Correlation Between AfreecaTV and NHN KCP
Can any of the company-specific risk be diversified away by investing in both AfreecaTV and NHN KCP 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 AfreecaTV and NHN KCP into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AfreecaTV Co and NHN KCP Corp, you can compare the effects of market volatilities on AfreecaTV and NHN KCP 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 AfreecaTV with a short position of NHN KCP. Check out your portfolio center. Please also check ongoing floating volatility patterns of AfreecaTV and NHN KCP.
Diversification Opportunities for AfreecaTV and NHN KCP
Very weak diversification
The 3 months correlation between AfreecaTV and NHN is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding AfreecaTV Co and NHN KCP Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NHN KCP Corp and AfreecaTV 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 AfreecaTV Co are associated (or correlated) with NHN KCP. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NHN KCP Corp has no effect on the direction of AfreecaTV i.e., AfreecaTV and NHN KCP go up and down completely randomly.
Pair Corralation between AfreecaTV and NHN KCP
Assuming the 90 days trading horizon AfreecaTV is expected to generate 13.47 times less return on investment than NHN KCP. In addition to that, AfreecaTV is 1.0 times more volatile than NHN KCP Corp. It trades about 0.01 of its total potential returns per unit of risk. NHN KCP Corp is currently generating about 0.1 per unit of volatility. If you would invest 726,000 in NHN KCP Corp on September 14, 2024 and sell it today you would earn a total of 104,000 from holding NHN KCP Corp or generate 14.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
AfreecaTV Co vs. NHN KCP Corp
Performance |
Timeline |
AfreecaTV |
NHN KCP Corp |
AfreecaTV and NHN KCP Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AfreecaTV and NHN KCP
The main advantage of trading using opposite AfreecaTV and NHN KCP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AfreecaTV position performs unexpectedly, NHN KCP 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 NHN KCP will offset losses from the drop in NHN KCP's long position.The idea behind AfreecaTV Co and NHN KCP Corp 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.NHN KCP vs. Cube Entertainment | NHN KCP vs. Dreamus Company | NHN KCP vs. LG Energy Solution | NHN KCP vs. Dongwon System |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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