Uber Technologies Stock Market Value
| UBER Stock | USD 73.40 1.88 2.50% |
| Symbol | Uber |
Uber Technologies Price To Book Ratio
Is Uber Technologies' industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Uber Technologies. If investors know Uber will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Uber Technologies listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 1.269 | Earnings Share 0.87 | Revenue Per Share 18.314 | Quarterly Revenue Growth 0.154 | Return On Assets 0.0196 |
The market value of Uber Technologies is measured differently than its book value, which is the value of Uber that is recorded on the company's balance sheet. Investors also form their own opinion of Uber Technologies' value that differs from its market value or its book value, called intrinsic value, which is Uber Technologies' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Uber Technologies' market value can be influenced by many factors that don't directly affect Uber Technologies' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
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.
Uber Technologies 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Uber Technologies' stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Uber Technologies.
| 04/27/2022 |
| 04/16/2024 |
If you would invest 0.00 in Uber Technologies on April 27, 2022 and sell it all today you would earn a total of 0.00 from holding Uber Technologies or generate 0.0% return on investment in Uber Technologies over 720 days. Uber Technologies is related to or competes with Zoom Video, Snowflake, Workday, C3 Ai, Shopify, Intuit, and Salesforce. Uber Technologies, Inc. develops and operates proprietary technology applications in the United States, Canada, Latin Am... More
Uber Technologies Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Uber Technologies' stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Uber Technologies upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.58 | |||
| Information Ratio | 0.0863 | |||
| Maximum Drawdown | 18.39 | |||
| Value At Risk | (2.52) | |||
| Potential Upside | 2.83 |
Uber Technologies Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Uber Technologies' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Uber Technologies' standard deviation. In reality, there are many statistical measures that can use Uber Technologies historical prices to predict the future Uber Technologies' volatility.| Risk Adjusted Performance | 0.0776 | |||
| Jensen Alpha | 0.1641 | |||
| Total Risk Alpha | 0.0581 | |||
| Sortino Ratio | 0.1342 | |||
| Treynor Ratio | 0.139 |
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.
Uber Technologies Backtested Returns
Uber Technologies appears to be very steady, given 3 months investment horizon. Uber Technologies owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.11, which indicates the firm had a 0.11% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Uber Technologies, which you can use to evaluate the volatility of the company. Please review Uber Technologies' Semi Deviation of 1.35, risk adjusted performance of 0.0776, and Coefficient Of Variation of 894.24 to confirm if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Uber Technologies holds a performance score of 8. The entity has a beta of 1.9, which indicates a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Uber Technologies will likely underperform. Please check Uber Technologies' downside variance, and the relationship between the sortino ratio and accumulation distribution , to make a quick decision on whether Uber Technologies' existing price patterns will revert.
Auto-correlation | 0.61 |
Good predictability
Uber Technologies has good predictability. Overlapping area represents the amount of predictability between Uber Technologies time series from 27th of April 2022 to 22nd of April 2023 and 22nd of April 2023 to 16th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Uber Technologies price movement. The serial correlation of 0.61 indicates that roughly 61.0% of current Uber Technologies price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.61 | |
| Spearman Rank Test | 0.56 | |
| Residual Average | 0.0 | |
| Price Variance | 194.66 |
Uber Technologies lagged returns against current returns
Autocorrelation, which is Uber Technologies stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Uber Technologies' stock expected returns. We can calculate the autocorrelation of Uber Technologies returns to help us make a trade decision. For example, suppose you find that Uber Technologies has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Uber Technologies regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Uber Technologies stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Uber Technologies stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Uber Technologies stock over time.
Current vs Lagged Prices |
| Timeline |
Uber Technologies Lagged Returns
When evaluating Uber Technologies' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Uber Technologies stock have on its future price. Uber Technologies autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Uber Technologies autocorrelation shows the relationship between Uber Technologies stock current value and its past values and can show if there is a momentum factor associated with investing in Uber Technologies.
Regressed Prices |
| Timeline |
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Check out Uber Technologies Correlation, Uber Technologies Volatility and Uber Technologies Alpha and Beta module to complement your research on Uber Technologies. To learn how to invest in Uber Stock, please use our How to Invest in Uber Technologies guide.Note that the Uber Technologies information on this page should be used as a complementary analysis to other Uber Technologies' statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
Complementary 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.
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Uber Technologies technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.