Good Times Stock Forecast - Simple Regression

GTIM Stock  USD 2.69  0.02  0.74%   
The Simple Regression forecasted value of Good Times Restaurants on the next trading day is expected to be 2.66 with a mean absolute deviation of 0.06 and the sum of the absolute errors of 3.59. Good Stock Forecast is based on your current time horizon. Although Good Times' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Good Times' systematic risk associated with finding meaningful patterns of Good Times fundamentals over time.
  
As of the 11th of December 2024, Inventory Turnover is likely to grow to 106.94, while Payables Turnover is likely to drop 13.30. . As of the 11th of December 2024, Common Stock Shares Outstanding is likely to grow to about 14.3 M, though Net Loss is likely to grow to (2.3 M).

Open Interest Against 2024-12-20 Good Option Contracts

Although open interest is a measure utilized in the options markets, it could be used to forecast Good Times' spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in Good Times' options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for Good Times stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current Good Times' open interest, investors have to compare it to Good Times' spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of Good Times is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in Good. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.
Simple Regression model is a single variable regression model that attempts to put a straight line through Good Times price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Good Times Simple Regression Price Forecast For the 12th of December 2024

Given 90 days horizon, the Simple Regression forecasted value of Good Times Restaurants on the next trading day is expected to be 2.66 with a mean absolute deviation of 0.06, mean absolute percentage error of 0.01, and the sum of the absolute errors of 3.59.
Please note that although there have been many attempts to predict Good 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 Good Times' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Good Times Stock Forecast Pattern

Backtest Good TimesGood Times Price PredictionBuy or Sell Advice 

Good Times Forecasted Value

In the context of forecasting Good Times' 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. Good Times' downside and upside margins for the forecasting period are 0.17 and 5.16, respectively. We have considered Good Times' 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.
Market Value
2.69
2.66
Expected Value
5.16
Upside

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 Good Times stock data series using in forecasting. Note that when a statistical model is used to represent Good Times 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.
AICAkaike Information Criteria113.0167
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0589
MAPEMean absolute percentage error0.0209
SAESum of the absolute errors3.5933
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Good Times Restaurants historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for Good Times

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Good Times Restaurants. 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.
Hype
Prediction
LowEstimatedHigh
0.222.715.20
Details
Intrinsic
Valuation
LowRealHigh
0.823.315.80
Details
0 Analysts
Consensus
LowTargetHigh
4.555.005.55
Details

Other Forecasting Options for Good Times

For every potential investor in Good, whether a beginner or expert, Good Times' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Good Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Good. Basic forecasting techniques help filter out the noise by identifying Good Times' price trends.

Good Times 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 Good Times stock to make a market-neutral strategy. Peer analysis of Good Times could also be used in its relative valuation, which is a method of valuing Good Times by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Good Times Restaurants Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Good Times' price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Good Times' current price.

Good Times Market Strength Events

Market strength indicators help investors to evaluate how Good Times stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Good Times shares will generate the highest return on investment. By undertsting and applying Good Times stock market strength indicators, traders can identify Good Times Restaurants entry and exit signals to maximize returns.

Good Times Risk Indicators

The analysis of Good Times' 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 Good Times' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting good 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.
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.

Building efficient market-beating portfolios requires time, education, and a lot of computing power!

The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.

Try AI Portfolio Architect
When determining whether Good Times Restaurants is a strong investment it is important to analyze Good Times' competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Good Times' future performance. For an informed investment choice regarding Good Stock, refer to the following important reports:
Check out Historical Fundamental Analysis of Good Times to cross-verify your projections.
You can also try the Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
Is Hotels, Restaurants & Leisure space 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 Good Times. If investors know Good 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 Good Times 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
0.714
Earnings Share
0.1
Revenue Per Share
12.523
Quarterly Revenue Growth
0.065
Return On Assets
0.0104
The market value of Good Times Restaurants is measured differently than its book value, which is the value of Good that is recorded on the company's balance sheet. Investors also form their own opinion of Good Times' value that differs from its market value or its book value, called intrinsic value, which is Good Times' 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 Good Times' market value can be influenced by many factors that don't directly affect Good Times' 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 Good Times' value and its price as these two are different measures arrived at by different means. Investors typically determine if Good Times is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Good Times' 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.