Correlation Between Hartford Municipal and Cm Commodity
Can any of the company-specific risk be diversified away by investing in both Hartford Municipal and Cm Commodity 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 Hartford Municipal and Cm Commodity into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between The Hartford Municipal and Cm Modity Index, you can compare the effects of market volatilities on Hartford Municipal and Cm Commodity 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 Hartford Municipal with a short position of Cm Commodity. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hartford Municipal and Cm Commodity.
Diversification Opportunities for Hartford Municipal and Cm Commodity
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between Hartford and COMIX is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding The Hartford Municipal and Cm Modity Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cm Modity Index and Hartford Municipal 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 The Hartford Municipal are associated (or correlated) with Cm Commodity. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cm Modity Index has no effect on the direction of Hartford Municipal i.e., Hartford Municipal and Cm Commodity go up and down completely randomly.
Pair Corralation between Hartford Municipal and Cm Commodity
Assuming the 90 days horizon Hartford Municipal is expected to generate 1.32 times less return on investment than Cm Commodity. But when comparing it to its historical volatility, The Hartford Municipal is 4.15 times less risky than Cm Commodity. It trades about 0.09 of its potential returns per unit of risk. Cm Modity Index is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 6,780 in Cm Modity Index on September 1, 2024 and sell it today you would earn a total of 223.00 from holding Cm Modity Index or generate 3.29% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
The Hartford Municipal vs. Cm Modity Index
Performance |
| Timeline |
| The Hartford Municipal |
| Cm Modity Index |
Hartford Municipal and Cm Commodity Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hartford Municipal and Cm Commodity
The main advantage of trading using opposite Hartford Municipal and Cm Commodity positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hartford Municipal position performs unexpectedly, Cm Commodity 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 Cm Commodity will offset losses from the drop in Cm Commodity's long position.| Hartford Municipal vs. Great West Real Estate | Hartford Municipal vs. Deutsche Real Estate | Hartford Municipal vs. Msif Real Estate | Hartford Municipal vs. Simt Real Estate |
| Cm Commodity vs. Unconstrained Emerging Markets | Cm Commodity vs. Unconstrained Emerging Markets | Cm Commodity vs. Unconstrained Emerging Markets | Cm Commodity vs. Emerging Markets Fund |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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