-
1 Comment
AECOM is currently in a long term uptrend where the price is trading 9.9% above its 200 day moving average.
From a valuation standpoint, the stock is 98.5% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.8.
AECOM's total revenue rose by 2.4% to $3B since the same quarter in the previous year.
Its net income has dropped by 35.7% to $26M since the same quarter in the previous year.
Finally, its free cash flow grew by 90.0% to $-24M since the same quarter in the previous year.
Based on the above factors, AECOM gets an overall score of 4/5.
Sector | Industrials |
---|---|
Industry | Engineering & Construction |
Exchange | NYSE |
CurrencyCode | USD |
ISIN | US00766T1007 |
Market Cap | 13B |
---|---|
PE Ratio | 22.48 |
Beta | 1.04 |
Target Price | 116.5 |
Dividend Yield | 1.0% |
AECOM, together with its subsidiaries, provides professional infrastructure consulting services for governments, businesses, and organizations worldwide. It operates in three segments: Americas, International, and AECOM Capital. The company offers advisory, planning, consulting, architectural and engineering design, construction and program management, and investment and development services to public and private clients. It is also involved in the investment and development of real estate projects. The company serves transportation, water, facilities, environmental, and energy sectors. The company was formerly known as AECOM Technology Corporation and changed its name to AECOM in January 2015. AECOM was incorporated in 1980 and is headquartered in Dallas, Texas.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for ACM 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