Correlation Between LEENO Industrial and Tokai Carbon
Can any of the company-specific risk be diversified away by investing in both LEENO Industrial and Tokai Carbon 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 LEENO Industrial and Tokai Carbon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LEENO Industrial and Tokai Carbon Korea, you can compare the effects of market volatilities on LEENO Industrial and Tokai Carbon 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 LEENO Industrial with a short position of Tokai Carbon. Check out your portfolio center. Please also check ongoing floating volatility patterns of LEENO Industrial and Tokai Carbon.
Diversification Opportunities for LEENO Industrial and Tokai Carbon
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between LEENO and Tokai is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding LEENO Industrial and Tokai Carbon Korea in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tokai Carbon Korea and LEENO Industrial 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 LEENO Industrial are associated (or correlated) with Tokai Carbon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tokai Carbon Korea has no effect on the direction of LEENO Industrial i.e., LEENO Industrial and Tokai Carbon go up and down completely randomly.
Pair Corralation between LEENO Industrial and Tokai Carbon
Assuming the 90 days trading horizon LEENO Industrial is expected to generate 4.25 times less return on investment than Tokai Carbon. In addition to that, LEENO Industrial is 1.04 times more volatile than Tokai Carbon Korea. It trades about 0.02 of its total potential returns per unit of risk. Tokai Carbon Korea is currently generating about 0.11 per unit of volatility. If you would invest 7,090,000 in Tokai Carbon Korea on December 29, 2024 and sell it today you would earn a total of 1,290,000 from holding Tokai Carbon Korea or generate 18.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
LEENO Industrial vs. Tokai Carbon Korea
Performance |
Timeline |
LEENO Industrial |
Tokai Carbon Korea |
LEENO Industrial and Tokai Carbon Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with LEENO Industrial and Tokai Carbon
The main advantage of trading using opposite LEENO Industrial and Tokai Carbon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LEENO Industrial position performs unexpectedly, Tokai Carbon 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 Tokai Carbon will offset losses from the drop in Tokai Carbon's long position.LEENO Industrial vs. Tokai Carbon Korea | LEENO Industrial vs. LF Co | LEENO Industrial vs. Koh Young Technology |
Tokai Carbon vs. LEENO Industrial | Tokai Carbon vs. Wonik Ips Co | Tokai Carbon vs. Dongjin Semichem Co | Tokai Carbon vs. Hana Materials |
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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