MFS Blended Money Management Overview

BRKCX -- USA Fund  

USD 13.56  0.15  1.12%

Analysis of MFS Blended manpower and management performance can provide insight into MFS Blended stock performance. Also an employee sentiment is becoming a valuable factor that investors can use to determine the amount of risk that may be associated with MFS Blended Research future performance. Check also Trending Equities.

MFS Blended Workforce Comparison

MFS Blended Research Em Mkts Eq C is rated below average in number of employees among similar funds. The total workforce of Diversified Emerging Mkts category is currently estimated at about 11.0. MFS Blended holds roughly 1.0 in number of employees claiming about 9% of all funds under Diversified Emerging Mkts category.

MFS Blended Research Benchmark Summation

Operator
The output start index for this execution was zero with a total number of output elements of seventeen. MFS Blended Research Price Series Summation is a cross summation of MFS Blended price series and its benchmark/peer. View also all equity analysis or get more info about price series summation math operators indicator.

MFS Blended Stakeholder

Jonathan Sage Fund Manager

MFS Blended Leadership

MFS Blended Research Top Executives

  Jonathan Sage  Executive
Fund Manager
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MFS Blended Research Annual Yield

In accordance with recently published financial statements MFS Blended Research Em Mkts Eq C has Annual Yield of 0.0%. This is 100.0% lower than that of the MFS family, and 100.0% lower than that of Diversified Emerging Mkts category, The Annual Yield for all funds is 100.0% higher than the company.
  Yield 
      MFS Blended Comparables 
Small firms, start-ups, or companies with high growth potential typically do not pay out dividends or distribute a lot of their profits. These companies will have small yield. Alternatively, more established companies, ETFs, and funds that invest in bonds will have a higher yields.
Check also Trending Equities. Please also try Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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