Service Properties Trust Stock Price Prediction
| SVC Stock | USD 4.90 0.06 1.21% |
Oversold Vs Overbought
46
Oversold | Overbought |
Quarterly Earnings Growth (0.66) | EPS Estimate Current Year (1.13) | EPS Estimate Next Year (0.92) | Wall Street Target Price 5.83 | Quarterly Revenue Growth 0.018 |
Using Service Properties hype-based prediction, you can estimate the value of Service Properties Trust from the perspective of Service Properties response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards Service Properties using Service Properties' stock options and short interest. It helps to benchmark the overall future attitude of investors towards Service using crowd psychology based on the activity and movement of Service Properties' stock price.
Service Properties Short Interest
A significant increase or decrease in Service Properties' short interest from the previous month could be a good indicator of investor sentiment towards Service. Short interest can provide insight into the potential direction of Service Properties stock and how bullish or bearish investors feel about the market overall.
200 Day MA 6.274 | Short Percent 0.0811 | Short Ratio 6.67 | Shares Short Prior Month 9.2 M | 50 Day MA 4.9862 |
Service Properties Trust Hype to Price Pattern
Investor biases related to Service Properties' public news can be used to forecast risks associated with an investment in Service. The trend in average sentiment can be used to explain how an investor holding Service can time the market purely based on public headlines and social activities around Service Properties Trust. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Some investors profit by finding stocks that are overvalued or undervalued based on market sentiment. The correlation of Service Properties' market sentiment to its price can help taders to make decisions based on the overall investors consensus about Service Properties.
Service Properties Implied Volatility | 0.0 |
Service Properties' implied volatility exposes the market's sentiment of Service Properties Trust stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Service Properties' implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Service Properties stock will not fluctuate a lot when Service Properties' options are near their expiration.
The fear of missing out, i.e., FOMO, can cause potential investors in Service Properties to buy its stock at a price that has no basis in reality. In that case, they are not buying Service because the equity is a good investment, but because they need to do something to avoid the feeling of missing out. On the other hand, investors will often sell stocks at prices well below their value during bear markets because they need to stop feeling the pain of losing money.
Service Properties after-hype prediction price | USD 4.92 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Service |
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 After-Hype Price Prediction Density Analysis
As far as predicting the price of Service Properties at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Service Properties or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of Service Properties, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Service Properties Estimiated After-Hype Price Volatility
In the context of predicting Service Properties' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Service Properties' historical news coverage. Service Properties' after-hype downside and upside margins for the prediction period are 2.06 and 7.78, respectively. We have considered Service Properties' daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Service Properties is slightly risky at this time. Analysis and calculation of next after-hype price of Service Properties Trust is based on 3 months time horizon.
Service Properties Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Service Properties is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Service Properties backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Service Properties, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.04 | 2.86 | 0.00 | 0.09 | 8 Events / Month | 3 Events / Month | In about 8 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
4.90 | 4.92 | 0.00 |
|
Service Properties Hype Timeline
On the 20th of September Service Properties Trust is traded for 4.90. The entity stock is not elastic to its hype. The average elasticity to hype of competition is 0.09. Service is anticipated not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is over 100%. The immediate return on the next news is anticipated to be very small, whereas the daily expected return is at this time at 0.04%. %. The volatility of related hype on Service Properties is about 126.44%, with the expected price after the next announcement by competition of 4.99. About 79.0% of the company shares are owned by institutional investors. The company has price-to-book ratio of 0.76. Typically companies with comparable Price to Book (P/B) are able to outperform the market in the long run. Service Properties Trust recorded a loss per share of 1.21. The entity last dividend was issued on the 22nd of July 2024. Considering the 90-day investment horizon the next anticipated press release will be in about 8 days. Check out Service Properties Basic Forecasting Models to cross-verify your projections.Service Properties Related Hype Analysis
Having access to credible news sources related to Service Properties' direct competition is more important than ever and may enhance your ability to predict Service Properties' future price movements. Getting to know how Service Properties' peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Service Properties may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| RHE | Regional Health Properties | (0.02) | 1 per month | 0.00 | (0.15) | 4.37 | (4.59) | 14.15 | |
| SSY | SunLink Health Systems | 0.05 | 4 per month | 4.35 | 0.02 | 5.33 | (5.00) | 38.01 | |
| MSTSX | Morningstar Unconstrained Allocation | (0.06) | 1 per month | 0.62 | (0.02) | 1.21 | (1.22) | 4.07 | |
| LIDR | Aeye Inc | 0.18 | 6 per month | 0.00 | (0.18) | 8.93 | (9.52) | 28.97 | |
| MLGF | Malaga Financial | 0.00 | 0 per month | 0.45 | (0.16) | 1.20 | (0.70) | 4.13 | |
| COKE | Coca Cola Consolidated | 22.56 | 11 per month | 1.42 | 0.12 | 3.45 | (1.61) | 13.02 | |
| SCAXX | Schwab California Municipal | 0.00 | 0 per month | 0.00 | (0.51) | 0.00 | 0.00 | 2.01 | |
| FPCG | First Physicians Capital | 0.00 | 0 per month | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
| DALI | First Trust Dorsey | 0.05 | 3 per month | 1.56 | (0.04) | 2.24 | (3.16) | 7.30 | |
| LICY | LiCycle Holdings Corp | (0.14) | 7 per month | 0.00 | (0.08) | 14.15 | (10.56) | 52.80 |
Service Properties Additional Predictive Modules
Most predictive techniques to examine Service price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Service using various technical indicators. When you analyze Service charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Service Properties Predictive Indicators
The successful prediction of Service Properties stock price could yield a significant profit to investors. But is it possible? The efficient-market hypothesis suggests that all published stock prices of traded companies, such as Service Properties Trust, already reflect all publicly available information. This academic statement is a fundamental principle of many financial and investing theories used today. However, the typical investor usually disagrees with a 'textbook' version of this hypothesis and continually tries to find mispriced stocks to increase returns. We use internally-developed statistical techniques to arrive at the intrinsic value of Service Properties based on analysis of Service Properties hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Service Properties's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Service Properties's related companies. | 2021 | 2022 | 2023 | 2024 (projected) | Dividend Yield | 0.00456 | 0.0317 | 0.094 | 0.0905 | Price To Sales Ratio | 0.97 | 0.64 | 0.75 | 0.71 |
Story Coverage note for Service Properties
The number of cover stories for Service Properties depends on current market conditions and Service Properties' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Service Properties is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Service Properties' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Contributor Headline
Latest Perspective From Macroaxis
Service Properties Short Properties
Service Properties' future price predictability will typically decrease when Service Properties' long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Service Properties Trust often depends not only on the future outlook of the potential Service Properties' investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. Service Properties' indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 165 M | |
| Cash And Short Term Investments | 197.8 M |
Complementary Tools for Service Stock analysis
When running Service Properties' price analysis, check to measure Service Properties' 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 Service Properties is operating at the current time. Most of Service Properties' value examination focuses on studying past and present price action to predict the probability of Service Properties' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Service Properties' price. Additionally, you may evaluate how the addition of Service Properties to your portfolios can decrease your overall portfolio volatility.
| Competition Analyzer Analyze and compare many basic indicators for a group of related or unrelated entities | |
| My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
| Price Transformation Use Price Transformation models to analyze the depth of different equity instruments across global markets | |
| Pair Correlation Compare performance and examine fundamental relationship between any two equity instruments |