Baillie Gifford Health Fund Return On Equity
BGHBX Fund | USD 5.82 0.02 0.34% |
Baillie Gifford Health fundamentals help investors to digest information that contributes to Baillie Gifford's financial success or failures. It also enables traders to predict the movement of Baillie Mutual Fund. The fundamental analysis module provides a way to measure Baillie Gifford's intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Baillie Gifford mutual fund.
Baillie |
Baillie Gifford Health Mutual Fund Return On Equity Analysis
Baillie Gifford's Return on Equity or ROE tells company stockholders how effectually their money is being utilized or reinvested. It is a useful ratio when analyzing company profitability or the management effectiveness given the capital invested by the shareholders. ROE shows how efficiently a company utilizes investments to generate income.
For most industries, Return on Equity between 10% and 30% are considered desirable to provide dividends to owners and have funds for the future growth of the company. Investors should be very careful using ROE as the only efficiency indicator because ROE can be high if a company is heavily leveraged.
Competition |
Based on the latest financial disclosure, Baillie Gifford Health has a Return On Equity of 0.0. This indicator is about the same for the Baillie Gifford Funds average (which is currently at 0.0) family and about the same as Health (which currently averages 0.0) category. This indicator is about the same for all United States funds average (which is currently at 0.0).
Did you try this?
Run AI Portfolio Architect Now
AI Portfolio ArchitectUse AI to generate optimal portfolios and find profitable investment opportunities |
All Next | Launch Module |
Baillie Fundamentals
Year To Date Return | 0.34 % | ||||
One Year Return | 7.58 % | ||||
Net Asset | 15.42 M |
About Baillie Gifford Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Baillie Gifford Health's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Baillie Gifford using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Baillie Gifford Health based on its fundamental data. In general, a quantitative approach, as applied to this mutual fund, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
Please read more on our fundamental analysis page.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Other Information on Investing in Baillie Mutual Fund
Baillie Gifford financial ratios help investors to determine whether Baillie Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Baillie with respect to the benefits of owning Baillie Gifford security.
Balance Of Power Check stock momentum by analyzing Balance Of Power indicator and other technical ratios | |
Theme Ratings Determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
Cryptocurrency Center Build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm |