Correlation Between Santander Bank and De Grey
Can any of the company-specific risk be diversified away by investing in both Santander Bank and De Grey 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 Santander Bank and De Grey into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Santander Bank Polska and De Grey Mining, you can compare the effects of market volatilities on Santander Bank and De Grey 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 Santander Bank with a short position of De Grey. Check out your portfolio center. Please also check ongoing floating volatility patterns of Santander Bank and De Grey.
Diversification Opportunities for Santander Bank and De Grey
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Santander and DGD is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Santander Bank Polska and De Grey Mining in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on De Grey Mining and Santander Bank 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 Santander Bank Polska are associated (or correlated) with De Grey. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of De Grey Mining has no effect on the direction of Santander Bank i.e., Santander Bank and De Grey go up and down completely randomly.
Pair Corralation between Santander Bank and De Grey
Assuming the 90 days horizon Santander Bank is expected to generate 3.67 times less return on investment than De Grey. In addition to that, Santander Bank is 1.27 times more volatile than De Grey Mining. It trades about 0.1 of its total potential returns per unit of risk. De Grey Mining is currently generating about 0.47 per unit of volatility. If you would invest 104.00 in De Grey Mining on October 22, 2024 and sell it today you would earn a total of 13.00 from holding De Grey Mining or generate 12.5% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 94.12% |
| Values | Daily Returns |
Santander Bank Polska vs. De Grey Mining
Performance |
| Timeline |
| Santander Bank Polska |
| De Grey Mining |
Santander Bank and De Grey Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Santander Bank and De Grey
The main advantage of trading using opposite Santander Bank and De Grey positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Santander Bank position performs unexpectedly, De Grey 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 De Grey will offset losses from the drop in De Grey's long position.| Santander Bank vs. De Grey Mining | Santander Bank vs. SILVER BULLET DATA | Santander Bank vs. Linedata Services SA | Santander Bank vs. FIREWEED METALS P |
| De Grey vs. Siemens Healthineers AG | De Grey vs. Cleanaway Waste Management | De Grey vs. Bausch Health Companies | De Grey vs. Ultra Clean Holdings |
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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