Correlation Between KMBB34 and Infosys
Can any of the company-specific risk be diversified away by investing in both KMBB34 and Infosys 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 KMBB34 and Infosys into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KMBB34 and Infosys Limited, you can compare the effects of market volatilities on KMBB34 and Infosys 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 KMBB34 with a short position of Infosys. Check out your portfolio center. Please also check ongoing floating volatility patterns of KMBB34 and Infosys.
Diversification Opportunities for KMBB34 and Infosys
Very poor diversification
The 3 months correlation between KMBB34 and Infosys is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding KMBB34 and Infosys Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Infosys Limited and KMBB34 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 KMBB34 are associated (or correlated) with Infosys. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Infosys Limited has no effect on the direction of KMBB34 i.e., KMBB34 and Infosys go up and down completely randomly.
Pair Corralation between KMBB34 and Infosys
Assuming the 90 days trading horizon KMBB34 is expected to generate 2.15 times less return on investment than Infosys. But when comparing it to its historical volatility, KMBB34 is 1.44 times less risky than Infosys. It trades about 0.09 of its potential returns per unit of risk. Infosys Limited is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 6,210 in Infosys Limited on September 23, 2024 and sell it today you would earn a total of 958.00 from holding Infosys Limited or generate 15.43% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 96.88% |
Values | Daily Returns |
KMBB34 vs. Infosys Limited
Performance |
Timeline |
KMBB34 |
Infosys Limited |
KMBB34 and Infosys Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KMBB34 and Infosys
The main advantage of trading using opposite KMBB34 and Infosys positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KMBB34 position performs unexpectedly, Infosys 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 Infosys will offset losses from the drop in Infosys' long position.The idea behind KMBB34 and Infosys Limited 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.Infosys vs. Accenture plc | Infosys vs. International Business Machines | Infosys vs. Fiserv Inc | Infosys vs. Fidelity National Information |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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