Correlation Between Motorcar Parts and Kandi Technologies
Can any of the company-specific risk be diversified away by investing in both Motorcar Parts and Kandi Technologies 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 Motorcar Parts and Kandi Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Motorcar Parts of and Kandi Technologies Group, you can compare the effects of market volatilities on Motorcar Parts and Kandi Technologies 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 Motorcar Parts with a short position of Kandi Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Motorcar Parts and Kandi Technologies.
Diversification Opportunities for Motorcar Parts and Kandi Technologies
-0.78 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Motorcar and Kandi is -0.78. Overlapping area represents the amount of risk that can be diversified away by holding Motorcar Parts of and Kandi Technologies Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kandi Technologies and Motorcar Parts 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 Motorcar Parts of are associated (or correlated) with Kandi Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kandi Technologies has no effect on the direction of Motorcar Parts i.e., Motorcar Parts and Kandi Technologies go up and down completely randomly.
Pair Corralation between Motorcar Parts and Kandi Technologies
Given the investment horizon of 90 days Motorcar Parts of is expected to generate 0.79 times more return on investment than Kandi Technologies. However, Motorcar Parts of is 1.27 times less risky than Kandi Technologies. It trades about 0.05 of its potential returns per unit of risk. Kandi Technologies Group is currently generating about -0.06 per unit of risk. If you would invest 627.00 in Motorcar Parts of on October 21, 2024 and sell it today you would earn a total of 93.00 from holding Motorcar Parts of or generate 14.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Motorcar Parts of vs. Kandi Technologies Group
Performance |
Timeline |
Motorcar Parts |
Kandi Technologies |
Motorcar Parts and Kandi Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Motorcar Parts and Kandi Technologies
The main advantage of trading using opposite Motorcar Parts and Kandi Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Motorcar Parts position performs unexpectedly, Kandi Technologies 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 Kandi Technologies will offset losses from the drop in Kandi Technologies' long position.Motorcar Parts vs. Monro Muffler Brake | Motorcar Parts vs. Standard Motor Products | Motorcar Parts vs. Stoneridge | Motorcar Parts vs. Douglas Dynamics |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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