Data Patterns (India) Market Value
| DATAPATTNS | 2,283 16.05 0.70% |
| Symbol | Data |
Data Patterns 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Data Patterns' stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Data Patterns.
| 10/30/2023 |
| 11/23/2024 |
If you would invest 0.00 in Data Patterns on October 30, 2023 and sell it all today you would earn a total of 0.00 from holding Data Patterns Limited or generate 0.0% return on investment in Data Patterns over 390 days. Data Patterns is related to or competes with Indian Railway, Cholamandalam Financial, Reliance Industries, Tata Consultancy, and Piramal Enterprises. Data Patterns is entity of India. It is traded as Stock on NSE exchange. More
Data Patterns Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Data Patterns' stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Data Patterns Limited upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.16) | |||
| Maximum Drawdown | 18.52 | |||
| Value At Risk | (4.32) | |||
| Potential Upside | 4.13 |
Data Patterns Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data Patterns' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data Patterns' standard deviation. In reality, there are many statistical measures that can use Data Patterns historical prices to predict the future Data Patterns' volatility.| Risk Adjusted Performance | (0.08) | |||
| Jensen Alpha | (0.29) | |||
| Total Risk Alpha | (0.77) | |||
| Treynor Ratio | 1.19 |
Data Patterns Limited Backtested Returns
Data Patterns Limited secures Sharpe Ratio (or Efficiency) of -0.11, which denotes the company had a -0.11% return per unit of risk over the last 3 months. Data Patterns Limited exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Data Patterns' Variance of 8.0, standard deviation of 2.83, and Mean Deviation of 1.9 to check the risk estimate we provide. The firm shows a Beta (market volatility) of -0.27, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Data Patterns are expected to decrease at a much lower rate. During the bear market, Data Patterns is likely to outperform the market. At this point, Data Patterns Limited has a negative expected return of -0.31%. Please make sure to confirm Data Patterns' treynor ratio, kurtosis, as well as the relationship between the Kurtosis and day typical price , to decide if Data Patterns Limited performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.78 |
Almost perfect reverse predictability
Data Patterns Limited has almost perfect reverse predictability. Overlapping area represents the amount of predictability between Data Patterns time series from 30th of October 2023 to 12th of May 2024 and 12th of May 2024 to 23rd of November 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Data Patterns Limited price movement. The serial correlation of -0.78 indicates that around 78.0% of current Data Patterns price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.78 | |
| Spearman Rank Test | -0.53 | |
| Residual Average | 0.0 | |
| Price Variance | 109.5 K |
Data Patterns Limited lagged returns against current returns
Autocorrelation, which is Data Patterns stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Data Patterns' stock expected returns. We can calculate the autocorrelation of Data Patterns returns to help us make a trade decision. For example, suppose you find that Data Patterns has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Data Patterns regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Data Patterns stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Data Patterns stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Data Patterns stock over time.
Current vs Lagged Prices |
| Timeline |
Data Patterns Lagged Returns
When evaluating Data Patterns' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Data Patterns stock have on its future price. Data Patterns autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Data Patterns autocorrelation shows the relationship between Data Patterns stock current value and its past values and can show if there is a momentum factor associated with investing in Data Patterns Limited.
Regressed Prices |
| Timeline |
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.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.