-
1 Comment
Azimut Holding S.p.A is currently in a long term uptrend where the price is trading 10.7% above its 200 day moving average.
From a valuation standpoint, the stock is 93.5% cheaper than other stocks from the Financial Services sector with a price to sales ratio of 2.9.
Azimut Holding S.p.A's total revenue sank by 28.3% to $213M since the same quarter in the previous year.
Its net income has dropped by 29.4% to $87M since the same quarter in the previous year.
Finally, its free cash flow grew by 77.2% to $137M since the same quarter in the previous year.
Based on the above factors, Azimut Holding S.p.A gets an overall score of 3/5.
| Exchange | F |
|---|---|
| CurrencyCode | EUR |
| ISIN | IT0003261697 |
| Sector | Financial Services |
| Industry | Asset Management |
| Market Cap | 5B |
|---|---|
| PE Ratio | 9.88 |
| Target Price | None |
| Dividend Yield | 5.6% |
| Beta | 0.97 |
Azimut Holding S.p.A. provides asset management and advisory solutions in Italy, Europe, the Middle East, the Americas, and the Asia-Pacific. It offers public and private markets, discretionary portfolio management, and token and digital asset solutions; advisory services; corporate investment banking and fintech solutions; mutual funds harmonized with the UCITS directive; alternative investment funds and open pension funds; and individual management of investment portfolios on behalf of third parties. The company also provides private insurance, unit linked insurance plans, and optional coverage; and pensions for individuals and companies. Azimut Holding S.p.A. was incorporated in 1990 and is headquartered in Milan, Italy.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for HDB.F 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 2026
