Automatic Data (Brazil) Market Value
| ADPR34 Stock | BRL 73.24 0.76 1.03% |
| Symbol | Automatic |
Automatic Data '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 Automatic Data'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 Automatic Data.
| 10/27/2024 |
| 11/26/2024 |
If you would invest 0.00 in Automatic Data on October 27, 2024 and sell it all today you would earn a total of 0.00 from holding Automatic Data Processing or generate 0.0% return on investment in Automatic Data over 30 days. Automatic Data is related to or competes with Fras Le, BTG Pactual, Telefonaktiebolaget, Cable One, Randon SA, and Alphabet. Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide More
Automatic Data 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 Automatic Data'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 Automatic Data Processing upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.52 | |||
| Information Ratio | 0.1286 | |||
| Maximum Drawdown | 9.17 | |||
| Value At Risk | (1.47) | |||
| Potential Upside | 2.58 |
Automatic Data Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Automatic Data's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Automatic Data's standard deviation. In reality, there are many statistical measures that can use Automatic Data historical prices to predict the future Automatic Data's volatility.| Risk Adjusted Performance | 0.1749 | |||
| Jensen Alpha | 0.2834 | |||
| Total Risk Alpha | 0.0804 | |||
| Sortino Ratio | 0.1182 | |||
| Treynor Ratio | 2.15 |
Automatic Data Processing Backtested Returns
Automatic Data appears to be very steady, given 3 months investment horizon. Automatic Data Processing secures Sharpe Ratio (or Efficiency) of 0.18, which signifies that the company had a 0.18% return per unit of risk over the last 3 months. We have found thirty technical indicators for Automatic Data Processing, which you can use to evaluate the volatility of the firm. Please makes use of Automatic Data's Mean Deviation of 0.7777, risk adjusted performance of 0.1749, and Downside Deviation of 1.52 to double-check if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Automatic Data holds a performance score of 13. The firm shows a Beta (market volatility) of 0.14, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Automatic Data's returns are expected to increase less than the market. However, during the bear market, the loss of holding Automatic Data is expected to be smaller as well. Please check Automatic Data's treynor ratio, value at risk, and the relationship between the sortino ratio and maximum drawdown , to make a quick decision on whether Automatic Data's price patterns will revert.
Auto-correlation | -0.14 |
Insignificant reverse predictability
Automatic Data Processing has insignificant reverse predictability. Overlapping area represents the amount of predictability between Automatic Data time series from 27th of October 2024 to 11th of November 2024 and 11th of November 2024 to 26th 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 Automatic Data Processing price movement. The serial correlation of -0.14 indicates that less than 14.0% of current Automatic Data price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.14 | |
| Spearman Rank Test | -0.52 | |
| Residual Average | 0.0 | |
| Price Variance | 0.33 |
Automatic Data Processing lagged returns against current returns
Autocorrelation, which is Automatic Data 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 Automatic Data's stock expected returns. We can calculate the autocorrelation of Automatic Data returns to help us make a trade decision. For example, suppose you find that Automatic Data 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 |
Automatic Data 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 Automatic Data stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Automatic Data stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Automatic Data stock over time.
Current vs Lagged Prices |
| Timeline |
Automatic Data Lagged Returns
When evaluating Automatic Data's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Automatic Data stock have on its future price. Automatic Data 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, Automatic Data autocorrelation shows the relationship between Automatic Data stock current value and its past values and can show if there is a momentum factor associated with investing in Automatic Data Processing.
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 Information and Resources on Investing in Automatic Stock
When determining whether Automatic Data Processing is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Automatic Stock is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Automatic Data Processing Stock. Highlighted below are key reports to facilitate an investment decision about Automatic Data Processing Stock:Check out Automatic Data Correlation, Automatic Data Volatility and Automatic Data Alpha and Beta module to complement your research on Automatic Data. You can also try the Idea Breakdown module to analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes.
Automatic Data technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.