Guess Stock Forecast - Polynomial Regression

GES Stock  USD 16.63  0.43  2.65%   
The Polynomial Regression forecasted value of Guess Inc on the next trading day is expected to be 16.10 with a mean absolute deviation of 0.41 and the sum of the absolute errors of 25.46. Guess Stock Forecast is based on your current time horizon.
  
At this time, Guess' Inventory Turnover is comparatively stable compared to the past year. Receivables Turnover is likely to gain to 8.88 in 2024, whereas Payables Turnover is likely to drop 5.67 in 2024. . Common Stock Shares Outstanding is likely to drop to about 67.9 M in 2024. Net Income Applicable To Common Shares is likely to drop to about 84.2 M in 2024.
Guess polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Guess Inc as well as the accuracy indicators are determined from the period prices.

Guess Polynomial Regression Price Forecast For the 23rd of November

Given 90 days horizon, the Polynomial Regression forecasted value of Guess Inc on the next trading day is expected to be 16.10 with a mean absolute deviation of 0.41, mean absolute percentage error of 0.25, and the sum of the absolute errors of 25.46.
Please note that although there have been many attempts to predict Guess 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 Guess' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Guess Stock Forecast Pattern

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Guess Forecasted Value

In the context of forecasting Guess' 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. Guess' downside and upside margins for the forecasting period are 14.07 and 18.13, respectively. We have considered Guess' 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
16.63
16.10
Expected Value
18.13
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Guess stock data series using in forecasting. Note that when a statistical model is used to represent Guess 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 Criteria118.5645
BiasArithmetic mean of the errors None
MADMean absolute deviation0.4106
MAPEMean absolute percentage error0.022
SAESum of the absolute errors25.4577
A single variable polynomial regression model attempts to put a curve through the Guess historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Guess

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Guess Inc. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Guess' 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.
Hype
Prediction
LowEstimatedHigh
14.6716.6918.71
Details
Intrinsic
Valuation
LowRealHigh
14.9719.5121.53
Details
Bollinger
Band Projection (param)
LowMiddleHigh
16.2016.9817.76
Details
4 Analysts
Consensus
LowTargetHigh
24.8427.3030.30
Details

Other Forecasting Options for Guess

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

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 Risk & Return  Correlation

Guess Inc 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 Guess' 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 Guess' current price.

Guess Market Strength Events

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

Guess Risk Indicators

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

Thematic Opportunities

Explore Investment Opportunities

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Additional Tools for Guess Stock Analysis

When running Guess' price analysis, check to measure Guess' 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 Guess is operating at the current time. Most of Guess' value examination focuses on studying past and present price action to predict the probability of Guess' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Guess' price. Additionally, you may evaluate how the addition of Guess to your portfolios can decrease your overall portfolio volatility.