Correlation Between Sercomm Corp and Connection Technology
Can any of the company-specific risk be diversified away by investing in both Sercomm Corp and Connection Technology 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 Connection Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sercomm Corp and Connection Technology Systems, you can compare the effects of market volatilities on Sercomm Corp and Connection Technology 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 Connection Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sercomm Corp and Connection Technology.
Diversification Opportunities for Sercomm Corp and Connection Technology
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Sercomm and Connection is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding Sercomm Corp and Connection Technology Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Connection Technology 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 Connection Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Connection Technology has no effect on the direction of Sercomm Corp i.e., Sercomm Corp and Connection Technology go up and down completely randomly.
Pair Corralation between Sercomm Corp and Connection Technology
Assuming the 90 days trading horizon Sercomm Corp is expected to generate 1.97 times more return on investment than Connection Technology. However, Sercomm Corp is 1.97 times more volatile than Connection Technology Systems. It trades about 0.11 of its potential returns per unit of risk. Connection Technology Systems is currently generating about -0.3 per unit of risk. If you would invest 11,450 in Sercomm Corp on October 9, 2024 and sell it today you would earn a total of 650.00 from holding Sercomm Corp or generate 5.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Sercomm Corp vs. Connection Technology Systems
Performance |
Timeline |
Sercomm Corp |
Connection Technology |
Sercomm Corp and Connection Technology Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sercomm Corp and Connection Technology
The main advantage of trading using opposite Sercomm Corp and Connection Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sercomm Corp position performs unexpectedly, Connection Technology 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 Connection Technology will offset losses from the drop in Connection Technology's long position.Sercomm Corp vs. Arcadyan Technology Corp | Sercomm Corp vs. Wistron NeWeb Corp | Sercomm Corp vs. Accton Technology Corp | Sercomm Corp vs. Alpha Networks |
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Check out your portfolio center.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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