-
1 Comment
MFS High Income Municipal Trust is currently in a long term uptrend where the price is trading 6.5% above its 200 day moving average.
From a valuation standpoint, the stock is 1965.3% more expensive than other stocks from the Financial Services sector with a price to sales ratio of 187.2.
MFS High Income Municipal Trust's total revenue sank by 9.6% to $6M since the same quarter in the previous year.
Its net income has dropped by 363.1% to $-14M since the same quarter in the previous year.
Finally, its free cash flow fell by 46.2% to $2M since the same quarter in the previous year.
Based on the above factors, MFS High Income Municipal Trust gets an overall score of 1/5.
| Exchange | NYSE |
|---|---|
| CurrencyCode | USD |
| ISIN | US59318D1046 |
| Sector | Financial Services |
| Industry | Asset Management |
| Beta | 0.66 |
|---|---|
| Market Cap | 109M |
| PE Ratio | 6.65 |
| Target Price | None |
| Dividend Yield | 5.6% |
MFS High Income Municipal Trust is a close ended fixed income mutual fund launched and managed by Massachusetts Financial Services Company. The fund invests in the fixed income markets. It primarily invests in municipal bonds and local general obligations of various sectors, such as multifamily, hospitals, care retirement, and investor-owned utilities. The fund benchmarks the performance of its portfolio against Barclays Municipal Bond Index. It was formerly known as Colonial High Income Municipal Trust. MFS High Income Municipal Trust was formed on February 17, 1989 and is domiciled in United States.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for CXE using our backtest tool. PyInvesting provides the backtesting software for you to backtest your investment strategy. Our backtest software is written using Python code and allows you to backtest stock, backtest etf, backtest options, backtest crypto and backtest forex online. Our backtesting Python framework is highly robust and gives you a realistic simulation of how your strategy would have performed in the past using backtest data.
© PyInvesting 2025
