve or -ve direction as that of market, it will have good correlation. On a given window of 48 prior days from now, how many days(or whatever timeframe) the stock matches up/down movement with respect to market, will give us correlation number. This value will be in the range +1 to -1. If price moves as per market direction, it will be 0 to +1. If price moves in opposite direction of market( that is stock goes up when market goes down or stock goes down when market goes up), the correlation will be 0 to -1.
Usually in practice, all stocks are mostly positively correlate with market, so they end up having values between 0 and +1. This means, stocks with close to +1 correlation will have high beta and low correlation( say 0.5) will result in low beta.
So correlation will play big role in beta value of a stock.
However there will be few stocks, which doesn't move exactly as that of market but still are high volatile. I will explain volatility in short. If one is filtering stocks based on beta, they will loose out gains on these high volatile stocks.
Instead of measuring an expected amount of return on a stock with respect to beta, we could simply use volatility to monitor a list of high volatile stocks to reap good returns over time.
Volatility: If market moves +0.5%, say stock x moves 1%, conversely if market moves -0.5%, stock x moves -1%, it is safe to say stock x is high volatile. In statistics/math terms, how much the stock is deviating from its mean compared to market, gives a relative value of volatility with respect to market. Standard deviation of stock versus market gives the volatility of the stock.
Higher the volatility, higher the gains or losses on the stock. Expecting returns on a stock based on the standard deviation is difficult. Instead, I will simply use a different calculation(explained below), that helps you easily see the expected returns in layman terms.
Say, if you buy a stock at the lowest price on a specific month, and sell at highest price in that same month, the profit can be measured in percentage wise. That same number averaged over 12 months gives a rough idea of how much profit one can expect if timed properly every month.
Selecting and timing on these high percentage profit returning stocks will amplify the returns over long time, compared to investing or trading in the low volatile stocks.
The indicator(free) of mine sangana beta table will list the stocks sector wise, how much percentage a stock moves low to high in a month.
It works for S&P500 and Nifty 500 stocks.
Happy trading !!!
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