USS (Germany) Market Value
USV Stock | EUR 8.35 0.05 0.60% |
Symbol | USS |
USS '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 USS's 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 USS.
01/02/2023 |
| 12/22/2024 |
If you would invest 0.00 in USS on January 2, 2023 and sell it all today you would earn a total of 0.00 from holding USS Co or generate 0.0% return on investment in USS over 720 days. USS is related to or competes with Copart, Zhongsheng Group, DIeteren Group, Penske Automotive, Lithia Motors, AutoNation, and Asbury Automotive. USS Co., Ltd., together with its subsidiaries, operates and manages used vehicle auction sites in Japan More
USS 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 USS's 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 USS Co upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.5 | |||
Information Ratio | (0.01) | |||
Maximum Drawdown | 6.62 | |||
Value At Risk | (2.38) | |||
Potential Upside | 2.44 |
USS Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for USS's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as USS's standard deviation. In reality, there are many statistical measures that can use USS historical prices to predict the future USS's volatility.Risk Adjusted Performance | 0.0147 | |||
Jensen Alpha | 0.0026 | |||
Total Risk Alpha | (0.03) | |||
Sortino Ratio | (0.01) | |||
Treynor Ratio | 0.0327 |
USS Co Backtested Returns
At this point, USS is not too volatile. USS Co owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0271, which indicates the firm had a 0.0271% return per unit of standard deviation over the last 3 months. We have found twenty-eight technical indicators for USS Co, which you can use to evaluate the volatility of the company. Please validate USS's coefficient of variation of 7473.53, and Risk Adjusted Performance of 0.0147 to confirm if the risk estimate we provide is consistent with the expected return of 0.0363%. USS has a performance score of 2 on a scale of 0 to 100. The entity has a beta of 0.25, which indicates not very significant fluctuations relative to the market. As returns on the market increase, USS's returns are expected to increase less than the market. However, during the bear market, the loss of holding USS is expected to be smaller as well. USS Co presently has a risk of 1.34%. Please validate USS semi variance, daily balance of power, and the relationship between the potential upside and skewness , to decide if USS will be following its existing price patterns.
Auto-correlation | 0.21 |
Weak predictability
USS Co has weak predictability. Overlapping area represents the amount of predictability between USS time series from 2nd of January 2023 to 28th of December 2023 and 28th of December 2023 to 22nd of December 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 USS Co price movement. The serial correlation of 0.21 indicates that over 21.0% of current USS price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.21 | |
Spearman Rank Test | 0.09 | |
Residual Average | 0.0 | |
Price Variance | 0.26 |
USS Co lagged returns against current returns
Autocorrelation, which is USS 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 USS's stock expected returns. We can calculate the autocorrelation of USS returns to help us make a trade decision. For example, suppose you find that USS 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 |
USS 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 USS stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if USS stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in USS stock over time.
Current vs Lagged Prices |
Timeline |
USS Lagged Returns
When evaluating USS's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of USS stock have on its future price. USS 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, USS autocorrelation shows the relationship between USS stock current value and its past values and can show if there is a momentum factor associated with investing in USS Co.
Regressed Prices |
Timeline |
Currently Active Assets on Macroaxis
Other Information on Investing in USS Stock
USS financial ratios help investors to determine whether USS Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in USS with respect to the benefits of owning USS security.