Applied Materials Stock Overlap Studies All Moving Average
| AMAT Stock | USD 174.70 0.00 0.00% |
| Symbol |
Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. The Moving Average is predictive technique used to analyze Applied Materials price data points by creating a series of averages of different subsets of Applied Materials entire price series.
Applied Materials Technical Analysis Modules
Most technical analysis of Applied Materials 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 Applied from various momentum indicators to cycle indicators. When you analyze Applied 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 Applied Materials 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 Applied Materials. We use our internally-developed statistical techniques to arrive at the intrinsic value of Applied Materials based on widely used predictive technical indicators. In general, we focus on analyzing Applied Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Applied Materials's daily price indicators and compare them against related drivers, such as overlap studies 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 Applied Materials's intrinsic value. In addition to deriving basic predictive indicators for Applied Materials, we also check how macroeconomic factors affect Applied Materials price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
| 2015 | 2020 | 2024 (projected) | PTB Ratio | 5.15 | 6.73 | 10.88 | Price To Sales Ratio | 3.17 | 5.64 | 5.5 |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Applied Materials in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Applied Materials' short interest history, or implied volatility extrapolated from Applied Materials options trading.
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Additional Tools for Applied Stock Analysis
When running Applied Materials' price analysis, check to measure Applied Materials' 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 Applied Materials is operating at the current time. Most of Applied Materials' value examination focuses on studying past and present price action to predict the probability of Applied Materials' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Applied Materials' price. Additionally, you may evaluate how the addition of Applied Materials to your portfolios can decrease your overall portfolio volatility.