Factset Research Systems Stock Market Value
| FDS Stock | USD 438.43 4.41 1.02% |
| Symbol | FactSet |
FactSet Research Systems Price To Book Ratio
Is FactSet Research's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of FactSet Research. If investors know FactSet will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about FactSet Research listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 0.08 | Dividend Share 3.92 | Earnings Share 12.63 | Revenue Per Share 56.495 | Quarterly Revenue Growth 0.06 |
The market value of FactSet Research Systems is measured differently than its book value, which is the value of FactSet that is recorded on the company's balance sheet. Investors also form their own opinion of FactSet Research's value that differs from its market value or its book value, called intrinsic value, which is FactSet Research's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because FactSet Research's market value can be influenced by many factors that don't directly affect FactSet Research's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between FactSet Research's value and its price as these two are different measures arrived at by different means. Investors typically determine if FactSet Research is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, FactSet Research's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
FactSet Research '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 FactSet Research'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 FactSet Research.
| 03/24/2024 |
| 04/23/2024 |
If you would invest 0.00 in FactSet Research on March 24, 2024 and sell it all today you would earn a total of 0.00 from holding FactSet Research Systems or generate 0.0% return on investment in FactSet Research over 30 days. FactSet Research is related to or competes with Dun Bradstreet, Moodys, MSCI, Intercontinental, SP Global, Nasdaq, and CME. FactSet Research Systems Inc., a financial data and analytics company, provides integrated financial information and ana... More
FactSet Research 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 FactSet Research'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 FactSet Research Systems upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.11) | |||
| Maximum Drawdown | 9.93 | |||
| Value At Risk | (2.50) | |||
| Potential Upside | 1.6 |
FactSet Research Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for FactSet Research's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as FactSet Research's standard deviation. In reality, there are many statistical measures that can use FactSet Research historical prices to predict the future FactSet Research's volatility.| Risk Adjusted Performance | (0.02) | |||
| Jensen Alpha | (0.13) | |||
| Total Risk Alpha | (0.25) | |||
| Treynor Ratio | (0.11) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of FactSet Research's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
FactSet Research Systems Backtested Returns
FactSet Research Systems secures Sharpe Ratio (or Efficiency) of -0.0705, which denotes the company had a -0.0705% return per unit of standard deviation over the last 3 months. FactSet Research Systems exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm FactSet Research's Coefficient Of Variation of (2,003), standard deviation of 1.4, and Mean Deviation of 0.9105 to check the risk estimate we provide. The firm shows a Beta (market volatility) of 0.73, which means possible diversification benefits within a given portfolio. As returns on the market increase, FactSet Research's returns are expected to increase less than the market. However, during the bear market, the loss of holding FactSet Research is expected to be smaller as well. FactSet Research Systems has an expected return of -0.1%. Please make sure to confirm FactSet Research Systems jensen alpha, as well as the relationship between the skewness and day median price , to decide if FactSet Research Systems performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.12 |
Insignificant predictability
FactSet Research Systems has insignificant predictability. Overlapping area represents the amount of predictability between FactSet Research time series from 24th of March 2024 to 8th of April 2024 and 8th of April 2024 to 23rd of April 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 FactSet Research Systems price movement. The serial correlation of 0.12 indicates that less than 12.0% of current FactSet Research price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.12 | |
| Spearman Rank Test | -0.33 | |
| Residual Average | 0.0 | |
| Price Variance | 27.95 |
FactSet Research Systems lagged returns against current returns
Autocorrelation, which is FactSet Research 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 FactSet Research's stock expected returns. We can calculate the autocorrelation of FactSet Research returns to help us make a trade decision. For example, suppose you find that FactSet Research 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 |
FactSet Research 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 FactSet Research stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if FactSet Research stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in FactSet Research stock over time.
Current vs Lagged Prices |
| Timeline |
FactSet Research Lagged Returns
When evaluating FactSet Research's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of FactSet Research stock have on its future price. FactSet Research 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, FactSet Research autocorrelation shows the relationship between FactSet Research stock current value and its past values and can show if there is a momentum factor associated with investing in FactSet Research Systems.
Regressed Prices |
| Timeline |
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Try AI Portfolio ArchitectCheck out FactSet Research Correlation, FactSet Research Volatility and FactSet Research Alpha and Beta module to complement your research on FactSet Research. Note that the FactSet Research Systems information on this page should be used as a complementary analysis to other FactSet Research's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Idea Analyzer module to analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas.
Complementary Tools for FactSet Stock analysis
When running FactSet Research's price analysis, check to measure FactSet Research'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 FactSet Research is operating at the current time. Most of FactSet Research's value examination focuses on studying past and present price action to predict the probability of FactSet Research's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move FactSet Research's price. Additionally, you may evaluate how the addition of FactSet Research to your portfolios can decrease your overall portfolio volatility.
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FactSet Research 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.