Correlation Between Mfs Emerging and Putnam Money
Can any of the company-specific risk be diversified away by investing in both Mfs Emerging and Putnam Money 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 Mfs Emerging and Putnam Money into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mfs Emerging Markets and Putnam Money Market, you can compare the effects of market volatilities on Mfs Emerging and Putnam Money 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 Mfs Emerging with a short position of Putnam Money. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Emerging and Putnam Money.
Diversification Opportunities for Mfs Emerging and Putnam Money
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Mfs and Putnam is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Emerging Markets and Putnam Money Market in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Money Market and Mfs Emerging 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 Mfs Emerging Markets are associated (or correlated) with Putnam Money. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Putnam Money Market has no effect on the direction of Mfs Emerging i.e., Mfs Emerging and Putnam Money go up and down completely randomly.
Pair Corralation between Mfs Emerging and Putnam Money
Assuming the 90 days horizon Mfs Emerging Markets is expected to generate 2.3 times more return on investment than Putnam Money. However, Mfs Emerging is 2.3 times more volatile than Putnam Money Market. It trades about 0.11 of its potential returns per unit of risk. Putnam Money Market is currently generating about 0.13 per unit of risk. If you would invest 1,129 in Mfs Emerging Markets on September 13, 2024 and sell it today you would earn a total of 98.00 from holding Mfs Emerging Markets or generate 8.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Flat |
Strength | Insignificant |
Accuracy | 99.6% |
Values | Daily Returns |
Mfs Emerging Markets vs. Putnam Money Market
Performance |
Timeline |
Mfs Emerging Markets |
Putnam Money Market |
Mfs Emerging and Putnam Money Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Emerging and Putnam Money
The main advantage of trading using opposite Mfs Emerging and Putnam Money positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Emerging position performs unexpectedly, Putnam Money 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 Putnam Money will offset losses from the drop in Putnam Money's long position.Mfs Emerging vs. Putnam Money Market | Mfs Emerging vs. John Hancock Money | Mfs Emerging vs. Cref Money Market | Mfs Emerging vs. Edward Jones Money |
Putnam Money vs. Vanguard Total Stock | Putnam Money vs. Vanguard 500 Index | Putnam Money vs. Vanguard Total Stock | Putnam Money vs. Vanguard Total Stock |
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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