Correlation Between POWERGRID Infrastructure and SBI Life
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By analyzing existing cross correlation between POWERGRID Infrastructure Investment and SBI Life Insurance, you can compare the effects of market volatilities on POWERGRID Infrastructure and SBI Life 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 POWERGRID Infrastructure with a short position of SBI Life. Check out your portfolio center. Please also check ongoing floating volatility patterns of POWERGRID Infrastructure and SBI Life.
Diversification Opportunities for POWERGRID Infrastructure and SBI Life
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between POWERGRID and SBI is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding POWERGRID Infrastructure Inves and SBI Life Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SBI Life Insurance and POWERGRID Infrastructure 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 POWERGRID Infrastructure Investment are associated (or correlated) with SBI Life. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SBI Life Insurance has no effect on the direction of POWERGRID Infrastructure i.e., POWERGRID Infrastructure and SBI Life go up and down completely randomly.
Pair Corralation between POWERGRID Infrastructure and SBI Life
Assuming the 90 days trading horizon POWERGRID Infrastructure Investment is expected to under-perform the SBI Life. But the stock apears to be less risky and, when comparing its historical volatility, POWERGRID Infrastructure Investment is 2.04 times less risky than SBI Life. The stock trades about -0.12 of its potential returns per unit of risk. The SBI Life Insurance is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 129,074 in SBI Life Insurance on October 11, 2024 and sell it today you would earn a total of 17,241 from holding SBI Life Insurance or generate 13.36% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 99.38% |
| Values | Daily Returns |
POWERGRID Infrastructure Inves vs. SBI Life Insurance
Performance |
| Timeline |
| POWERGRID Infrastructure |
| SBI Life Insurance |
POWERGRID Infrastructure and SBI Life Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with POWERGRID Infrastructure and SBI Life
The main advantage of trading using opposite POWERGRID Infrastructure and SBI Life positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POWERGRID Infrastructure position performs unexpectedly, SBI Life 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 SBI Life will offset losses from the drop in SBI Life's long position.The idea behind POWERGRID Infrastructure Investment and SBI Life Insurance pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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