Correlation Between Bank of America and Quaker Chemical
Can any of the company-specific risk be diversified away by investing in both Bank of America and Quaker Chemical 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 America and Quaker Chemical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Verizon Communications and Quaker Chemical, you can compare the effects of market volatilities on Bank of America and Quaker Chemical 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 America with a short position of Quaker Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Quaker Chemical.
Diversification Opportunities for Bank of America and Quaker Chemical
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Bank and Quaker is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Verizon Communications and Quaker Chemical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Quaker Chemical and Bank of America 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 Verizon Communications are associated (or correlated) with Quaker Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Quaker Chemical has no effect on the direction of Bank of America i.e., Bank of America and Quaker Chemical go up and down completely randomly.
Pair Corralation between Bank of America and Quaker Chemical
Assuming the 90 days trading horizon Verizon Communications is expected to generate 0.58 times more return on investment than Quaker Chemical. However, Verizon Communications is 1.74 times less risky than Quaker Chemical. It trades about 0.11 of its potential returns per unit of risk. Quaker Chemical is currently generating about 0.0 per unit of risk. If you would invest 3,807 in Verizon Communications on September 4, 2024 and sell it today you would earn a total of 374.00 from holding Verizon Communications or generate 9.82% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Verizon Communications vs. Quaker Chemical
Performance |
Timeline |
Verizon Communications |
Quaker Chemical |
Bank of America and Quaker Chemical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of America and Quaker Chemical
The main advantage of trading using opposite Bank of America and Quaker Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Quaker Chemical 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 Quaker Chemical will offset losses from the drop in Quaker Chemical's long position.Bank of America vs. Lifeway Foods | Bank of America vs. PARKEN Sport Entertainment | Bank of America vs. Flutter Entertainment PLC | Bank of America vs. REMEDY ENTERTAINMENT OYJ |
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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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