Correlation Between MEDIANA CoLtd and DB Insurance
Can any of the company-specific risk be diversified away by investing in both MEDIANA CoLtd and DB Insurance 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 MEDIANA CoLtd and DB Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MEDIANA CoLtd and DB Insurance Co, you can compare the effects of market volatilities on MEDIANA CoLtd and DB Insurance 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 MEDIANA CoLtd with a short position of DB Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of MEDIANA CoLtd and DB Insurance.
Diversification Opportunities for MEDIANA CoLtd and DB Insurance
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between MEDIANA and 005830 is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding MEDIANA CoLtd and DB Insurance Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DB Insurance and MEDIANA CoLtd 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 MEDIANA CoLtd are associated (or correlated) with DB Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DB Insurance has no effect on the direction of MEDIANA CoLtd i.e., MEDIANA CoLtd and DB Insurance go up and down completely randomly.
Pair Corralation between MEDIANA CoLtd and DB Insurance
Assuming the 90 days trading horizon MEDIANA CoLtd is expected to generate 1.21 times more return on investment than DB Insurance. However, MEDIANA CoLtd is 1.21 times more volatile than DB Insurance Co. It trades about -0.02 of its potential returns per unit of risk. DB Insurance Co is currently generating about -0.03 per unit of risk. If you would invest 515,000 in MEDIANA CoLtd on September 13, 2024 and sell it today you would lose (30,500) from holding MEDIANA CoLtd or give up 5.92% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
MEDIANA CoLtd vs. DB Insurance Co
Performance |
Timeline |
MEDIANA CoLtd |
DB Insurance |
MEDIANA CoLtd and DB Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MEDIANA CoLtd and DB Insurance
The main advantage of trading using opposite MEDIANA CoLtd and DB Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MEDIANA CoLtd position performs unexpectedly, DB Insurance 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 DB Insurance will offset losses from the drop in DB Insurance's long position.MEDIANA CoLtd vs. Samsung Electronics Co | MEDIANA CoLtd vs. Samsung Electronics Co | MEDIANA CoLtd vs. SK Hynix | MEDIANA CoLtd vs. SK Holdings Co |
DB Insurance vs. KB Financial Group | DB Insurance vs. Shinhan Financial Group | DB Insurance vs. Hana Financial | DB Insurance vs. Woori Financial Group |
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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