-
1 Comment
Clipper Realty Inc is currently in a long term uptrend where the price is trading 0.4% above its 200 day moving average.
From a valuation standpoint, the stock is 87.9% cheaper than other stocks from the Real Estate sector with a price to sales ratio of 1.2.
Clipper Realty Inc's total revenue rose by 3.3% to $32M since the same quarter in the previous year.
Its net income has increased by 9.1% to $-974K since the same quarter in the previous year.
Finally, its free cash flow grew by 116.6% to $6M since the same quarter in the previous year.
Based on the above factors, Clipper Realty Inc gets an overall score of 5/5.
Industry | REIT - Residential |
---|---|
Exchange | NYSE |
CurrencyCode | USD |
ISIN | US18885T3068 |
Sector | Real Estate |
Beta | 0.98 |
---|---|
PE Ratio | None |
Target Price | 7.5 |
Dividend Yield | 10.% |
Market Cap | 155M |
Clipper Realty Inc. (the "Company" or "we") is a self-administered and self-managed real estate company that acquires, owns, manages, operates and repositions multifamily residential and commercial properties in the New York metropolitan area, with a current portfolio in Manhattan and Brooklyn. Our primary focus is to own, manage and operate our portfolio and to acquire and reposition additional multifamily residential and commercial properties in the New York metropolitan area. The Company has been organized and operates in conformity with the requirements for qualification and taxation as a real estate investment trust ("REIT") under the U.S. federal income tax law and elected to be treated as a REIT commencing with the taxable year ended December 31, 2015.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for CLPR 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