Correlation Between Song Shang and Tainet Communication
Can any of the company-specific risk be diversified away by investing in both Song Shang and Tainet Communication 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 Song Shang and Tainet Communication into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Song Shang Electronics and Tainet Communication System, you can compare the effects of market volatilities on Song Shang and Tainet Communication 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 Song Shang with a short position of Tainet Communication. Check out your portfolio center. Please also check ongoing floating volatility patterns of Song Shang and Tainet Communication.
Diversification Opportunities for Song Shang and Tainet Communication
0.47 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Song and Tainet is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding Song Shang Electronics and Tainet Communication System in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tainet Communication and Song Shang 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 Song Shang Electronics are associated (or correlated) with Tainet Communication. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tainet Communication has no effect on the direction of Song Shang i.e., Song Shang and Tainet Communication go up and down completely randomly.
Pair Corralation between Song Shang and Tainet Communication
Assuming the 90 days trading horizon Song Shang Electronics is expected to generate 1.9 times more return on investment than Tainet Communication. However, Song Shang is 1.9 times more volatile than Tainet Communication System. It trades about -0.01 of its potential returns per unit of risk. Tainet Communication System is currently generating about -0.08 per unit of risk. If you would invest 2,900 in Song Shang Electronics on September 17, 2024 and sell it today you would lose (215.00) from holding Song Shang Electronics or give up 7.41% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Song Shang Electronics vs. Tainet Communication System
Performance |
Timeline |
Song Shang Electronics |
Tainet Communication |
Song Shang and Tainet Communication Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Song Shang and Tainet Communication
The main advantage of trading using opposite Song Shang and Tainet Communication positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Song Shang position performs unexpectedly, Tainet Communication 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 Tainet Communication will offset losses from the drop in Tainet Communication's long position.Song Shang vs. Tainet Communication System | Song Shang vs. TWOWAY Communications | Song Shang vs. Taiwan Mobile Co | Song Shang vs. Highwealth Construction Corp |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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