FAT Brands Stock Forecast - Simple Regression
| FAT Stock | USD 0.38 0 0.79% |
The Simple Regression forecasted value of FAT Brands on the next trading day is expected to be -0.03 with a mean absolute deviation of 0.24 and the sum of the absolute errors of 14.66. FAT Stock Forecast is based on your current time horizon.
At this time the relative strength indicator of FAT Brands' share price is below 20 . This usually indicates that the stock is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Quarterly Earnings Growth 112.056 | EPS Estimate Next Quarter (1.47) | EPS Estimate Current Year (12.67) | EPS Estimate Next Year (10.61) | Wall Street Target Price 10 |
Using FAT Brands hype-based prediction, you can estimate the value of FAT Brands from the perspective of FAT Brands response to recently generated media hype and the effects of current headlines on its competitors.
FAT Brands Hype to Price Pattern
Investor biases related to FAT Brands' public news can be used to forecast risks associated with an investment in FAT. The trend in average sentiment can be used to explain how an investor holding FAT can time the market purely based on public headlines and social activities around FAT Brands. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
The Simple Regression forecasted value of FAT Brands on the next trading day is expected to be -0.03 with a mean absolute deviation of 0.24 and the sum of the absolute errors of 14.66.
FAT Brands after-hype prediction price | USD 0.36 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Check out Historical Fundamental Analysis of FAT Brands to cross-verify your projections. FAT Brands Additional Predictive Modules
Most predictive techniques to examine FAT price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for FAT using various technical 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 | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
FAT Brands Simple Regression Price Forecast For the 24th of January
Given 90 days horizon, the Simple Regression forecasted value of FAT Brands on the next trading day is expected to be -0.03 with a mean absolute deviation of 0.24, mean absolute percentage error of 0.07, and the sum of the absolute errors of 14.66.Please note that although there have been many attempts to predict FAT Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that FAT Brands' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
FAT Brands Stock Forecast Pattern
| Backtest FAT Brands | FAT Brands Price Prediction | Buy or Sell Advice |
FAT Brands Forecasted Value
In the context of forecasting FAT Brands' Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. FAT Brands' downside and upside margins for the forecasting period are 0 and 8.50, respectively. We have considered FAT Brands' daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of FAT Brands stock data series using in forecasting. Note that when a statistical model is used to represent FAT Brands stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 115.503 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.2403 |
| MAPE | Mean absolute percentage error | 0.4181 |
| SAE | Sum of the absolute errors | 14.6589 |
Predictive Modules for FAT Brands
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as FAT Brands. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.FAT Brands After-Hype Price Prediction Density Analysis
As far as predicting the price of FAT Brands at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in FAT Brands or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of FAT Brands, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
FAT Brands Estimiated After-Hype Price Volatility
In the context of predicting FAT Brands' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on FAT Brands' historical news coverage. FAT Brands' after-hype downside and upside margins for the prediction period are 0.02 and 8.95, respectively. We have considered FAT Brands' daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
FAT Brands is dangerous at this time. Analysis and calculation of next after-hype price of FAT Brands is based on 3 months time horizon.
FAT Brands Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as FAT Brands is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading FAT Brands backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with FAT Brands, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
2.18 | 8.53 | 0.02 | 0.16 | 11 Events / Month | 6 Events / Month | In about 11 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
0.38 | 0.36 | 6.01 |
|
FAT Brands Hype Timeline
On the 23rd of January FAT Brands is traded for 0.38. The entity has historical hype elasticity of -0.02, and average elasticity to hype of competition of 0.16. FAT is forecasted to decline in value after the next headline, with the price expected to drop to 0.36. The average volatility of media hype impact on the company price is over 100%. The price depreciation on the next news is expected to be -6.01%, whereas the daily expected return is currently at -2.18%. The volatility of related hype on FAT Brands is about 11847.22%, with the expected price after the next announcement by competition of 0.54. About 67.0% of the company shares are held by company insiders. The company recorded a loss per share of 13.36. FAT Brands last dividend was issued on the 15th of November 2024. The entity had 1794:1000 split on the 30th of January 2025. Considering the 90-day investment horizon the next forecasted press release will be in about 11 days. Check out Historical Fundamental Analysis of FAT Brands to cross-verify your projections.FAT Brands Related Hype Analysis
Having access to credible news sources related to FAT Brands' direct competition is more important than ever and may enhance your ability to predict FAT Brands' future price movements. Getting to know how FAT Brands' peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how FAT Brands may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| NDLS | Noodles Company | 0.04 | 11 per month | 5.08 | 0.07 | 13.64 | (8.75) | 44.79 | |
| RAVE | Rave Restaurant Group | (0.05) | 9 per month | 3.17 | 0.05 | 5.45 | (4.43) | 23.89 | |
| REE | Ree Automotive Holding | 0.02 | 9 per month | 0.00 | (0.16) | 8.00 | (8.97) | 25.96 | |
| LESL | Leslies | 0.27 | 6 per month | 0.00 | (0.15) | 9.20 | (9.63) | 42.31 | |
| ARKR | Ark Restaurants Corp | 0.25 | 10 per month | 0.00 | (0.09) | 3.15 | (5.82) | 12.34 | |
| NTZ | Natuzzi SpA | 0.15 | 10 per month | 4.29 | 0 | 10.37 | (7.04) | 25.04 | |
| MKDW | MKDWELL Tech Ordinary | 0.01 | 5 per month | 0.00 | (0.07) | 10.00 | (5.88) | 31.11 | |
| CDRO | Codere Online Corp | 0.05 | 5 per month | 1.65 | 0.08 | 5.98 | (3.51) | 13.32 | |
| PFAI | Pinnacle Food Group | (0.03) | 5 per month | 0.00 | (0.17) | 6.90 | (8.57) | 31.61 | |
| LITB | LightInTheBox Holding Co | 0.01 | 7 per month | 5.83 | 0.03 | 13.41 | (9.79) | 30.20 |
Other Forecasting Options for FAT Brands
For every potential investor in FAT, whether a beginner or expert, FAT Brands' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. FAT Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in FAT. Basic forecasting techniques help filter out the noise by identifying FAT Brands' price trends.FAT Brands Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with FAT Brands stock to make a market-neutral strategy. Peer analysis of FAT Brands could also be used in its relative valuation, which is a method of valuing FAT Brands by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
FAT Brands Market Strength Events
Market strength indicators help investors to evaluate how FAT Brands stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading FAT Brands shares will generate the highest return on investment. By undertsting and applying FAT Brands stock market strength indicators, traders can identify FAT Brands entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 0.38 | |||
| Day Typical Price | 0.38 | |||
| Price Action Indicator | 0.0045 | |||
| Period Momentum Indicator | 0.003 |
FAT Brands Risk Indicators
The analysis of FAT Brands' basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in FAT Brands' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fat stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 5.37 | |||
| Standard Deviation | 8.22 | |||
| Variance | 67.59 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for FAT Brands
The number of cover stories for FAT Brands depends on current market conditions and FAT Brands' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that FAT Brands is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about FAT Brands' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Contributor Headline
Latest Perspective From Macroaxis
FAT Brands Short Properties
FAT Brands' future price predictability will typically decrease when FAT Brands' long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of FAT Brands often depends not only on the future outlook of the potential FAT Brands' investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. FAT Brands' indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 17 M | |
| Cash And Short Term Investments | 23.4 M |
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.