Correlation Between Humasis and KCC
Can any of the company-specific risk be diversified away by investing in both Humasis and KCC 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 Humasis and KCC into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Humasis Co and KCC Corporation, you can compare the effects of market volatilities on Humasis and KCC 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 Humasis with a short position of KCC. Check out your portfolio center. Please also check ongoing floating volatility patterns of Humasis and KCC.
Diversification Opportunities for Humasis and KCC
Excellent diversification
The 3 months correlation between Humasis and KCC is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Humasis Co and KCC Corp. in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KCC Corporation and Humasis 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 Humasis Co are associated (or correlated) with KCC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KCC Corporation has no effect on the direction of Humasis i.e., Humasis and KCC go up and down completely randomly.
Pair Corralation between Humasis and KCC
Assuming the 90 days trading horizon Humasis Co is expected to under-perform the KCC. But the stock apears to be less risky and, when comparing its historical volatility, Humasis Co is 1.28 times less risky than KCC. The stock trades about -0.26 of its potential returns per unit of risk. The KCC Corporation is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 26,350,000 in KCC Corporation on January 3, 2025 and sell it today you would lose (800,000) from holding KCC Corporation or give up 3.04% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Humasis Co vs. KCC Corp.
Performance |
| Timeline |
| Humasis |
| KCC Corporation |
Humasis and KCC Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Humasis and KCC
The main advantage of trading using opposite Humasis and KCC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Humasis position performs unexpectedly, KCC 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 KCC will offset losses from the drop in KCC's long position.The idea behind Humasis Co and KCC Corporation pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| KCC vs. Digital Power Communications | KCC vs. LS Materials | KCC vs. National Plastic Co | KCC vs. WONIK Materials CoLtd |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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