Service Properties Trust Stock Market Value
SVC Stock | USD 2.83 0.04 1.43% |
Symbol | Service |
Service Properties Trust Price To Book Ratio
Is Diversified REITs space 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 Service Properties. If investors know Service 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 Service Properties 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 (0.66) | Dividend Share 0.61 | Earnings Share (1.47) | Revenue Per Share 11.405 | Quarterly Revenue Growth (0.01) |
The market value of Service Properties Trust is measured differently than its book value, which is the value of Service that is recorded on the company's balance sheet. Investors also form their own opinion of Service Properties' value that differs from its market value or its book value, called intrinsic value, which is Service Properties' 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 Service Properties' market value can be influenced by many factors that don't directly affect Service Properties' 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 Service Properties' value and its price as these two are different measures arrived at by different means. Investors typically determine if Service Properties is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Service Properties' 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.
Service Properties '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 Service Properties' 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 Service Properties.
11/04/2024 |
| 12/04/2024 |
If you would invest 0.00 in Service Properties on November 4, 2024 and sell it all today you would earn a total of 0.00 from holding Service Properties Trust or generate 0.0% return on investment in Service Properties over 30 days. Service Properties is related to or competes with Sphere Entertainment, Arrow Electronics, National CineMedia, Semtech, Canlan Ice, Bel Fuse, and Ryman Hospitality. Service Properties Trust is a real estate investment trust, or REIT, which owns a diverse portfolio of hotels and net le... More
Service Properties 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 Service Properties' 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 Service Properties Trust upside and downside potential and time the market with a certain degree of confidence.
Information Ratio | (0.20) | |||
Maximum Drawdown | 23.1 | |||
Value At Risk | (5.79) | |||
Potential Upside | 5.02 |
Service Properties Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Service Properties' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Service Properties' standard deviation. In reality, there are many statistical measures that can use Service Properties historical prices to predict the future Service Properties' volatility.Risk Adjusted Performance | (0.12) | |||
Jensen Alpha | (0.87) | |||
Total Risk Alpha | (1.22) | |||
Treynor Ratio | (0.40) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Service Properties' 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.
Service Properties Trust Backtested Returns
Service Properties Trust owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.17, which indicates the firm had a -0.17% return per unit of risk over the last 3 months. Service Properties Trust exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Service Properties' Risk Adjusted Performance of (0.12), variance of 15.53, and Coefficient Of Variation of (578.75) to confirm the risk estimate we provide. The entity has a beta of 1.73, 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, Service Properties will likely underperform. At this point, Service Properties Trust has a negative expected return of -0.67%. Please make sure to validate Service Properties' maximum drawdown, accumulation distribution, as well as the relationship between the Accumulation Distribution and market facilitation index , to decide if Service Properties Trust performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.17 |
Insignificant reverse predictability
Service Properties Trust has insignificant reverse predictability. Overlapping area represents the amount of predictability between Service Properties time series from 4th of November 2024 to 19th of November 2024 and 19th of November 2024 to 4th 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 Service Properties Trust price movement. The serial correlation of -0.17 indicates that over 17.0% of current Service Properties price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.17 | |
Spearman Rank Test | -0.68 | |
Residual Average | 0.0 | |
Price Variance | 0.01 |
Service Properties Trust lagged returns against current returns
Autocorrelation, which is Service Properties 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 Service Properties' stock expected returns. We can calculate the autocorrelation of Service Properties returns to help us make a trade decision. For example, suppose you find that Service Properties 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 |
Service Properties 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 Service Properties stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Service Properties stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Service Properties stock over time.
Current vs Lagged Prices |
Timeline |
Service Properties Lagged Returns
When evaluating Service Properties' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Service Properties stock have on its future price. Service Properties 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, Service Properties autocorrelation shows the relationship between Service Properties stock current value and its past values and can show if there is a momentum factor associated with investing in Service Properties Trust.
Regressed Prices |
Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether Service Properties Trust offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Service Properties' financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Service Properties Trust Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Service Properties Trust Stock:Check out Service Properties Correlation, Service Properties Volatility and Service Properties Alpha and Beta module to complement your research on Service Properties. You can also try the Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
Service Properties 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.