Correlation Between Kenmec Mechanical and Song Ho
Can any of the company-specific risk be diversified away by investing in both Kenmec Mechanical and Song Ho 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 Kenmec Mechanical and Song Ho into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kenmec Mechanical Engineering and Song Ho Industrial, you can compare the effects of market volatilities on Kenmec Mechanical and Song Ho 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 Kenmec Mechanical with a short position of Song Ho. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kenmec Mechanical and Song Ho.
Diversification Opportunities for Kenmec Mechanical and Song Ho
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Kenmec and Song is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Kenmec Mechanical Engineering and Song Ho Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Song Ho Industrial and Kenmec Mechanical 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 Kenmec Mechanical Engineering are associated (or correlated) with Song Ho. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Song Ho Industrial has no effect on the direction of Kenmec Mechanical i.e., Kenmec Mechanical and Song Ho go up and down completely randomly.
Pair Corralation between Kenmec Mechanical and Song Ho
Assuming the 90 days trading horizon Kenmec Mechanical is expected to generate 1.23 times less return on investment than Song Ho. In addition to that, Kenmec Mechanical is 7.79 times more volatile than Song Ho Industrial. It trades about 0.01 of its total potential returns per unit of risk. Song Ho Industrial is currently generating about 0.05 per unit of volatility. If you would invest 2,750 in Song Ho Industrial on October 24, 2024 and sell it today you would earn a total of 10.00 from holding Song Ho Industrial or generate 0.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Kenmec Mechanical Engineering vs. Song Ho Industrial
Performance |
Timeline |
Kenmec Mechanical |
Song Ho Industrial |
Kenmec Mechanical and Song Ho Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kenmec Mechanical and Song Ho
The main advantage of trading using opposite Kenmec Mechanical and Song Ho positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kenmec Mechanical position performs unexpectedly, Song Ho 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 Song Ho will offset losses from the drop in Song Ho's long position.Kenmec Mechanical vs. TWOWAY Communications | Kenmec Mechanical vs. Farglory FTZ Investment | Kenmec Mechanical vs. Cameo Communications | Kenmec Mechanical vs. Tai Tung Communication |
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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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