Correlation Between INSURANCE AUST and MSAD INSURANCE
Can any of the company-specific risk be diversified away by investing in both INSURANCE AUST and MSAD 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 INSURANCE AUST and MSAD INSURANCE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between INSURANCE AUST GRP and MSAD INSURANCE, you can compare the effects of market volatilities on INSURANCE AUST and MSAD 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 INSURANCE AUST with a short position of MSAD INSURANCE. Check out your portfolio center. Please also check ongoing floating volatility patterns of INSURANCE AUST and MSAD INSURANCE.
Diversification Opportunities for INSURANCE AUST and MSAD INSURANCE
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between INSURANCE and MSAD is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding INSURANCE AUST GRP and MSAD INSURANCE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MSAD INSURANCE and INSURANCE AUST 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 INSURANCE AUST GRP are associated (or correlated) with MSAD INSURANCE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MSAD INSURANCE has no effect on the direction of INSURANCE AUST i.e., INSURANCE AUST and MSAD INSURANCE go up and down completely randomly.
Pair Corralation between INSURANCE AUST and MSAD INSURANCE
Assuming the 90 days trading horizon INSURANCE AUST GRP is expected to generate 1.03 times more return on investment than MSAD INSURANCE. However, INSURANCE AUST is 1.03 times more volatile than MSAD INSURANCE. It trades about 0.2 of its potential returns per unit of risk. MSAD INSURANCE is currently generating about 0.09 per unit of risk. If you would invest 456.00 in INSURANCE AUST GRP on August 24, 2024 and sell it today you would earn a total of 36.00 from holding INSURANCE AUST GRP or generate 7.89% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.65% |
| Values | Daily Returns |
INSURANCE AUST GRP vs. MSAD INSURANCE
Performance |
| Timeline |
| INSURANCE AUST GRP |
| MSAD INSURANCE |
INSURANCE AUST and MSAD INSURANCE Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with INSURANCE AUST and MSAD INSURANCE
The main advantage of trading using opposite INSURANCE AUST and MSAD INSURANCE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if INSURANCE AUST position performs unexpectedly, MSAD 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 MSAD INSURANCE will offset losses from the drop in MSAD INSURANCE's long position.| INSURANCE AUST vs. Apple Inc | INSURANCE AUST vs. Apple Inc | INSURANCE AUST vs. Apple Inc | INSURANCE AUST vs. Apple Inc |
| MSAD INSURANCE vs. Apple Inc | MSAD INSURANCE vs. Apple Inc | MSAD INSURANCE vs. Apple Inc | MSAD INSURANCE vs. Apple Inc |
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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