Correlation Between Rocky Mountain and Bank of Nova Scotia
Can any of the company-specific risk be diversified away by investing in both Rocky Mountain and Bank of Nova Scotia 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 Rocky Mountain and Bank of Nova Scotia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Rocky Mountain Liquor and Bank of Nova, you can compare the effects of market volatilities on Rocky Mountain and Bank of Nova Scotia 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 Rocky Mountain with a short position of Bank of Nova Scotia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Rocky Mountain and Bank of Nova Scotia.
Diversification Opportunities for Rocky Mountain and Bank of Nova Scotia
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Rocky and Bank is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Rocky Mountain Liquor and Bank of Nova in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of Nova Scotia and Rocky Mountain 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 Rocky Mountain Liquor are associated (or correlated) with Bank of Nova Scotia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of Nova Scotia has no effect on the direction of Rocky Mountain i.e., Rocky Mountain and Bank of Nova Scotia go up and down completely randomly.
Pair Corralation between Rocky Mountain and Bank of Nova Scotia
Assuming the 90 days horizon Rocky Mountain Liquor is expected to under-perform the Bank of Nova Scotia. In addition to that, Rocky Mountain is 5.96 times more volatile than Bank of Nova. It trades about -0.02 of its total potential returns per unit of risk. Bank of Nova is currently generating about 0.1 per unit of volatility. If you would invest 6,521 in Bank of Nova on September 20, 2024 and sell it today you would earn a total of 1,169 from holding Bank of Nova or generate 17.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 99.47% |
Values | Daily Returns |
Rocky Mountain Liquor vs. Bank of Nova
Performance |
Timeline |
Rocky Mountain Liquor |
Bank of Nova Scotia |
Rocky Mountain and Bank of Nova Scotia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Rocky Mountain and Bank of Nova Scotia
The main advantage of trading using opposite Rocky Mountain and Bank of Nova Scotia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Rocky Mountain position performs unexpectedly, Bank of Nova Scotia 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 Bank of Nova Scotia will offset losses from the drop in Bank of Nova Scotia's long position.Rocky Mountain vs. HPQ Silicon Resources | Rocky Mountain vs. Major Drilling Group | Rocky Mountain vs. 2028 Investment Grade | Rocky Mountain vs. Partners Value Investments |
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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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