-
1 Comment
Firm Capital Apartment Real Estate Investment Trust is currently in a long term uptrend where the price is trading 31.5% above its 200 day moving average.
From a valuation standpoint, the stock is 77.7% cheaper than other stocks from the Real Estate sector with a price to sales ratio of 12.6.
Firm Capital Apartment Real Estate Investment Trust's total revenue sank by 2.5% to $1M since the same quarter in the previous year.
Its net income has dropped by 29.7% to $2M since the same quarter in the previous year.
Finally, its free cash flow fell by 152.3% to $-2M since the same quarter in the previous year.
Based on the above factors, Firm Capital Apartment Real Estate Investment Trust gets an overall score of 2/5.
| Exchange | V |
|---|---|
| CurrencyCode | CAD |
| ISIN | None |
| Sector | Real Estate |
| Industry | REIT - Residential |
| Market Cap | 34M |
|---|---|
| PE Ratio | None |
| Target Price | 7.14 |
| Dividend Yield | 0.0% |
| Beta | 0.5 |
Firm Capital Apartment Real Estate Investment Trust (the "Trust") is a U.S. focused real estate investment trust that pursues multi-residential income producing real estate and related debt investments on both a wholly owned and joint venture basis. The Trust has ownership interests in a total of 1,756 apartment units diversely located in Florida, Connecticut, Texas, New York, New Jersey, Georgia and Maryland. The Trust trades on the TSXV exchange under the symbols FCA.U and FCA.UN. The registered office of the Trust and its head office operations are located at 163 Cartwright Avenue, Toronto, Ontario, M6A 1V5. The Trust is domiciled in Canada.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for FCA-UN.V 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
