Uber Technologies Stock Forecast - Double Exponential Smoothing
| 0A1U Stock | USD 70.50 1.30 1.88% |
The Double Exponential Smoothing forecasted value of Uber Technologies on the next trading day is expected to be 71.15 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.30. Uber Stock Forecast is based on your current time horizon.
Uber |
Uber Technologies Double Exponential Smoothing Price Forecast For the 25th of November
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Uber Technologies on the next trading day is expected to be 71.15 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.03, and the sum of the absolute errors of 1.30.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
| Backtest Uber Technologies | Uber Technologies Price Prediction | Buy or Sell Advice |
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 70.51 and 71.79, 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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing 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.| AIC | Akaike Information Criteria | Huge |
| Bias | Arithmetic mean of the errors | -0.022 |
| MAD | Mean absolute deviation | 0.022 |
| MAPE | Mean absolute percentage error | 3.0E-4 |
| SAE | Sum of the absolute errors | 1.3 |
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.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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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.
| Mean Deviation | 0.2087 | |||
| Standard Deviation | 0.8987 | |||
| Variance | 0.8076 |
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 ArchitectCheck 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.