Correlation Between SCI Information and Sangsin Energy
Can any of the company-specific risk be diversified away by investing in both SCI Information and Sangsin Energy 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 SCI Information and Sangsin Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SCI Information Service and Sangsin Energy Display, you can compare the effects of market volatilities on SCI Information and Sangsin Energy 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 SCI Information with a short position of Sangsin Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of SCI Information and Sangsin Energy.
Diversification Opportunities for SCI Information and Sangsin Energy
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between SCI and Sangsin is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding SCI Information Service and Sangsin Energy Display in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sangsin Energy Display and SCI Information 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 SCI Information Service are associated (or correlated) with Sangsin Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sangsin Energy Display has no effect on the direction of SCI Information i.e., SCI Information and Sangsin Energy go up and down completely randomly.
Pair Corralation between SCI Information and Sangsin Energy
Assuming the 90 days trading horizon SCI Information Service is expected to generate 0.84 times more return on investment than Sangsin Energy. However, SCI Information Service is 1.18 times less risky than Sangsin Energy. It trades about -0.02 of its potential returns per unit of risk. Sangsin Energy Display is currently generating about -0.03 per unit of risk. If you would invest 371,262 in SCI Information Service on September 26, 2024 and sell it today you would lose (140,262) from holding SCI Information Service or give up 37.78% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
SCI Information Service vs. Sangsin Energy Display
Performance |
Timeline |
SCI Information Service |
Sangsin Energy Display |
SCI Information and Sangsin Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SCI Information and Sangsin Energy
The main advantage of trading using opposite SCI Information and Sangsin Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SCI Information position performs unexpectedly, Sangsin Energy 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 Sangsin Energy will offset losses from the drop in Sangsin Energy's long position.SCI Information vs. KB Financial Group | SCI Information vs. Shinhan Financial Group | SCI Information vs. Hyundai Motor | SCI Information vs. Hyundai Motor Co |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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