Oxford Metrics (UK) Price Prediction
| OMG Stock | 64.20 2.20 3.55% |
Oversold Vs Overbought
55
Oversold | Overbought |
Quarterly Earnings Growth (0.57) | EPS Estimate Current Year 0.0216 | EPS Estimate Next Year 0.029 | Wall Street Target Price 107.5 | Quarterly Revenue Growth 0.105 |
Using Oxford Metrics hype-based prediction, you can estimate the value of Oxford Metrics plc from the perspective of Oxford Metrics response to recently generated media hype and the effects of current headlines on its competitors.
The fear of missing out, i.e., FOMO, can cause potential investors in Oxford Metrics to buy its stock at a price that has no basis in reality. In that case, they are not buying Oxford 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.
Oxford Metrics after-hype prediction price | GBX 64.46 |
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.
Oxford |
Oxford Metrics After-Hype Price Prediction Density Analysis
As far as predicting the price of Oxford Metrics 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 Oxford Metrics 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 Oxford Metrics, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Oxford Metrics Estimiated After-Hype Price Volatility
In the context of predicting Oxford Metrics' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Oxford Metrics' historical news coverage. Oxford Metrics' after-hype downside and upside margins for the prediction period are 60.89 and 68.03, respectively. We have considered Oxford Metrics' 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
Oxford Metrics is very steady at this time. Analysis and calculation of next after-hype price of Oxford Metrics plc is based on 3 months time horizon.
Oxford Metrics Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Oxford Metrics is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Oxford Metrics 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 Oxford Metrics, 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 |
0.32 | 3.57 | 0.26 | 9.18 | 4 Events / Month | 1 Events / Month | In about 4 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
64.20 | 64.46 | 0.40 |
|
Oxford Metrics Hype Timeline
Oxford Metrics plc is now traded for 64.20on London Exchange of UK. The entity has historical hype elasticity of 0.26, and average elasticity to hype of competition of -9.18. Oxford is forecasted to increase in value after the next headline, with the price projected to jump to 64.46 or above. The average volatility of media hype impact on the company the price is over 100%. The price growth on the next news is projected to be 0.4%, whereas the daily expected return is now at -0.32%. The volatility of related hype on Oxford Metrics is about 12.44%, with the expected price after the next announcement by competition of 55.02. The company reported the revenue of 44.24 M. Net Income was 5.66 M with profit before overhead, payroll, taxes, and interest of 19.46 M. Assuming the 90 days trading horizon the next forecasted press release will be in about 4 days. Check out Oxford Metrics Basic Forecasting Models to cross-verify your projections.Oxford Metrics Related Hype Analysis
Having access to credible news sources related to Oxford Metrics' direct competition is more important than ever and may enhance your ability to predict Oxford Metrics' future price movements. Getting to know how Oxford Metrics' 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 Oxford Metrics may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| GRX | GreenX Metals | 0.00 | 2 per month | 0.00 | (0.03) | 4.48 | (4.76) | 44.49 | |
| 0R1G | Home Depot | (227.53) | 2 per month | 0.00 | (0.39) | 0.00 | 0.00 | 1.28 | |
| 0QZ2 | Silvercorp Metals | 0.03 | 3 per month | 0.00 | (0.05) | 5.96 | (6.39) | 27.96 | |
| POW | Power Metal Resources | (0.90) | 3 per month | 0.00 | (0.05) | 5.26 | (6.03) | 17.14 | |
| 0QT5 | Gaztransport et Technigaz | (0.40) | 2 per month | 1.05 | (0.03) | 2.82 | (1.83) | 5.95 | |
| 0R8S | Infrastrutture Wireless Italiane | 0.00 | 0 per month | 0.00 | (0.24) | 1.37 | (1.55) | 7.55 | |
| 0HEJ | American Homes 4 | (0.24) | 3 per month | 1.22 | (0.1) | 2.04 | (1.88) | 5.71 | |
| SVML | Sovereign Metals | (0.50) | 3 per month | 1.54 | 0.09 | 7.46 | (2.78) | 13.81 |
Oxford Metrics Additional Predictive Modules
Most predictive techniques to examine Oxford price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Oxford using various technical indicators. When you analyze Oxford 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 Oxford Metrics Predictive Indicators
The successful prediction of Oxford Metrics 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 Oxford Metrics plc, 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 Oxford Metrics based on analysis of Oxford Metrics hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Oxford Metrics's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Oxford Metrics's related companies.
Story Coverage note for Oxford Metrics
The number of cover stories for Oxford Metrics depends on current market conditions and Oxford Metrics' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Oxford Metrics 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 Oxford Metrics' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios
Story Categories
Currently Trending Categories
Oxford Metrics Short Properties
Oxford Metrics' future price predictability will typically decrease when Oxford Metrics' long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Oxford Metrics plc often depends not only on the future outlook of the potential Oxford Metrics' 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. Oxford Metrics' indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 131.1 M | |
| Cash And Short Term Investments | 66 M |
Complementary Tools for Oxford Stock analysis
When running Oxford Metrics' price analysis, check to measure Oxford Metrics' 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 Oxford Metrics is operating at the current time. Most of Oxford Metrics' value examination focuses on studying past and present price action to predict the probability of Oxford Metrics' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Oxford Metrics' price. Additionally, you may evaluate how the addition of Oxford Metrics to your portfolios can decrease your overall portfolio volatility.
| Analyst Advice Analyst recommendations and target price estimates broken down by several categories | |
| Theme Ratings Determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
| Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
| Portfolio File Import Quickly import all of your third-party portfolios from your local drive in csv format | |
| FinTech Suite Use AI to screen and filter profitable investment opportunities | |
| Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
| Global Correlations Find global opportunities by holding instruments from different markets |