Fat Brands Stock Overlap Studies Double Exponential Moving Average
| FAT Stock | USD 5.33 0.04 0.74% |
| Symbol |
Illegal number of arguments. The output start index for this execution was zero with a total number of output elements of zero. The Double Exponential Moving Average indicator was developed by Patrick Mulloy. It consists of a single exponential moving average and a double exponential moving average. This indicator is more responsive to FAT Brands changes than the simple moving average.
FAT Brands Technical Analysis Modules
Most technical analysis of FAT Brands 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 FAT from various momentum indicators to cycle indicators. When you analyze FAT 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 | ||
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| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About FAT Brands 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 FAT Brands. We use our internally-developed statistical techniques to arrive at the intrinsic value of FAT Brands based on widely used predictive technical indicators. In general, we focus on analyzing FAT Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build FAT Brands'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 FAT Brands's intrinsic value. In addition to deriving basic predictive indicators for FAT Brands, we also check how macroeconomic factors affect FAT Brands price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
| 2022 | 2023 (projected) | Dividend Yield | 0.16 | 0.15 | Price To Sales Ratio | 0.21 | 0.24 |
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Additional Tools for FAT Stock Analysis
When running FAT Brands' price analysis, check to measure FAT Brands' 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 FAT Brands is operating at the current time. Most of FAT Brands' value examination focuses on studying past and present price action to predict the probability of FAT Brands' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move FAT Brands' price. Additionally, you may evaluate how the addition of FAT Brands to your portfolios can decrease your overall portfolio volatility.