Correlation Between SBI Insurance and AVITA Medical
Can any of the company-specific risk be diversified away by investing in both SBI Insurance and AVITA Medical 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 SBI Insurance and AVITA Medical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SBI Insurance Group and AVITA Medical, you can compare the effects of market volatilities on SBI Insurance and AVITA Medical 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 SBI Insurance with a short position of AVITA Medical. Check out your portfolio center. Please also check ongoing floating volatility patterns of SBI Insurance and AVITA Medical.
Diversification Opportunities for SBI Insurance and AVITA Medical
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between SBI and AVITA is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding SBI Insurance Group and AVITA Medical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AVITA Medical and SBI 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 SBI Insurance Group are associated (or correlated) with AVITA Medical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AVITA Medical has no effect on the direction of SBI Insurance i.e., SBI Insurance and AVITA Medical go up and down completely randomly.
Pair Corralation between SBI Insurance and AVITA Medical
Assuming the 90 days trading horizon SBI Insurance is expected to generate 10.84 times less return on investment than AVITA Medical. But when comparing it to its historical volatility, SBI Insurance Group is 2.53 times less risky than AVITA Medical. It trades about 0.04 of its potential returns per unit of risk. AVITA Medical is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 162.00 in AVITA Medical on September 2, 2024 and sell it today you would earn a total of 78.00 from holding AVITA Medical or generate 48.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
SBI Insurance Group vs. AVITA Medical
Performance |
Timeline |
SBI Insurance Group |
AVITA Medical |
SBI Insurance and AVITA Medical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SBI Insurance and AVITA Medical
The main advantage of trading using opposite SBI Insurance and AVITA Medical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SBI Insurance position performs unexpectedly, AVITA Medical 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 AVITA Medical will offset losses from the drop in AVITA Medical's long position.SBI Insurance vs. Apple Inc | SBI Insurance vs. Apple Inc | SBI Insurance vs. Apple Inc | SBI Insurance vs. Apple Inc |
AVITA Medical vs. CECO ENVIRONMENTAL | AVITA Medical vs. MITSUBISHI STEEL MFG | AVITA Medical vs. SBI Insurance Group | AVITA Medical vs. BLUESCOPE STEEL |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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