Correlation Between ETRACS 2xMonthly and Columbia
Can any of the company-specific risk be diversified away by investing in both ETRACS 2xMonthly and Columbia 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 ETRACS 2xMonthly and Columbia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ETRACS 2xMonthly Pay and Columbia EM Core, you can compare the effects of market volatilities on ETRACS 2xMonthly and Columbia 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 ETRACS 2xMonthly with a short position of Columbia. Check out your portfolio center. Please also check ongoing floating volatility patterns of ETRACS 2xMonthly and Columbia.
Diversification Opportunities for ETRACS 2xMonthly and Columbia
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between ETRACS and Columbia is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding ETRACS 2xMonthly Pay and Columbia EM Core in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Columbia EM Core and ETRACS 2xMonthly 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 ETRACS 2xMonthly Pay are associated (or correlated) with Columbia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Columbia EM Core has no effect on the direction of ETRACS 2xMonthly i.e., ETRACS 2xMonthly and Columbia go up and down completely randomly.
Pair Corralation between ETRACS 2xMonthly and Columbia
Given the investment horizon of 90 days ETRACS 2xMonthly Pay is expected to under-perform the Columbia. In addition to that, ETRACS 2xMonthly is 1.52 times more volatile than Columbia EM Core. It trades about -0.03 of its total potential returns per unit of risk. Columbia EM Core is currently generating about -0.04 per unit of volatility. If you would invest 3,218 in Columbia EM Core on September 12, 2024 and sell it today you would lose (78.00) from holding Columbia EM Core or give up 2.42% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
ETRACS 2xMonthly Pay vs. Columbia EM Core
Performance |
Timeline |
ETRACS 2xMonthly Pay |
Columbia EM Core |
ETRACS 2xMonthly and Columbia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ETRACS 2xMonthly and Columbia
The main advantage of trading using opposite ETRACS 2xMonthly and Columbia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ETRACS 2xMonthly position performs unexpectedly, Columbia 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 Columbia will offset losses from the drop in Columbia's long position.ETRACS 2xMonthly vs. ProShares Ultra Euro | ETRACS 2xMonthly vs. ProShares UltraShort Yen | ETRACS 2xMonthly vs. ProShares Ultra Telecommunications | ETRACS 2xMonthly vs. ProShares Ultra Consumer |
Columbia vs. iShares MSCI Emerging | Columbia vs. Hartford Multifactor Emerging | Columbia vs. SPDR MSCI Emerging | Columbia vs. FlexShares Morningstar Emerging |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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