Correlation Between Qs Large and Mfs Blended

Can any of the company-specific risk be diversified away by investing in both Qs Large and Mfs Blended 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 Qs Large and Mfs Blended into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Qs Large Cap and Mfs Blended Research, you can compare the effects of market volatilities on Qs Large and Mfs Blended 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 Qs Large with a short position of Mfs Blended. Check out your portfolio center. Please also check ongoing floating volatility patterns of Qs Large and Mfs Blended.

Diversification Opportunities for Qs Large and Mfs Blended

-0.48

Correlation Coefficient

Qs Large  Mfs Blended

Very good diversification

The 3 months correlation between LMUSX and Mfs is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding Qs Large Cap and Mfs Blended Research in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Blended Research and Qs Large 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 Qs Large Cap are associated (or correlated) with Mfs Blended. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Blended Research has no effect on the direction of Qs Large i.e., Qs Large and Mfs Blended go up and down completely randomly.

Pair Corralation between Qs Large and Mfs Blended

Assuming the 90 days horizon Qs Large Cap is expected to generate 0.79 times more return on investment than Mfs Blended. However, Qs Large Cap is 1.26 times less risky than Mfs Blended. It trades about 0.34 of its potential returns per unit of risk. Mfs Blended Research is currently generating about -0.02 per unit of risk. If you would invest  2,527  in Qs Large Cap on September 19, 2024 and sell it today you would earn a total of  96.00  from holding Qs Large Cap or generate 3.8% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Very Weak
Accuracy	100.0%
Values	Daily Returns

Qs Large Cap  vs.  Mfs Blended Research

Qs Large Cap

Risk-Adjusted Performance

16 of 100

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in Qs Large Cap are ranked lower than 16 (%) of all funds and portfolios of funds over the last 90 days. In spite of fairly weak basic indicators, Qs Large may actually be approaching a critical reversion point that can send shares even higher in January 2025.

Mfs Blended Research

Risk-Adjusted Performance

0 of 100

Insignificant

Over the last 90 days Mfs Blended Research has generated negative risk-adjusted returns adding no value to fund investors. In spite of fairly strong fundamental indicators, Mfs Blended is not utilizing all of its potentials. The current stock price disturbance, may contribute to short-term losses for the investors.

Pair Trading with Qs Large and Mfs Blended

The main advantage of trading using opposite Qs Large and Mfs Blended positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Qs Large position performs unexpectedly, Mfs Blended 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 Mfs Blended will offset losses from the drop in Mfs Blended's long position.

The idea behind Qs Large Cap and Mfs Blended Research pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.