Correlation Between Kalyani Steels and Power Finance
Can any of the company-specific risk be diversified away by investing in both Kalyani Steels and Power Finance 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 Kalyani Steels and Power Finance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kalyani Steels Limited and Power Finance, you can compare the effects of market volatilities on Kalyani Steels and Power Finance 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 Kalyani Steels with a short position of Power Finance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kalyani Steels and Power Finance.
Diversification Opportunities for Kalyani Steels and Power Finance
0.12 | Correlation Coefficient |
Average diversification
The 3 months correlation between Kalyani and Power is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding Kalyani Steels Limited and Power Finance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power Finance and Kalyani Steels 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 Kalyani Steels Limited are associated (or correlated) with Power Finance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power Finance has no effect on the direction of Kalyani Steels i.e., Kalyani Steels and Power Finance go up and down completely randomly.
Pair Corralation between Kalyani Steels and Power Finance
Assuming the 90 days trading horizon Kalyani Steels Limited is expected to generate 2.26 times more return on investment than Power Finance. However, Kalyani Steels is 2.26 times more volatile than Power Finance. It trades about 0.3 of its potential returns per unit of risk. Power Finance is currently generating about -0.22 per unit of risk. If you would invest 91,450 in Kalyani Steels Limited on October 5, 2024 and sell it today you would earn a total of 23,930 from holding Kalyani Steels Limited or generate 26.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 90.91% |
Values | Daily Returns |
Kalyani Steels Limited vs. Power Finance
Performance |
Timeline |
Kalyani Steels |
Power Finance |
Kalyani Steels and Power Finance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kalyani Steels and Power Finance
The main advantage of trading using opposite Kalyani Steels and Power Finance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kalyani Steels position performs unexpectedly, Power Finance 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 Power Finance will offset losses from the drop in Power Finance's long position.Kalyani Steels vs. NMDC Limited | Kalyani Steels vs. Steel Authority of | Kalyani Steels vs. Embassy Office Parks | Kalyani Steels vs. Jai Balaji Industries |
Power Finance vs. Sanginita Chemicals Limited | Power Finance vs. DMCC SPECIALITY CHEMICALS | Power Finance vs. Sumitomo Chemical India | Power Finance vs. Thirumalai Chemicals Limited |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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