Correlation Between US Bancorp and International Business
Can any of the company-specific risk be diversified away by investing in both US Bancorp and International Business 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 US Bancorp and International Business into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between US Bancorp and International Business Machines, you can compare the effects of market volatilities on US Bancorp and International Business 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 US Bancorp with a short position of International Business. Check out your portfolio center. Please also check ongoing floating volatility patterns of US Bancorp and International Business.
Diversification Opportunities for US Bancorp and International Business
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between USB and International is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding US Bancorp and International Business Machine in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on International Business and US Bancorp 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 US Bancorp are associated (or correlated) with International Business. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of International Business has no effect on the direction of US Bancorp i.e., US Bancorp and International Business go up and down completely randomly.
Pair Corralation between US Bancorp and International Business
Assuming the 90 days trading horizon US Bancorp is expected to generate 1.06 times more return on investment than International Business. However, US Bancorp is 1.06 times more volatile than International Business Machines. It trades about -0.04 of its potential returns per unit of risk. International Business Machines is currently generating about -0.22 per unit of risk. If you would invest 101,550 in US Bancorp on September 27, 2024 and sell it today you would lose (1,100) from holding US Bancorp or give up 1.08% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
US Bancorp vs. International Business Machine
Performance |
Timeline |
US Bancorp |
International Business |
US Bancorp and International Business Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with US Bancorp and International Business
The main advantage of trading using opposite US Bancorp and International Business positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if US Bancorp position performs unexpectedly, International Business 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 International Business will offset losses from the drop in International Business' long position.US Bancorp vs. Southern Copper | US Bancorp vs. Monster Beverage Corp | US Bancorp vs. BHP Group | US Bancorp vs. Prudential Financial |
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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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