Sangoma Technologies Stock Forecast - Simple Regression
| STC Stock | 6.41 0.19 2.88% |
Sangoma Stock outlook is based on your current time horizon. Although Sangoma Technologies' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Sangoma Technologies' systematic risk associated with finding meaningful patterns of Sangoma Technologies fundamentals over time.
As of today, the relative strength indicator of Sangoma Technologies' share price is approaching 39. This usually implies that the stock is in nutural position, most likellhy at or near its support level. The main point of RSI analysis is to track how fast people are buying or selling Sangoma Technologies, making its price go up or down. Momentum 39
Sell Extended
Oversold | Overbought |
EPS Estimate Next Quarter (0.07) | EPS Estimate Current Year (0.17) | Wall Street Target Price 11.2307 | EPS Estimate Current Quarter (0.06) | Quarterly Revenue Growth (0.15) |
Using Sangoma Technologies hype-based prediction, you can estimate the value of Sangoma Technologies Corp from the perspective of Sangoma Technologies response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Regression forecasted value of Sangoma Technologies Corp on the next trading day is expected to be 6.65 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 10.61. Sangoma Technologies after-hype prediction price | CAD 6.41 |
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.
Sangoma |
Sangoma Technologies Additional Predictive Modules
Most predictive techniques to examine Sangoma price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Sangoma using various technical indicators. When you analyze Sangoma 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 |
Sangoma Technologies Simple Regression Price Forecast For the 29th of January
Given 90 days horizon, the Simple Regression forecasted value of Sangoma Technologies Corp on the next trading day is expected to be 6.65 with a mean absolute deviation of 0.17, mean absolute percentage error of 0.05, and the sum of the absolute errors of 10.61.Please note that although there have been many attempts to predict Sangoma Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Sangoma Technologies' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Sangoma Technologies Stock Forecast Pattern
| Backtest Sangoma Technologies | Sangoma Technologies Price Prediction | Buy or Sell Advice |
Sangoma Technologies Forecasted Value
In the context of forecasting Sangoma Technologies' Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Sangoma Technologies' downside and upside margins for the forecasting period are 4.78 and 8.53, respectively. We have considered Sangoma Technologies' daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of Sangoma Technologies stock data series using in forecasting. Note that when a statistical model is used to represent Sangoma Technologies stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 116.9174 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1712 |
| MAPE | Mean absolute percentage error | 0.0241 |
| SAE | Sum of the absolute errors | 10.6118 |
Predictive Modules for Sangoma Technologies
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Sangoma Technologies Corp. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Sangoma Technologies After-Hype Price Density Analysis
As far as predicting the price of Sangoma Technologies 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 Sangoma Technologies 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 Sangoma Technologies, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Sangoma Technologies Estimiated After-Hype Price Volatility
In the context of predicting Sangoma Technologies' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Sangoma Technologies' historical news coverage. Sangoma Technologies' after-hype downside and upside margins for the prediction period are 4.56 and 8.26, respectively. We have considered Sangoma Technologies' 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
Sangoma Technologies is somewhat reliable at this time. Analysis and calculation of next after-hype price of Sangoma Technologies Corp is based on 3 months time horizon.
