Correlation Between Arcosa and Shenzhen Investment
Can any of the company-specific risk be diversified away by investing in both Arcosa and Shenzhen Investment 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 Arcosa and Shenzhen Investment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Arcosa Inc and Shenzhen Investment Holdings, you can compare the effects of market volatilities on Arcosa and Shenzhen Investment 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 Arcosa with a short position of Shenzhen Investment. Check out your portfolio center. Please also check ongoing floating volatility patterns of Arcosa and Shenzhen Investment.
Diversification Opportunities for Arcosa and Shenzhen Investment
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Arcosa and Shenzhen is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Arcosa Inc and Shenzhen Investment Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shenzhen Investment and Arcosa 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 Arcosa Inc are associated (or correlated) with Shenzhen Investment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shenzhen Investment has no effect on the direction of Arcosa i.e., Arcosa and Shenzhen Investment go up and down completely randomly.
Pair Corralation between Arcosa and Shenzhen Investment
Considering the 90-day investment horizon Arcosa is expected to generate 2.58 times less return on investment than Shenzhen Investment. But when comparing it to its historical volatility, Arcosa Inc is 2.09 times less risky than Shenzhen Investment. It trades about 0.06 of its potential returns per unit of risk. Shenzhen Investment Holdings is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 5.96 in Shenzhen Investment Holdings on October 8, 2024 and sell it today you would earn a total of 16.04 from holding Shenzhen Investment Holdings or generate 269.13% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Arcosa Inc vs. Shenzhen Investment Holdings
Performance |
Timeline |
Arcosa Inc |
Shenzhen Investment |
Arcosa and Shenzhen Investment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Arcosa and Shenzhen Investment
The main advantage of trading using opposite Arcosa and Shenzhen Investment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Arcosa position performs unexpectedly, Shenzhen Investment 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 Shenzhen Investment will offset losses from the drop in Shenzhen Investment's long position.Arcosa vs. Construction Partners | Arcosa vs. Topbuild Corp | Arcosa vs. Comfort Systems USA | Arcosa vs. Ameresco |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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