Uber CDR Stock Forward View - Triple Exponential Smoothing

UBER Stock   10.93  -0.23  -2.06%   
The forecast reference data for Uber CDR on this page is generated using Triple Exponential Smoothing applied to historical price observations. Projected values and error measures are included as reference material.
The Triple Exponential Smoothing forecasted value of Uber CDR on the next trading day is expected to be 10.87 with a mean absolute deviation of 0.18 and the sum of the absolute errors of 10.87.As with simple exponential smoothing, in triple exponential smoothing models past Uber CDR observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Uber CDR observations. The Triple Exponential Smoothing reference values for Uber CDR are derived from publicly available price data and should be used for informational purposes only.
Triple exponential smoothing for Uber CDR - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Uber CDR prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in Uber CDR price movement. However, neither of these exponential smoothing models address any seasonality of Uber CDR.

Triple Exponential Smoothing Price Forecast For the 22nd of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Uber CDR on the next trading day is expected to be 10.87 with a mean absolute deviation of 0.18 , mean absolute percentage error of 0.06 , and the sum of the absolute errors of 10.87 .
Please note that although there have been many attempts to predict Uber Stock prices using its time series forecasting, we generally do not suggest 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 CDR's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

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Forecasted Value

The next-day forecast for Uber CDR focuses on identifying predictive downside and upside bands that can frame a realistic trading range. The current forecast range spans downside near 8.85 and upside near 12.89.
Market Value
10.93
10.87
Expected Value
12.89
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Uber CDR stock data series using in forecasting. Note that when a statistical model is used to represent Uber CDR 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 CriteriaHuge
BiasArithmetic mean of the errors -0.0415
MADMean absolute deviation0.1812
MAPEMean absolute percentage error0.0158
SAESum of the absolute errors10.87
As with simple exponential smoothing, in triple exponential smoothing models past Uber CDR observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Uber CDR observations.

Other Forecasting Options for Uber CDR

Investors at all stages of experience who consider Uber must develop an understanding of Uber CDR's price dynamics. The noise embedded in Uber Stock price charts can create misleading signals and skew investment decisions.

Uber CDR Related Equities

The following equities are related to Uber CDR and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Uber CDR against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
 Risk & Return  Correlation

Uber CDR Market Strength Events

Market strength indicators applied to Uber CDR stock give investors a structured view of the security's momentum relative to the overall market. Using these indicators, traders can refine their timing when entering or exiting positions in Uber CDR.

Uber CDR Risk Indicators

Evaluating Uber CDR's risk indicators is an important step in accurately forecasting its price and assessing the suitability of an investment. Understanding the risk profile of Uber CDR's allows investors to make more informed decisions about position sizing and risk.
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 Uber CDR

A coverage review of Uber CDR shows when the security is attracting above-average attention from contributors and market observers. The practical risk is that faster visibility can increase both interest and skepticism at the same time.

Other Macroaxis Stories

Macroaxis publishes story content for a diverse readership that includes finance students, independent investors, money managers, and market-focused operating teams. What connects that audience is a focus on building stronger portfolios through better research, risk awareness, and comparative analysis.

More Resources for Uber Stock Analysis

Other Information on Investing in Uber Stock

The ratio set for Uber CDR connects key financial figures across reports. These metrics link profitability, liquidity, and valuation signals.