Correlation Between POWERGRID Infrastructure and Kewal Kiran
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By analyzing existing cross correlation between POWERGRID Infrastructure Investment and Kewal Kiran Clothing, you can compare the effects of market volatilities on POWERGRID Infrastructure and Kewal Kiran 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 Kewal Kiran. Check out your portfolio center. Please also check ongoing floating volatility patterns of POWERGRID Infrastructure and Kewal Kiran.
Diversification Opportunities for POWERGRID Infrastructure and Kewal Kiran
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between POWERGRID and Kewal is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding POWERGRID Infrastructure Inves and Kewal Kiran Clothing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kewal Kiran Clothing 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 Kewal Kiran. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kewal Kiran Clothing has no effect on the direction of POWERGRID Infrastructure i.e., POWERGRID Infrastructure and Kewal Kiran go up and down completely randomly.
Pair Corralation between POWERGRID Infrastructure and Kewal Kiran
Assuming the 90 days trading horizon POWERGRID Infrastructure Investment is expected to generate 0.37 times more return on investment than Kewal Kiran. However, POWERGRID Infrastructure Investment is 2.71 times less risky than Kewal Kiran. It trades about -0.11 of its potential returns per unit of risk. Kewal Kiran Clothing is currently generating about -0.1 per unit of risk. If you would invest 8,833 in POWERGRID Infrastructure Investment on October 10, 2024 and sell it today you would lose (400.00) from holding POWERGRID Infrastructure Investment or give up 4.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 96.77% |
Values | Daily Returns |
POWERGRID Infrastructure Inves vs. Kewal Kiran Clothing
Performance |
Timeline |
POWERGRID Infrastructure |
Kewal Kiran Clothing |
POWERGRID Infrastructure and Kewal Kiran Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with POWERGRID Infrastructure and Kewal Kiran
The main advantage of trading using opposite POWERGRID Infrastructure and Kewal Kiran positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POWERGRID Infrastructure position performs unexpectedly, Kewal Kiran 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 Kewal Kiran will offset losses from the drop in Kewal Kiran's long position.The idea behind POWERGRID Infrastructure Investment and Kewal Kiran Clothing 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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