Correlation Between BigBearai Holdings and Infosys
Can any of the company-specific risk be diversified away by investing in both BigBearai Holdings 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 BigBearai Holdings and Infosys into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BigBearai Holdings and Infosys Ltd ADR, you can compare the effects of market volatilities on BigBearai Holdings 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 BigBearai Holdings with a short position of Infosys. Check out your portfolio center. Please also check ongoing floating volatility patterns of BigBearai Holdings and Infosys.
Diversification Opportunities for BigBearai Holdings and Infosys
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between BigBearai and Infosys is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding BigBearai Holdings and Infosys Ltd ADR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Infosys Ltd ADR and BigBearai Holdings 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 BigBearai Holdings 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 Ltd ADR has no effect on the direction of BigBearai Holdings i.e., BigBearai Holdings and Infosys go up and down completely randomly.
Pair Corralation between BigBearai Holdings and Infosys
Given the investment horizon of 90 days BigBearai Holdings is expected to generate 7.06 times more return on investment than Infosys. However, BigBearai Holdings is 7.06 times more volatile than Infosys Ltd ADR. It trades about 0.3 of its potential returns per unit of risk. Infosys Ltd ADR is currently generating about 0.1 per unit of risk. If you would invest 159.00 in BigBearai Holdings on October 7, 2024 and sell it today you would earn a total of 294.00 from holding BigBearai Holdings or generate 184.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
BigBearai Holdings vs. Infosys Ltd ADR
Performance |
Timeline |
BigBearai Holdings |
Infosys Ltd ADR |
BigBearai Holdings and Infosys Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BigBearai Holdings and Infosys
The main advantage of trading using opposite BigBearai Holdings and Infosys positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BigBearai Holdings 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.BigBearai Holdings vs. Innodata | BigBearai Holdings vs. CLPS Inc | BigBearai Holdings vs. ARB IOT Group | BigBearai Holdings vs. FiscalNote Holdings |
Infosys vs. Cognizant Technology Solutions | Infosys vs. WNS Holdings | Infosys vs. CLARIVATE PLC | Infosys vs. Gartner |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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