Correlation Between Kaiser Aluminum and Commonwealth Bank
Can any of the company-specific risk be diversified away by investing in both Kaiser Aluminum and Commonwealth Bank 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 Kaiser Aluminum and Commonwealth Bank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kaiser Aluminum and Commonwealth Bank of, you can compare the effects of market volatilities on Kaiser Aluminum and Commonwealth Bank 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 Kaiser Aluminum with a short position of Commonwealth Bank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kaiser Aluminum and Commonwealth Bank.
Diversification Opportunities for Kaiser Aluminum and Commonwealth Bank
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Kaiser and Commonwealth is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Kaiser Aluminum and Commonwealth Bank of in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Commonwealth Bank and Kaiser Aluminum 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 Kaiser Aluminum are associated (or correlated) with Commonwealth Bank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Commonwealth Bank has no effect on the direction of Kaiser Aluminum i.e., Kaiser Aluminum and Commonwealth Bank go up and down completely randomly.
Pair Corralation between Kaiser Aluminum and Commonwealth Bank
Assuming the 90 days trading horizon Kaiser Aluminum is expected to generate 1.82 times more return on investment than Commonwealth Bank. However, Kaiser Aluminum is 1.82 times more volatile than Commonwealth Bank of. It trades about 0.37 of its potential returns per unit of risk. Commonwealth Bank of is currently generating about 0.09 per unit of risk. If you would invest 4,599 in Kaiser Aluminum on April 20, 2025 and sell it today you would earn a total of 2,951 from holding Kaiser Aluminum or generate 64.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Kaiser Aluminum vs. Commonwealth Bank of
Performance |
Timeline |
Kaiser Aluminum |
Commonwealth Bank |
Kaiser Aluminum and Commonwealth Bank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kaiser Aluminum and Commonwealth Bank
The main advantage of trading using opposite Kaiser Aluminum and Commonwealth Bank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kaiser Aluminum position performs unexpectedly, Commonwealth Bank 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 Commonwealth Bank will offset losses from the drop in Commonwealth Bank's long position.Kaiser Aluminum vs. Hellenic Telecommunications Organization | Kaiser Aluminum vs. Rogers Communications | Kaiser Aluminum vs. Iridium Communications | Kaiser Aluminum vs. Chunghwa Telecom Co |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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