Correlation Between Sercomm Corp and Dow Jones

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Can any of the company-specific risk be diversified away by investing in both Sercomm Corp and Dow Jones at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Sercomm Corp and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sercomm Corp and Dow Jones Industrial, you can compare the effects of market volatilities on Sercomm Corp and Dow Jones and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Sercomm Corp with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sercomm Corp and Dow Jones.

Diversification Opportunities for Sercomm Corp and Dow Jones

0.3
  Correlation Coefficient

Weak diversification

The 3 months correlation between Sercomm and Dow is 0.3. Overlapping area represents the amount of risk that can be diversified away by holding Sercomm Corp and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Sercomm Corp is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Sercomm Corp are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Sercomm Corp i.e., Sercomm Corp and Dow Jones go up and down completely randomly.
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Pair Corralation between Sercomm Corp and Dow Jones

Assuming the 90 days trading horizon Sercomm Corp is expected to under-perform the Dow Jones. In addition to that, Sercomm Corp is 2.25 times more volatile than Dow Jones Industrial. It trades about -0.04 of its total potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.27 per unit of volatility. If you would invest  4,223,305  in Dow Jones Industrial on August 30, 2024 and sell it today you would earn a total of  248,901  from holding Dow Jones Industrial or generate 5.89% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

Sercomm Corp  vs.  Dow Jones Industrial

 Performance 
       Timeline  

Sercomm Corp and Dow Jones Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Sercomm Corp and Dow Jones

The main advantage of trading using opposite Sercomm Corp and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sercomm Corp position performs unexpectedly, Dow Jones can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Dow Jones will offset losses from the drop in Dow Jones' long position.
The idea behind Sercomm Corp and Dow Jones Industrial pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.

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