Correlation Between Champlain Small and Calamos Market
Can any of the company-specific risk be diversified away by investing in both Champlain Small and Calamos Market 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 Champlain Small and Calamos Market into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Champlain Small and Calamos Market Neutral, you can compare the effects of market volatilities on Champlain Small and Calamos Market 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 Champlain Small with a short position of Calamos Market. Check out your portfolio center. Please also check ongoing floating volatility patterns of Champlain Small and Calamos Market.
Diversification Opportunities for Champlain Small and Calamos Market
-0.3 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Champlain and Calamos is -0.3. Overlapping area represents the amount of risk that can be diversified away by holding Champlain Small and Calamos Market Neutral in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Calamos Market Neutral and Champlain Small 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 Champlain Small are associated (or correlated) with Calamos Market. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Calamos Market Neutral has no effect on the direction of Champlain Small i.e., Champlain Small and Calamos Market go up and down completely randomly.
Pair Corralation between Champlain Small and Calamos Market
Assuming the 90 days horizon Champlain Small is expected to under-perform the Calamos Market. In addition to that, Champlain Small is 6.39 times more volatile than Calamos Market Neutral. It trades about -0.11 of its total potential returns per unit of risk. Calamos Market Neutral is currently generating about 0.1 per unit of volatility. If you would invest 1,522 in Calamos Market Neutral on December 24, 2024 and sell it today you would earn a total of 16.00 from holding Calamos Market Neutral or generate 1.05% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Champlain Small vs. Calamos Market Neutral
Performance |
Timeline |
Champlain Small |
Calamos Market Neutral |
Champlain Small and Calamos Market Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Champlain Small and Calamos Market
The main advantage of trading using opposite Champlain Small and Calamos Market positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Champlain Small position performs unexpectedly, Calamos Market 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 Calamos Market will offset losses from the drop in Calamos Market's long position.Champlain Small vs. The Hartford Midcap | Champlain Small vs. Mfs Emerging Markets | Champlain Small vs. Wells Fargo Special | Champlain Small vs. Washington Mutual Investors |
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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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