Data Patterns Limited Stock Probability Of Bankruptcy
DATAPATTNS | 2,358 45.45 1.97% |
Data | Probability Of Bankruptcy |
Data Patterns Limited Company probability of financial unrest Analysis
Data Patterns' 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 Data Patterns Probability Of Bankruptcy | Less than 9% |
Most of Data Patterns' 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, Data Patterns Limited is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.
Our calculation of Data Patterns 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 Data Patterns 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 Data Patterns Limited 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, Data Patterns Limited has a Probability Of Bankruptcy of 9.0%. This is 78.86% lower than that of the Aerospace & Defense sector and 75.12% lower than that of the Industrials industry. The probability of bankruptcy for all India stocks is 77.4% higher than that of the company.
Data Probability Of Bankruptcy Peer Comparison
Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Data Patterns' direct or indirect competition against its Probability Of Bankruptcy to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Data Patterns could also be used in its relative valuation, which is a method of valuing Data Patterns by comparing valuation metrics of similar companies.Data Patterns is currently under evaluation in probability of bankruptcy category among its peers.
Data Patterns Main Bankruptcy Drivers
2019 | 2020 | 2021 | 2022 | 2023 | 2024 (projected) | ||
Net Debt | 649.8M | 283.7M | (1.5B) | (2.1B) | (846.4M) | (804.1M) | |
Total Current Liabilities | 1.2B | 717M | 1.0B | 1.3B | 3.5B | 3.7B | |
Non Current Liabilities Total | 251.2M | 489.0M | 287M | 1.4B | 173.5M | 164.8M | |
Total Assets | 3.0B | 3.3B | 7.1B | 14.3B | 16.9B | 8.7B | |
Total Current Assets | 2.2B | 2.6B | 5.2B | 12.4B | 14.0B | 7.0B | |
Total Cash From Operating Activities | 152.4M | 543.1M | 502.5M | (172.4M) | 1.4B | 1.5B |
Data Fundamentals
Return On Equity | 0.15 | ||||
Return On Asset | 0.0822 | ||||
Profit Margin | 0.35 % | ||||
Operating Margin | 0.33 % | ||||
Current Valuation | 123.88 B | ||||
Shares Outstanding | 55.98 M | ||||
Shares Owned By Insiders | 56.67 % | ||||
Shares Owned By Institutions | 18.00 % | ||||
Price To Book | 9.59 X | ||||
Price To Sales | 24.78 X | ||||
Revenue | 5.2 B | ||||
Gross Profit | 2.23 B | ||||
EBITDA | 2.22 B | ||||
Net Income | 1.82 B | ||||
Total Debt | 35 M | ||||
Book Value Per Share | 236.53 X | ||||
Cash Flow From Operations | 1.39 B | ||||
Earnings Per Share | 33.06 X | ||||
Target Price | 2688.4 | ||||
Number Of Employees | 1.34 K | ||||
Beta | 0.33 | ||||
Market Capitalization | 132.35 B | ||||
Total Asset | 16.92 B | ||||
Retained Earnings | 5.09 B | ||||
Working Capital | 10.51 B | ||||
Annual Yield | 0 % | ||||
Net Asset | 16.92 B |
About Data Patterns Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Data Patterns Limited's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Data Patterns using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Data Patterns Limited based on its fundamental data. In general, a quantitative approach, as applied to this company, 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.
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When running Data Patterns' price analysis, check to measure Data Patterns' market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Data Patterns is operating at the current time. Most of Data Patterns' value examination focuses on studying past and present price action to predict the probability of Data Patterns' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Data Patterns' price. Additionally, you may evaluate how the addition of Data Patterns to your portfolios can decrease your overall portfolio volatility.