Correlation Between ITM Semiconductor and Tokai Carbon
Can any of the company-specific risk be diversified away by investing in both ITM Semiconductor 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 ITM Semiconductor and Tokai Carbon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ITM Semiconductor Co and Tokai Carbon Korea, you can compare the effects of market volatilities on ITM Semiconductor 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 ITM Semiconductor with a short position of Tokai Carbon. Check out your portfolio center. Please also check ongoing floating volatility patterns of ITM Semiconductor and Tokai Carbon.
Diversification Opportunities for ITM Semiconductor and Tokai Carbon
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between ITM and Tokai is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding ITM Semiconductor Co 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 ITM Semiconductor 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 ITM Semiconductor Co 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 ITM Semiconductor i.e., ITM Semiconductor and Tokai Carbon go up and down completely randomly.
Pair Corralation between ITM Semiconductor and Tokai Carbon
Assuming the 90 days trading horizon ITM Semiconductor Co is expected to under-perform the Tokai Carbon. In addition to that, ITM Semiconductor is 1.19 times more volatile than Tokai Carbon Korea. It trades about -0.19 of its total potential returns per unit of risk. Tokai Carbon Korea is currently generating about -0.2 per unit of volatility. If you would invest 9,120,000 in Tokai Carbon Korea on September 5, 2024 and sell it today you would lose (2,240,000) from holding Tokai Carbon Korea or give up 24.56% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
ITM Semiconductor Co vs. Tokai Carbon Korea
Performance |
Timeline |
ITM Semiconductor |
Tokai Carbon Korea |
ITM Semiconductor and Tokai Carbon Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ITM Semiconductor and Tokai Carbon
The main advantage of trading using opposite ITM Semiconductor and Tokai Carbon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ITM Semiconductor 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.ITM Semiconductor vs. SS TECH | ITM Semiconductor vs. LEENO Industrial | ITM Semiconductor vs. Wonik Ips Co | ITM Semiconductor vs. SFA Semicon Co |
Tokai Carbon vs. SK Hynix | Tokai Carbon vs. LX Semicon Co | Tokai Carbon vs. People Technology | 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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