Correlation Between MOBA Network and Kancera AB
Can any of the company-specific risk be diversified away by investing in both MOBA Network and Kancera AB 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 MOBA Network and Kancera AB into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MOBA Network publ and Kancera AB, you can compare the effects of market volatilities on MOBA Network and Kancera AB 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 MOBA Network with a short position of Kancera AB. Check out your portfolio center. Please also check ongoing floating volatility patterns of MOBA Network and Kancera AB.
Diversification Opportunities for MOBA Network and Kancera AB
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between MOBA and Kancera is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding MOBA Network publ and Kancera AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kancera AB and MOBA Network 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 MOBA Network publ are associated (or correlated) with Kancera AB. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kancera AB has no effect on the direction of MOBA Network i.e., MOBA Network and Kancera AB go up and down completely randomly.
Pair Corralation between MOBA Network and Kancera AB
Assuming the 90 days trading horizon MOBA Network publ is expected to under-perform the Kancera AB. But the stock apears to be less risky and, when comparing its historical volatility, MOBA Network publ is 1.56 times less risky than Kancera AB. The stock trades about -0.04 of its potential returns per unit of risk. The Kancera AB is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 215.00 in Kancera AB on September 4, 2024 and sell it today you would lose (106.00) from holding Kancera AB or give up 49.3% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
MOBA Network publ vs. Kancera AB
Performance |
| Timeline |
| MOBA Network publ |
| Kancera AB |
MOBA Network and Kancera AB Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with MOBA Network and Kancera AB
The main advantage of trading using opposite MOBA Network and Kancera AB positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MOBA Network position performs unexpectedly, Kancera AB 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 Kancera AB will offset losses from the drop in Kancera AB's long position.| MOBA Network vs. Greater Than AB | MOBA Network vs. IAR Systems Group | MOBA Network vs. Lime Technologies AB | MOBA Network vs. FormPipe Software AB |
| Kancera AB vs. Combigene AB | Kancera AB vs. Cantargia AB | Kancera AB vs. Fingerprint Cards AB | Kancera AB vs. Spectrumone publ AB |
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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