-
1 Comment
Monro, Inc is currently in a long term uptrend where the price is trading 5.8% above its 200 day moving average.
From a valuation standpoint, the stock is 97.8% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 2.0.
Monro, Inc's total revenue sank by 99.9% to $285K since the same quarter in the previous year.
Its net income has dropped by 64.6% to $7M since the same quarter in the previous year.
Finally, its free cash flow grew by 426.9% to $144M since the same quarter in the previous year.
Based on the above factors, Monro, Inc gets an overall score of 3/5.
Exchange | NASDAQ |
---|---|
CurrencyCode | USD |
Industry | Auto Parts |
ISIN | US6102361010 |
Sector | Consumer Cyclical |
PE Ratio | 22.69 |
---|---|
Market Cap | 437M |
Dividend Yield | 7.7% |
Beta | 1.1 |
Target Price | 19.75 |
Monro, Inc. engages in the operation of retail tire and automotive repair stores in the United States. It offers replacement tires and tire related services, automotive undercar repair services, and routine maintenance services primarily to passenger cars, light trucks, and vans. The company also provides other products and services for brakes; mufflers and exhaust systems; and steering, drive train, suspension, and wheel alignment. In addition, it operates its stores under the Monro Auto Service and Tire Centers, Tire Choice Auto Service Centers, Mr. Tire Auto Service Centers, Car-X Tire & Auto, Tire Warehouse Tires for Less, Ken Towery's Tire & Auto Care, Mountain View Tire & Auto Service, and Tire Barn Warehouse brand names. The company was founded in 1957 and is headquartered in Rochester, New York.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for MNRO 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