Automatic Data (UK) Market Value
| 0HJI Stock | 303.40 0.25 0.08% |
| 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.
| 09/03/2024 |
| 01/31/2025 |
If you would invest 0.00 in Automatic Data on September 3, 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 150 days. Automatic Data is related to or competes with Empire Metals, Wheaton Precious, Monks Investment, Jupiter Fund, Lindsell Train, Impax Asset, and Edinburgh Investment. Automatic Data is entity of United Kingdom 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 | 0.9906 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 7.53 | |||
| Value At Risk | (1.28) | |||
| Potential Upside | 1.2 |
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 | 0.0732 | |||
| Jensen Alpha | 0.0737 | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 2.02 |
Automatic Data Processing Backtested Returns
Currently, Automatic Data Processing is very steady. Automatic Data Processing secures Sharpe Ratio (or Efficiency) of 0.0792, which signifies that the company had a 0.0792 % return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Automatic Data Processing, which you can use to evaluate the volatility of the firm. Please confirm Automatic Data's Mean Deviation of 0.7011, downside deviation of 0.9906, and Risk Adjusted Performance of 0.0732 to double-check if the risk estimate we provide is consistent with the expected return of 0.0815%. Automatic Data has a performance score of 6 on a scale of 0 to 100. The firm shows a Beta (market volatility) of 0.0381, 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. Automatic Data Processing right now shows a risk of 1.03%. Please confirm Automatic Data Processing standard deviation, total risk alpha, treynor ratio, as well as the relationship between the jensen alpha and sortino ratio , to decide if Automatic Data Processing will be following its price patterns.
Auto-correlation | -0.3 |
Weak reverse predictability
Automatic Data Processing has weak reverse predictability. Overlapping area represents the amount of predictability between Automatic Data time series from 3rd of September 2024 to 17th of November 2024 and 17th of November 2024 to 31st of January 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 Automatic Data Processing price movement. The serial correlation of -0.3 indicates that nearly 30.0% of current Automatic Data price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.3 | |
| Spearman Rank Test | -0.44 | |
| Residual Average | 0.0 | |
| Price Variance | 25.14 |
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 |
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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 Automatic Stock Analysis
When running Automatic Data's price analysis, check to measure Automatic Data's 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 Automatic Data is operating at the current time. Most of Automatic Data's value examination focuses on studying past and present price action to predict the probability of Automatic Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Automatic Data's price. Additionally, you may evaluate how the addition of Automatic Data to your portfolios can decrease your overall portfolio volatility.