Uber Technologies Stock Forecast - 20 Period Moving Average
| UT8 Stock | 58.70 0.76 1.31% |
The 20 Period Moving Average forecasted value of Uber Technologies on the next trading day is expected to be 62.58 with a mean absolute deviation of 3.72 and the sum of the absolute errors of 152.52. Uber Stock Forecast is based on your current time horizon.
Uber |
Uber Technologies 20 Period Moving Average Price Forecast For the 24th of December
Given 90 days horizon, the 20 Period Moving Average forecasted value of Uber Technologies on the next trading day is expected to be 62.58 with a mean absolute deviation of 3.72, mean absolute percentage error of 19.78, and the sum of the absolute errors of 152.52.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 59.53 and 65.63, 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 20 Period Moving Average 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 | 84.3376 |
| Bias | Arithmetic mean of the errors | 3.2691 |
| MAD | Mean absolute deviation | 3.7201 |
| MAPE | Mean absolute percentage error | 0.0592 |
| SAE | Sum of the absolute errors | 152.524 |
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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Uber Technologies' 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.
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 | 1.98 | |||
| Standard Deviation | 3.05 | |||
| Variance | 9.31 |
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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Additional Tools for Uber Stock Analysis
When running Uber Technologies' price analysis, check to measure Uber Technologies' 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 Uber Technologies is operating at the current time. Most of Uber Technologies' value examination focuses on studying past and present price action to predict the probability of Uber Technologies' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Uber Technologies' price. Additionally, you may evaluate how the addition of Uber Technologies to your portfolios can decrease your overall portfolio volatility.