Correlation Between Innometry and Samsung Heavy
Can any of the company-specific risk be diversified away by investing in both Innometry and Samsung Heavy 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 Innometry and Samsung Heavy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Innometry Co and Samsung Heavy Industries, you can compare the effects of market volatilities on Innometry and Samsung Heavy 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 Innometry with a short position of Samsung Heavy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Innometry and Samsung Heavy.
Diversification Opportunities for Innometry and Samsung Heavy
-0.63 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Innometry and Samsung is -0.63. Overlapping area represents the amount of risk that can be diversified away by holding Innometry Co and Samsung Heavy Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Samsung Heavy Industries and Innometry 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 Innometry Co are associated (or correlated) with Samsung Heavy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Samsung Heavy Industries has no effect on the direction of Innometry i.e., Innometry and Samsung Heavy go up and down completely randomly.
Pair Corralation between Innometry and Samsung Heavy
Assuming the 90 days trading horizon Innometry Co is expected to under-perform the Samsung Heavy. In addition to that, Innometry is 1.06 times more volatile than Samsung Heavy Industries. It trades about -0.09 of its total potential returns per unit of risk. Samsung Heavy Industries is currently generating about 0.07 per unit of volatility. If you would invest 960,000 in Samsung Heavy Industries on September 3, 2024 and sell it today you would earn a total of 202,000 from holding Samsung Heavy Industries or generate 21.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Innometry Co vs. Samsung Heavy Industries
Performance |
| Timeline |
| Innometry |
| Samsung Heavy Industries |
Innometry and Samsung Heavy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Innometry and Samsung Heavy
The main advantage of trading using opposite Innometry and Samsung Heavy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Innometry position performs unexpectedly, Samsung Heavy 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 Samsung Heavy will offset losses from the drop in Samsung Heavy's long position.| Innometry vs. Daejoo Electronic Materials | Innometry vs. Parksystems Corp | Innometry vs. BH Co | Innometry vs. Partron Co |
| Samsung Heavy vs. KB Financial Group | Samsung Heavy vs. Shinhan Financial Group | Samsung Heavy vs. Daejung Chemicals Metals | Samsung Heavy vs. SK Chemicals Co |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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