Correlation Between China DatangRenewable and Penske Automotive
Can any of the company-specific risk be diversified away by investing in both China DatangRenewable and Penske Automotive 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 China DatangRenewable and Penske Automotive into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Datang and Penske Automotive Group, you can compare the effects of market volatilities on China DatangRenewable and Penske Automotive 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 China DatangRenewable with a short position of Penske Automotive. Check out your portfolio center. Please also check ongoing floating volatility patterns of China DatangRenewable and Penske Automotive.
Diversification Opportunities for China DatangRenewable and Penske Automotive
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between China and Penske is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding China Datang and Penske Automotive Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Penske Automotive and China DatangRenewable 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 China Datang are associated (or correlated) with Penske Automotive. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Penske Automotive has no effect on the direction of China DatangRenewable i.e., China DatangRenewable and Penske Automotive go up and down completely randomly.
Pair Corralation between China DatangRenewable and Penske Automotive
Assuming the 90 days horizon China Datang is expected to generate 1.92 times more return on investment than Penske Automotive. However, China DatangRenewable is 1.92 times more volatile than Penske Automotive Group. It trades about 0.06 of its potential returns per unit of risk. Penske Automotive Group is currently generating about -0.06 per unit of risk. If you would invest 24.00 in China Datang on December 21, 2024 and sell it today you would earn a total of 2.00 from holding China Datang or generate 8.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
China Datang vs. Penske Automotive Group
Performance |
Timeline |
China DatangRenewable |
Penske Automotive |
China DatangRenewable and Penske Automotive Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with China DatangRenewable and Penske Automotive
The main advantage of trading using opposite China DatangRenewable and Penske Automotive positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China DatangRenewable position performs unexpectedly, Penske Automotive 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 Penske Automotive will offset losses from the drop in Penske Automotive's long position.China DatangRenewable vs. Retail Estates NV | China DatangRenewable vs. TRADEGATE | China DatangRenewable vs. Tradegate AG Wertpapierhandelsbank | China DatangRenewable vs. AUTO TRADER ADR |
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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 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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