Oppenheimer Gbl Alloc Fund Chance Of Distress
| QVGIX Fund | USD 19.90 0.02 0.10% |
Oppenheimer |
Oppenheimer Gbl Alloc Mutual Fund chance of distress Analysis
Oppenheimer Gbl's Probability Of Bankruptcy is a relative measure of the likelihood of financial distress. For stocks, the Probability Of Bankruptcy is the normalized value of Z-Score. For funds and ETFs, it is derived from a multi-factor model developed by Macroaxis. The score is used to predict the probability of a firm or a fund experiencing financial distress within the next 24 months. Unlike Z-Score, Probability Of Bankruptcy is the value between 0 and 100, indicating the firm's actual probability it will be financially distressed in the next 2 fiscal years.
More About Probability Of Bankruptcy | All Equity Analysis
Probability Of Bankruptcy | = | Normalized | | Z-Score |
Current Oppenheimer Gbl Probability Of Bankruptcy | Less than 22% |
Most of Oppenheimer Gbl's fundamental indicators, such as Probability Of Bankruptcy, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, Oppenheimer Gbl Alloc is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.
Our calculation of Oppenheimer Gbl probability of bankruptcy is based on Altman Z-Score and Piotroski F-Score, but not limited to these measures. To be applied to a broader range of industries and markets, we use several other techniques to enhance the accuracy of predicting Oppenheimer Gbl odds of financial distress. These include financial statement analysis, different types of price predictions, earning estimates, analysis consensus, and basic intrinsic valuation. Please use the options below to get a better understanding of different measures that drive the calculation of Oppenheimer Gbl Alloc financial health.
The Probability of Bankruptcy SHOULD NOT be confused with the actual chance of a company to file for chapter 7, 11, 12, or 13 bankruptcy protection. Macroaxis simply defines Financial Distress as an operational condition where a company is having difficulty meeting its current financial obligations towards its creditors or delivering on the expectations of its investors. Macroaxis derives these conditions daily from both public financial statements as well as analysis of stock prices reacting to market conditions or economic downturns, including short-term and long-term historical volatility. Other factors taken into account include analysis of liquidity, revenue patterns, R&D expenses, and commitments, as well as public headlines and social sentiment.
| Competition |
Based on the latest financial disclosure, Oppenheimer Gbl Alloc has a Probability Of Bankruptcy of 22.0%. This is much higher than that of the Invesco family and significantly higher than that of the World Allocation category. The probability of bankruptcy for all United States funds is notably lower than that of the firm.
Oppenheimer Probability Of Bankruptcy Peer Comparison
Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Oppenheimer Gbl's direct or indirect competition against its Probability Of Bankruptcy to detect undervalued stocks with similar characteristics or determine the mutual funds which would be a good addition to a portfolio. Peer analysis of Oppenheimer Gbl could also be used in its relative valuation, which is a method of valuing Oppenheimer Gbl by comparing valuation metrics of similar companies.Oppenheimer Gbl is currently under evaluation in probability of bankruptcy among similar funds.
Oppenheimer Fundamentals
| Price To Earning | 18.96 X | ||||
| Price To Book | 2.33 X | ||||
| Price To Sales | 1.63 X | ||||
| Total Asset | 916.68 M | ||||
| Annual Yield | 0.02 % | ||||
| Year To Date Return | 8.71 % | ||||
| One Year Return | 13.17 % | ||||
| Three Year Return | 1.51 % | ||||
| Five Year Return | 5.94 % | ||||
| Ten Year Return | 5.11 % | ||||
| Net Asset | 1.07 B | ||||
| Last Dividend Paid | 0.39 | ||||
| Cash Position Weight | 13.19 % | ||||
| Equity Positions Weight | 53.97 % | ||||
| Bond Positions Weight | 0.45 % |
About Oppenheimer Gbl Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Oppenheimer Gbl Alloc's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Oppenheimer Gbl using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Oppenheimer Gbl Alloc 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 Oppenheimer Mutual Fund
Oppenheimer Gbl financial ratios help investors to determine whether Oppenheimer 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 Oppenheimer with respect to the benefits of owning Oppenheimer Gbl security.
| 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 | |
| Transaction History View history of all your transactions and understand their impact on performance | |
| Portfolio Backtesting Avoid under-diversification and over-optimization by backtesting your portfolios |