| DATAPATTNS | | | 2,358 45.45 1.97% |
Altman Z Score is one of the simplest fundamental models to determine how likely your company is to fail. The module uses available fundamental data of a given equity to approximate the Altman Z score. Altman Z Score is determined by evaluating five fundamental price points available from the company's current public disclosure documents. Check out
Investing Opportunities to better understand how to build diversified portfolios, which includes a position in Data Patterns Limited. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as
signals in american community survey.
Capital Expenditures is likely to gain to about 915.6
M in 2024, whereas
Capital Lease Obligations is likely to drop slightly above 32.8
M in 2024. At this time, Data Patterns'
Income Tax Expense is comparatively stable compared to the past year.
Data Patterns Limited Company Z Score Analysis
Data Patterns' Z-Score is a simple linear, multi-factor model that measures the financial health and economic stability of a company. The score is used to predict the probability of a firm going into bankruptcy within next 24 months or two fiscal years from the day stated on the accounting statements used to calculate it. The model uses five fundamental business ratios that are weighted according to algorithm of Professor Edward Altman who developed it in the late 1960s at New York University..
| First Factor | = | 1.2 * ( | Working Capital | / | Total Assets ) |
|
| Second Factor | = | 1.4 * ( | Retained Earnings | / | Total Assets ) |
|
| Thrid Factor | = | 3.3 * ( | EBITAD | / | Total Assets ) |
|
| Fouth Factor | = | 0.6 * ( | Market Value of Equity | / | Total Liabilities ) |
|
| Fifth Factor | = | 0.99 * ( | Revenue | / | Total Assets ) |
|
To calculate a Z-Score, one would need to know a company's current working capital, its total assets and liabilities, and the amount of its latest earnings as well as earnings before interest and tax. Z-Scores can be used to compare the odds of bankruptcy of companies in a similar line of business or firms operating in the same industry. Companies with Z-Scores above 3.1 are generally considered to be stable and healthy with a low probability of bankruptcy. Scores that fall between 1.8 and 3.1 lie in a so-called 'grey area,' with scores of less than 1 indicating the highest probability of distress. Z Score is a used widely measure by financial auditors, accountants, money managers, loan processors, wealth advisers, and day traders. In the last 25 years, many financial models that utilize z-scores proved it to be successful as a predictor of corporate bankruptcy.
According to the company's disclosures, Data Patterns Limited has a Z Score of 0.0. This is 100.0% lower than that of the Aerospace & Defense sector and 100.0% lower than that of the
Industrials industry. The z score for all India stocks is 100.0% higher than that of the company.
| | Odds Of BankruptcyGet analysis of equity chance of financial distress in the next 2 years |
Data Fundamentals
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.
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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.