Automatic Data Valuation

ADPR34 Stock  BRL 57.12  0.08  0.14%   
At this time, the firm appears to be overvalued. Automatic Data Processing shows a prevailing Real Value of R$50.64 per share. The current price of the firm is R$57.12. Our model approximates the value of Automatic Data Processing from analyzing the firm fundamentals such as Current Valuation of 586.65 B, return on equity of 0.78, and Profit Margin of 0.18 % as well as examining its technical indicators and probability of bankruptcy.
Overvalued
Today
57.12
Please note that Automatic Data's price fluctuation is very steady at this time. Calculation of the real value of Automatic Data Processing is based on 3 months time horizon. Increasing Automatic Data's time horizon generally increases the accuracy of value calculation and significantly improves the predictive power of the methodology used.
Since Automatic Data is currently traded on the exchange, buyers and sellers on that exchange determine the market value of Automatic Stock. However, Automatic Data's intrinsic value may or may not be the same as its current market price, in which case there is an opportunity to profit from the mispricing, assuming the market price will eventually merge with its intrinsic value.
Historical Market  57.12 Real  50.64 Hype  57.12 Naive  56.9
The real value of Automatic Stock, also known as its intrinsic value, is the underlying worth of Automatic Data Processing Company, which is reflected in its stock price. It is based on Automatic Data's financial performance, growth prospects, management team, or industry conditions. The intrinsic value of Automatic Data's stock can be calculated using various methods such as discounted cash flow analysis, price-to-earnings ratio, or price-to-book ratio. That value may differ from its current market price, which is determined by supply and demand factors such as investor sentiment, market trends, or news.
50.64
Real Value
62.83
Upside
Estimating the potential upside or downside of Automatic Data Processing helps investors to forecast how Automatic stock's addition to their portfolios will impact the overall performance. We also use other valuation drivers to help us estimate the true value of Automatic Data more accurately as focusing exclusively on Automatic Data's fundamentals will not take into account other important factors:
Bollinger
Band Projection (param)
LowerMiddle BandUpper
56.3558.5860.80
Details
Hype
Prediction
LowEstimatedHigh
55.9057.1258.34
Details
Naive
Forecast
LowNext ValueHigh
55.6856.9058.12
Details

About Automatic Data Valuation

The stock valuation mechanism determines Automatic Data's current worth on a weekly basis. Our valuation model uses a comparative analysis of Automatic Data. We calculate exposure to Automatic Data's market risk, different technical and fundamental indicators, and relevant financial multiples and ratios and then compare them to those of Automatic Data's related companies.
Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. The company was founded in 1949 and is headquartered in Roseland, New Jersey. AUTOMATIC DTDRN operates under Staffing Employment Services classification in Brazil and is traded on Sao Paolo Stock Exchange. It employs 58000 people.

8 Steps to conduct Automatic Data's Valuation Analysis

Company's valuation is the process of determining the worth of any company in monetary terms. It estimates Automatic Data's potential worth based on factors such as financial performance, market conditions, growth prospects, and overall economic environment. The result of company valuation is a single number representing a Company's current market value. This value can be used as a benchmark for various financial transactions such as mergers and acquisitions, initial public offerings (IPOs), or private equity investments. To conduct Automatic Data's valuation analysis, follow these 8 steps:
  • Gather financial information: Obtain Automatic Data's financial statements, including balance sheets, income statements, and cash flow statements.
  • Determine Automatic Data's revenue streams: Identify Automatic Data's primary sources of revenue, including products or services offered, target markets, and pricing strategies.
  • Analyze market data: Research Automatic Data's industry and market trends, including the size of the market, growth rate, and competition.
  • Establish Automatic Data's growth potential: Evaluate Automatic Data's management, business model, and growth potential.
  • Determine Automatic Data's financial performance: Analyze its financial statements to assess its historical performance and future potential.
  • Choose a valuation method: Consider the Company's specific circumstances and choose an appropriate valuation method, such as the discounted cash flow (DCF) or comparable analysis method.
  • Calculate the value: Apply the chosen valuation method to the financial information and market data to calculate Automatic Data's estimated value.
  • Review and adjust: Review the results and make necessary adjustments, considering any relevant factors that may have been missed or overlooked.
Note: This is a general outline, and different approaches and methods may be used depending on the type and size of the company being valued. We also recomment to seek professional assistance to ensure accuracy.

Complementary 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.
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