Correlation Between Mfs Emerging and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both Mfs Emerging and Goldman Sachs 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 Goldman Sachs 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 Goldman Sachs Short, you can compare the effects of market volatilities on Mfs Emerging and Goldman Sachs 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 Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Emerging and Goldman Sachs.
Diversification Opportunities for Mfs Emerging and Goldman Sachs
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between MFS and GOLDMAN is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Emerging Markets and Goldman Sachs Short in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs Short 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 Goldman Sachs. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Goldman Sachs Short has no effect on the direction of Mfs Emerging i.e., Mfs Emerging and Goldman Sachs go up and down completely randomly.
Pair Corralation between Mfs Emerging and Goldman Sachs
Assuming the 90 days horizon Mfs Emerging Markets is expected to generate 3.59 times more return on investment than Goldman Sachs. However, Mfs Emerging is 3.59 times more volatile than Goldman Sachs Short. It trades about 0.12 of its potential returns per unit of risk. Goldman Sachs Short is currently generating about 0.2 per unit of risk. If you would invest 1,204 in Mfs Emerging Markets on September 4, 2024 and sell it today you would earn a total of 8.00 from holding Mfs Emerging Markets or generate 0.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Mfs Emerging Markets vs. Goldman Sachs Short
Performance |
Timeline |
Mfs Emerging Markets |
Goldman Sachs Short |
Mfs Emerging and Goldman Sachs Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Emerging and Goldman Sachs
The main advantage of trading using opposite Mfs Emerging and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Emerging position performs unexpectedly, Goldman Sachs 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 Goldman Sachs will offset losses from the drop in Goldman Sachs' long position.Mfs Emerging vs. Mfs Prudent Investor | Mfs Emerging vs. Mfs Prudent Investor | Mfs Emerging vs. Mfs Prudent Investor | Mfs Emerging vs. Mfs Prudent Investor |
Goldman Sachs vs. Goldman Sachs Clean | Goldman Sachs vs. Goldman Sachs Clean | Goldman Sachs vs. Goldman Sachs Clean | Goldman Sachs vs. Goldman Sachs Clean |
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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