Correlation Between Military Insurance and POST TELECOMMU
Can any of the company-specific risk be diversified away by investing in both Military Insurance and POST TELECOMMU 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 Military Insurance and POST TELECOMMU into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Military Insurance Corp and POST TELECOMMU, you can compare the effects of market volatilities on Military Insurance and POST TELECOMMU 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 Military Insurance with a short position of POST TELECOMMU. Check out your portfolio center. Please also check ongoing floating volatility patterns of Military Insurance and POST TELECOMMU.
Diversification Opportunities for Military Insurance and POST TELECOMMU
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Military and POST is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding Military Insurance Corp and POST TELECOMMU in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on POST TELECOMMU and Military Insurance 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 Military Insurance Corp are associated (or correlated) with POST TELECOMMU. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of POST TELECOMMU has no effect on the direction of Military Insurance i.e., Military Insurance and POST TELECOMMU go up and down completely randomly.
Pair Corralation between Military Insurance and POST TELECOMMU
Assuming the 90 days trading horizon Military Insurance Corp is expected to generate 0.72 times more return on investment than POST TELECOMMU. However, Military Insurance Corp is 1.39 times less risky than POST TELECOMMU. It trades about 0.01 of its potential returns per unit of risk. POST TELECOMMU is currently generating about 0.0 per unit of risk. If you would invest 1,705,161 in Military Insurance Corp on October 10, 2024 and sell it today you would lose (15,161) from holding Military Insurance Corp or give up 0.89% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 91.06% |
Values | Daily Returns |
Military Insurance Corp vs. POST TELECOMMU
Performance |
Timeline |
Military Insurance Corp |
POST TELECOMMU |
Military Insurance and POST TELECOMMU Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Military Insurance and POST TELECOMMU
The main advantage of trading using opposite Military Insurance and POST TELECOMMU positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Military Insurance position performs unexpectedly, POST TELECOMMU 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 POST TELECOMMU will offset losses from the drop in POST TELECOMMU's long position.Military Insurance vs. FIT INVEST JSC | Military Insurance vs. Damsan JSC | Military Insurance vs. An Phat Plastic | Military Insurance vs. APG Securities Joint |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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