Correlation Between Killam Apartment and First Capital
Can any of the company-specific risk be diversified away by investing in both Killam Apartment and First Capital 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 Killam Apartment and First Capital into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Killam Apartment Real and First Capital Real, you can compare the effects of market volatilities on Killam Apartment and First Capital 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 Killam Apartment with a short position of First Capital. Check out your portfolio center. Please also check ongoing floating volatility patterns of Killam Apartment and First Capital.
Diversification Opportunities for Killam Apartment and First Capital
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Killam and First is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Killam Apartment Real and First Capital Real in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First Capital Real and Killam Apartment 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 Killam Apartment Real are associated (or correlated) with First Capital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First Capital Real has no effect on the direction of Killam Apartment i.e., Killam Apartment and First Capital go up and down completely randomly.
Pair Corralation between Killam Apartment and First Capital
Assuming the 90 days trading horizon Killam Apartment Real is expected to under-perform the First Capital. In addition to that, Killam Apartment is 1.18 times more volatile than First Capital Real. It trades about -0.31 of its total potential returns per unit of risk. First Capital Real is currently generating about -0.1 per unit of volatility. If you would invest 1,836 in First Capital Real on September 13, 2024 and sell it today you would lose (92.00) from holding First Capital Real or give up 5.01% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Killam Apartment Real vs. First Capital Real
Performance |
Timeline |
Killam Apartment Real |
First Capital Real |
Killam Apartment and First Capital Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Killam Apartment and First Capital
The main advantage of trading using opposite Killam Apartment and First Capital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Killam Apartment position performs unexpectedly, First Capital 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 First Capital will offset losses from the drop in First Capital's long position.Killam Apartment vs. Canadian Apartment Properties | Killam Apartment vs. Granite Real Estate | Killam Apartment vs. Choice Properties Real | Killam Apartment vs. HR Real Estate |
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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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