Data Agro (Pakistan) Market Value
| DAAG Stock | 90.32 0.75 0.82% |
| Symbol | Data |
Data Agro '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 Agro's 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 Agro.
| 12/16/2024 |
| 03/16/2025 |
If you would invest 0.00 in Data Agro on December 16, 2024 and sell it all today you would earn a total of 0.00 from holding Data Agro or generate 0.0% return on investment in Data Agro over 90 days. Data Agro is related to or competes with United Insurance, Fauji Foods, Adamjee Insurance, and Century Insurance. More
Data Agro 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 Agro's 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 Agro upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 3.77 | |||
| Information Ratio | 0.0656 | |||
| Maximum Drawdown | 18.85 | |||
| Value At Risk | (6.67) | |||
| Potential Upside | 10.0 |
Data Agro Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data Agro's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data Agro's standard deviation. In reality, there are many statistical measures that can use Data Agro historical prices to predict the future Data Agro's volatility.| Risk Adjusted Performance | 0.0466 | |||
| Jensen Alpha | 0.1277 | |||
| Total Risk Alpha | 0.7738 | |||
| Sortino Ratio | 0.0806 | |||
| Treynor Ratio | (0.32) |
Data Agro Backtested Returns
Data Agro secures Sharpe Ratio (or Efficiency) of -0.0715, which denotes the company had a -0.0715 % return per unit of risk over the last 3 months. Data Agro exposes twenty-nine different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Data Agro's Downside Deviation of 3.77, coefficient of variation of 2262.48, and Mean Deviation of 3.53 to check the risk estimate we provide. The firm shows a Beta (market volatility) of -0.61, which means possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning Data Agro are expected to decrease at a much lower rate. During the bear market, Data Agro is likely to outperform the market. At this point, Data Agro has a negative expected return of -0.3%. Please make sure to confirm Data Agro's total risk alpha, treynor ratio, value at risk, as well as the relationship between the sortino ratio and maximum drawdown , to decide if Data Agro performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.58 |
Modest predictability
Data Agro has modest predictability. Overlapping area represents the amount of predictability between Data Agro time series from 16th of December 2024 to 30th of January 2025 and 30th of January 2025 to 16th of March 2025. 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 Agro price movement. The serial correlation of 0.58 indicates that roughly 58.0% of current Data Agro price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.58 | |
| Spearman Rank Test | 0.63 | |
| Residual Average | 0.0 | |
| Price Variance | 107.07 |
Data Agro lagged returns against current returns
Autocorrelation, which is Data Agro 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 Agro's stock expected returns. We can calculate the autocorrelation of Data Agro returns to help us make a trade decision. For example, suppose you find that Data Agro 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 Agro 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 Agro stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Data Agro stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Data Agro stock over time.
Current vs Lagged Prices |
| Timeline |
Data Agro Lagged Returns
When evaluating Data Agro's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Data Agro stock have on its future price. Data Agro 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 Agro autocorrelation shows the relationship between Data Agro stock current value and its past values and can show if there is a momentum factor associated with investing in Data Agro.
Regressed Prices |
| Timeline |
Pair Trading with Data Agro
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Data Agro position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Data Agro will appreciate offsetting losses from the drop in the long position's value.Moving together with Data Stock
Moving against Data Stock
The ability to find closely correlated positions to Data Agro could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Data Agro when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Data Agro - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Data Agro to buy it.
The correlation of Data Agro is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Data Agro moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Data Agro moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Data Agro can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Other Information on Investing in Data Stock
Data Agro financial ratios help investors to determine whether Data Stock 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 Data with respect to the benefits of owning Data Agro security.