Correlation Between Silvercorp Metals and Automatic Data
Can any of the company-specific risk be diversified away by investing in both Silvercorp Metals and Automatic Data 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 Silvercorp Metals and Automatic Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Silvercorp Metals and Automatic Data Processing, you can compare the effects of market volatilities on Silvercorp Metals and Automatic Data 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 Silvercorp Metals with a short position of Automatic Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Silvercorp Metals and Automatic Data.
Diversification Opportunities for Silvercorp Metals and Automatic Data
-0.54 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Silvercorp and Automatic is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Silvercorp Metals and Automatic Data Processing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Automatic Data Processing and Silvercorp Metals 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 Silvercorp Metals are associated (or correlated) with Automatic Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Automatic Data Processing has no effect on the direction of Silvercorp Metals i.e., Silvercorp Metals and Automatic Data go up and down completely randomly.
Pair Corralation between Silvercorp Metals and Automatic Data
Assuming the 90 days trading horizon Silvercorp Metals is expected to under-perform the Automatic Data. In addition to that, Silvercorp Metals is 3.51 times more volatile than Automatic Data Processing. It trades about -0.22 of its total potential returns per unit of risk. Automatic Data Processing is currently generating about 0.05 per unit of volatility. If you would invest 28,693 in Automatic Data Processing on September 25, 2024 and sell it today you would earn a total of 639.00 from holding Automatic Data Processing or generate 2.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Silvercorp Metals vs. Automatic Data Processing
Performance |
Timeline |
Silvercorp Metals |
Automatic Data Processing |
Silvercorp Metals and Automatic Data Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Silvercorp Metals and Automatic Data
The main advantage of trading using opposite Silvercorp Metals and Automatic Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Silvercorp Metals position performs unexpectedly, Automatic Data 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 Automatic Data will offset losses from the drop in Automatic Data's long position.Silvercorp Metals vs. GreenX Metals | Silvercorp Metals vs. Central Asia Metals | Silvercorp Metals vs. Jacquet Metal Service | Silvercorp Metals vs. Golden Metal Resources |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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