Correlation Between Banque Cantonale and Metall Zug
Can any of the company-specific risk be diversified away by investing in both Banque Cantonale and Metall Zug 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 Banque Cantonale and Metall Zug into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Banque Cantonale du and Metall Zug AG, you can compare the effects of market volatilities on Banque Cantonale and Metall Zug 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 Banque Cantonale with a short position of Metall Zug. Check out your portfolio center. Please also check ongoing floating volatility patterns of Banque Cantonale and Metall Zug.
Diversification Opportunities for Banque Cantonale and Metall Zug
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Banque and Metall is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding Banque Cantonale du and Metall Zug AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Metall Zug AG and Banque Cantonale 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 Banque Cantonale du are associated (or correlated) with Metall Zug. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Metall Zug AG has no effect on the direction of Banque Cantonale i.e., Banque Cantonale and Metall Zug go up and down completely randomly.
Pair Corralation between Banque Cantonale and Metall Zug
Assuming the 90 days trading horizon Banque Cantonale du is expected to generate 0.22 times more return on investment than Metall Zug. However, Banque Cantonale du is 4.59 times less risky than Metall Zug. It trades about -0.19 of its potential returns per unit of risk. Metall Zug AG is currently generating about -0.1 per unit of risk. If you would invest 11,250 in Banque Cantonale du on September 4, 2024 and sell it today you would lose (200.00) from holding Banque Cantonale du or give up 1.78% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.45% |
| Values | Daily Returns |
Banque Cantonale du vs. Metall Zug AG
Performance |
| Timeline |
| Banque Cantonale |
| Metall Zug AG |
Banque Cantonale and Metall Zug Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Banque Cantonale and Metall Zug
The main advantage of trading using opposite Banque Cantonale and Metall Zug positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Banque Cantonale position performs unexpectedly, Metall Zug 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 Metall Zug will offset losses from the drop in Metall Zug's long position.| Banque Cantonale vs. Metall Zug AG | Banque Cantonale vs. Swiss Steel Holding | Banque Cantonale vs. Luzerner Kantonalbank AG | Banque Cantonale vs. Glarner Kantonalbank |
| Metall Zug vs. Bucher Industries AG | Metall Zug vs. Burckhardt Compression | Metall Zug vs. Also Holding AG | Metall Zug vs. Emmi AG |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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