Ross Stores Stock Statistic Functions Beta
ROST Stock | USD 142.96 3.64 2.61% |
Symbol |
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. The Beta measures systematic risk based on how returns on Ross Stores correlated with the market. If Beta is less than 0 Ross Stores generally moves in the opposite direction as compared to the market. If Ross Stores Beta is about zero movement of price series is uncorrelated with the movement of the benchmark. if Beta is between zero and one Ross Stores is generally moves in the same direction as, but less than the movement of the market. For Beta = 1 movement of Ross Stores is generally in the same direction as the market. If Beta > 1 Ross Stores moves generally in the same direction as, but more than the movement of the benchmark.
Ross Stores Technical Analysis Modules
Most technical analysis of Ross Stores help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Ross from various momentum indicators to cycle indicators. When you analyze Ross charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.Cycle Indicators | ||
Math Operators | ||
Math Transform | ||
Momentum Indicators | ||
Overlap Studies | ||
Pattern Recognition | ||
Price Transform | ||
Statistic Functions | ||
Volatility Indicators | ||
Volume Indicators |
About Ross Stores Predictive Technical Analysis
Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Ross Stores. We use our internally-developed statistical techniques to arrive at the intrinsic value of Ross Stores based on widely used predictive technical indicators. In general, we focus on analyzing Ross Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Ross Stores's daily price indicators and compare them against related drivers, such as statistic functions and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Ross Stores's intrinsic value. In addition to deriving basic predictive indicators for Ross Stores, we also check how macroeconomic factors affect Ross Stores price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
2011 | 2014 | 2020 | 2024 (projected) | Dividend Yield | 0.0102 | 0.009195 | 0.009444 | 0.008882 | Price To Sales Ratio | 1.41 | 2.51 | 2.36 | 1.72 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Ross Stores' 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.
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Additional Tools for Ross Stock Analysis
When running Ross Stores' price analysis, check to measure Ross Stores' 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 Ross Stores is operating at the current time. Most of Ross Stores' value examination focuses on studying past and present price action to predict the probability of Ross Stores' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Ross Stores' price. Additionally, you may evaluate how the addition of Ross Stores to your portfolios can decrease your overall portfolio volatility.