Correlation Between Bank of Zhengzhou and Advanced Micro
Can any of the company-specific risk be diversified away by investing in both Bank of Zhengzhou and Advanced Micro 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 Bank of Zhengzhou and Advanced Micro into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of Zhengzhou and Advanced Micro Devices, you can compare the effects of market volatilities on Bank of Zhengzhou and Advanced Micro 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 Bank of Zhengzhou with a short position of Advanced Micro. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of Zhengzhou and Advanced Micro.
Diversification Opportunities for Bank of Zhengzhou and Advanced Micro
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Bank and Advanced is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Bank of Zhengzhou and Advanced Micro Devices in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Advanced Micro Devices and Bank of Zhengzhou 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 Bank of Zhengzhou are associated (or correlated) with Advanced Micro. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Advanced Micro Devices has no effect on the direction of Bank of Zhengzhou i.e., Bank of Zhengzhou and Advanced Micro go up and down completely randomly.
Pair Corralation between Bank of Zhengzhou and Advanced Micro
Assuming the 90 days horizon Bank of Zhengzhou is expected to generate 1.18 times less return on investment than Advanced Micro. In addition to that, Bank of Zhengzhou is 1.11 times more volatile than Advanced Micro Devices. It trades about 0.26 of its total potential returns per unit of risk. Advanced Micro Devices is currently generating about 0.34 per unit of volatility. If you would invest 7,537 in Advanced Micro Devices on April 21, 2025 and sell it today you would earn a total of 6,063 from holding Advanced Micro Devices or generate 80.44% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Bank of Zhengzhou vs. Advanced Micro Devices
Performance |
Timeline |
Bank of Zhengzhou |
Advanced Micro Devices |
Bank of Zhengzhou and Advanced Micro Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of Zhengzhou and Advanced Micro
The main advantage of trading using opposite Bank of Zhengzhou and Advanced Micro positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of Zhengzhou position performs unexpectedly, Advanced Micro 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 Advanced Micro will offset losses from the drop in Advanced Micro's long position.Bank of Zhengzhou vs. FORWARD AIR P | Bank of Zhengzhou vs. Ryanair Holdings plc | Bank of Zhengzhou vs. LION ONE METALS | Bank of Zhengzhou vs. ANDRADA MINING LTD |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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