Data Competitors
| DATAPATTNS | 2,283 16.05 0.70% |
Data |
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Data Patterns Competition Correlation Matrix
Typically, diversification allows investors to combine positions across different asset classes to reduce overall portfolio risk. Correlation between Data Patterns and its competitors represents the degree of relationship between the price movements of corresponding stocks. A correlation of about +1.0 implies that the price of Data and its corresponding peer move in tandem. A correlation of -1.0 means that prices move in opposite directions. A correlation of close to zero suggests that the price movements of assets are uncorrelated; in other words, the historical price movement of Data Patterns Limited does not affect the price movement of the other competitor.
| -0.19 | 0.82 | 0.85 | 0.05 | IRFC | ||
| -0.19 | 0.31 | -0.07 | 0.25 | CHOLAHLDNG | ||
| 0.82 | 0.31 | 0.82 | 0.14 | RELIANCE | ||
| 0.85 | -0.07 | 0.82 | 0.04 | TCS | ||
| 0.05 | 0.25 | 0.14 | 0.04 | PEL | ||
| Click cells to compare fundamentals | Check Volatility | Backtest Portfolio |
High positive correlations
| High negative correlations
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Risk-Adjusted Indicators
There is a big difference between Data Stock performing well and Data Patterns Company doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze Data Patterns' multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.| Mean Deviation | Jensen Alpha | Sortino Ratio | Treynor Ratio | Semi Deviation | Expected Shortfall | Potential Upside | Value @Risk | Maximum Drawdown | ||
|---|---|---|---|---|---|---|---|---|---|---|
| IRFC | 1.48 | (0.29) | 0.00 | 0.93 | 0.00 | 4.98 | 11.19 | |||
| CHOLAHLDNG | 1.84 | (0.09) | 0.00 | (0.26) | 0.00 | 3.65 | 11.57 | |||
| RELIANCE | 0.92 | (0.26) | 0.00 | (18.01) | 0.00 | 1.54 | 5.53 | |||
| TCS | 0.76 | (0.10) | 0.00 | 3.49 | 0.00 | 1.26 | 7.29 | |||
| PEL | 1.50 | 0.12 | 0.00 | 7.06 | 1.90 | 2.90 | 10.76 |
Cross Equities Net Income Analysis
Compare Data Patterns Limited and related stocks such as Indian Railway Finance, Cholamandalam Financial, and Reliance Industries Net Income Over Time
| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IRFC | 5.2 B | 5.2 B | 5.2 B | 7 B | 7.6 B | 8.5 B | 21.1 B | 20 B | 21.4 B | 31.9 B | 44.2 B | 60.9 B | 61.7 B | 64.1 B | 32.4 B |
| CHOLAHLDNG | 941.1 M | 2.7 B | 2.9 B | 3.1 B | 4.2 B | 10.4 B | 4.5 B | 6 B | 7 B | 5.5 B | 8.2 B | 10.2 B | 12.9 B | 17.7 B | 18.6 B |
| RELIANCE | 76.3 B | 197.2 B | 208.8 B | 224.9 B | 235.7 B | 276.3 B | 299 B | 360.8 B | 395.9 B | 393.5 B | 491.3 B | 607 B | 667 B | 696.2 B | 731 B |
| TCS | 19.8 B | 104.1 B | 139.2 B | 191.6 B | 198.5 B | 242.9 B | 262.9 B | 258.3 B | 314.7 B | 323.4 B | 324.3 B | 383.3 B | 421.5 B | 459.1 B | 482 B |
| PEL | 1.6 B | 1.1 B | (2.3 B) | (5 B) | 28.5 B | 9.5 B | 12.5 B | 51.2 B | 14.7 B | 240.3 M | 13.3 B | 19.2 B | 143.3 B | (16.8 B) | (16 B) |
Data Patterns Limited and related stocks such as Indian Railway Finance, Cholamandalam Financial, and Reliance Industries Net Income description
Net income is one of the most important fundamental items in finance. It plays a large role in Data Patterns Limited financial statement analysis. It represents the amount of money remaining after all of Data Patterns Limited operating expenses, interest, taxes and preferred stock dividends have been deducted from a company total revenue.Data Patterns Competitive Analysis
The better you understand Data Patterns competitors, the better chance you have of utilizing it as a position in your portfolios. From an individual investor's perspective, Data Patterns' competitive analysis can cover a whole range of metrics. Some of these will be more critical depending on who you are as an investor and how you react to market volatility. However, if you are locking your investment sandscape to a long-term horizon, comparing the fundamental indicator across Data Patterns' competition over several years is one of the best ways to analyze its investment potential.| Better Than Average | Worse Than Peers | View Performance Chart |
Data Patterns Competition Performance Charts
Five steps to successful analysis of Data Patterns Competition
Data Patterns' competitive analysis is the process of researching and evaluating its competitive landscape. It provides an understanding of the strengths, weaknesses, opportunities, and threats (SWOT) faced by Data Patterns Limited in relation to its competition. Data Patterns' competition analysis typically involves several steps, including:- Identifying the key players in the market: This involves identifying the major competitors of Data Patterns in the market, both direct and indirect, as well as new entrants and disruptive technologies.
- Assessing the strengths and weaknesses of each competitor: This involves evaluating each competitor's strengths and weaknesses in areas such as product offerings, market share, brand recognition, financial performance, and distribution channels.
- Understanding the competitive environment: This involves evaluating the regulatory environment, economic conditions, and other factors that may impact Data Patterns' competitive landscape.
- Identifying opportunities and threats: This involves using the information gathered during the analysis to identify opportunities and threats to Data Patterns Limited, and developing a strategy to address them.
- Evaluating the competitive landscape: This involves understanding the competitive dynamics of the market, such as pricing, marketing, and distribution strategies, as well as analyzing the competitive advantage of each competitor.
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Additional Tools for Data Stock Analysis
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.