Sangoma Technologies Stock Price Outlook Analysis
Have you ever been surprised when a price of a Company such as Sangoma Technologies is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Sangoma Technologies 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 Sangoma Technologies, 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 |
0.11 | 1.88 | 0.01 | 0.02 | 7 Events / Month | 2 Events / Month | In about 7 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
6.41 | 6.41 | 0.00 |
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Sangoma Technologies Hype Timeline
Sangoma Technologies Corp is at this time traded for 6.41on Toronto Exchange of Canada. The entity has historical hype elasticity of 0.01, and average elasticity to hype of competition of -0.02. Sangoma is forecasted 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 forecasted to be very small, whereas the daily expected return is at this time at -0.11%. %. The volatility of related hype on Sangoma Technologies is about 1091.61%, with the expected price after the next announcement by competition of 6.39. About 27.0% of the company outstanding shares are owned by corporate insiders. The company has price-to-book ratio of 0.63. Typically companies with comparable Price to Book (P/B) are able to outperform the market in the long run. Sangoma Technologies Corp recorded a loss per share of 0.22. The entity last dividend was issued on the 17th of February 2006. The firm had 1:7 split on the 8th of November 2021. Assuming the 90 days trading horizon the next forecasted press release will be in about 7 days. Check out Historical Fundamental Analysis of Sangoma Technologies to cross-verify your projections.Sangoma Technologies Related Hype Analysis
Having access to credible news sources related to Sangoma Technologies' direct competition is more important than ever and may enhance your ability to predict Sangoma Technologies' future price movements. Getting to know how Sangoma Technologies' 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 Sangoma Technologies may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| XTRA | Xtract One Technologies | (0.01) | 8 per month | 0.00 | (0.03) | 8.33 | (5.97) | 33.14 | |
| VCM | Vecima Networks | (0.01) | 5 per month | 0.00 | (0.05) | 3.65 | (2.82) | 11.20 | |
| TC | Tucows Inc | (1.14) | 9 per month | 2.63 | 0.09 | 5.66 | (4.40) | 13.41 | |
| WNDR | WonderFi Technologies | (0.01) | 6 per month | 0.00 | (0.05) | 3.85 | (3.70) | 14.14 | |
| HAI | Haivision Systems | 0.05 | 6 per month | 0.91 | 0.25 | 3.82 | (2.52) | 12.30 | |
| DND | Dye Durham | (0.47) | 7 per month | 0.00 | (0.02) | 8.23 | (10.13) | 54.37 | |
| SYZ | Sylogist | (0.16) | 6 per month | 0.00 | (0.1) | 3.42 | (3.23) | 13.34 | |
| IMP | Intermap Technologies Corp | 0.22 | 8 per month | 0.00 | (0.29) | 3.91 | (5.25) | 17.19 | |
| ALYA | Alithya Group inc | (0.02) | 4 per month | 0.00 | (0.08) | 4.09 | (3.45) | 12.58 |
Other Forecasting Options for Sangoma Technologies
For every potential investor in Sangoma, whether a beginner or expert, Sangoma Technologies' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Sangoma Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Sangoma. Basic forecasting techniques help filter out the noise by identifying Sangoma Technologies' price trends.Sangoma Technologies Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Sangoma Technologies stock to make a market-neutral strategy. Peer analysis of Sangoma Technologies could also be used in its relative valuation, which is a method of valuing Sangoma Technologies by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Sangoma Technologies Market Strength Events
Market strength indicators help investors to evaluate how Sangoma Technologies stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Sangoma Technologies shares will generate the highest return on investment. By undertsting and applying Sangoma Technologies stock market strength indicators, traders can identify Sangoma Technologies Corp entry and exit signals to maximize returns.
Sangoma Technologies Risk Indicators
The analysis of Sangoma Technologies' basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Sangoma Technologies' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting sangoma stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 1.36 | |||
| Standard Deviation | 1.93 | |||
| Variance | 3.73 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for Sangoma Technologies
The number of cover stories for Sangoma Technologies depends on current market conditions and Sangoma Technologies' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Sangoma Technologies 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 Sangoma Technologies' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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Sangoma Technologies Short Properties
Sangoma Technologies' future price predictability will typically decrease when Sangoma Technologies' long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Sangoma Technologies Corp often depends not only on the future outlook of the potential Sangoma Technologies' 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. Sangoma Technologies' indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 33.5 M | |
| Cash And Short Term Investments | 13.5 M |
Check out Historical Fundamental Analysis of Sangoma Technologies to cross-verify your projections. You can also try the Portfolio Manager module to state of the art Portfolio Manager to monitor and improve performance of your invested capital.