Uber Technologies Stock Forecast - Polynomial Regression

0A1U Stock  USD 70.50  1.30  1.88%   
The Polynomial Regression forecasted value of Uber Technologies on the next trading day is expected to be 69.84 with a mean absolute deviation of 0.10 and the sum of the absolute errors of 6.22. Uber Stock Forecast is based on your current time horizon.
  
Uber Technologies polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Uber Technologies as well as the accuracy indicators are determined from the period prices.

Uber Technologies Polynomial Regression Price Forecast For the 24th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Uber Technologies on the next trading day is expected to be 69.84 with a mean absolute deviation of 0.10, mean absolute percentage error of 0.03, and the sum of the absolute errors of 6.22.
Please note that although there have been many attempts to predict Uber 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 Uber Technologies' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Uber Technologies Stock Forecast Pattern

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Uber Technologies Forecasted Value

In the context of forecasting Uber Technologies' 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. Uber Technologies' downside and upside margins for the forecasting period are 69.20 and 70.48, respectively. We have considered Uber Technologies' 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
70.50
69.84
Expected Value
70.48
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 Uber Technologies stock data series using in forecasting. Note that when a statistical model is used to represent Uber Technologies 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 Criteria114.6871
BiasArithmetic mean of the errors None
MADMean absolute deviation0.102
MAPEMean absolute percentage error0.0015
SAESum of the absolute errors6.2208
A single variable polynomial regression model attempts to put a curve through the Uber Technologies 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 Uber Technologies

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Uber Technologies. 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
69.8670.5071.14
Details
Intrinsic
Valuation
LowRealHigh
69.5470.1770.82
Details
Bollinger
Band Projection (param)
LowMiddleHigh
68.8470.0771.29
Details

Other Forecasting Options for Uber Technologies

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

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

Uber Technologies 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 Uber Technologies' 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 Uber Technologies' current price.

Uber Technologies Market Strength Events

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

Uber Technologies Risk Indicators

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

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When determining whether Uber Technologies is a strong investment it is important to analyze Uber Technologies' 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 Uber Technologies' future performance. For an informed investment choice regarding Uber Stock, refer to the following important reports:
Check out Historical Fundamental Analysis of Uber Technologies to cross-verify your projections.
For more information on how to buy Uber Stock please use our How to buy in Uber Stock guide.
You can also try the Fundamentals Comparison module to compare fundamentals across multiple equities to find investing opportunities.
Please note, there is a significant difference between Uber Technologies' value and its price as these two are different measures arrived at by different means. Investors typically determine if Uber Technologies is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Uber Technologies' 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.