Automotive Properties Real Stock Price Prediction
| APR-UN Stock | CAD 11.42 0.08 0.71% |
Momentum 75
Buy Stretched
Oversold | Overbought |
Quarterly Earnings Growth 4.07 | EPS Estimate Current Year 0.62 | EPS Estimate Next Year 1.02 | Wall Street Target Price 12.575 | Quarterly Revenue Growth 0.079 |
Using Automotive Properties hype-based prediction, you can estimate the value of Automotive Properties Real from the perspective of Automotive Properties 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 Automotive Properties to buy its stock at a price that has no basis in reality. In that case, they are not buying Automotive 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.
Automotive Properties after-hype prediction price | CAD 11.42 |
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.
Automotive |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Automotive 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.
Automotive Properties After-Hype Price Prediction Density Analysis
As far as predicting the price of Automotive 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 Automotive 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 Automotive Properties, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Automotive Properties Estimiated After-Hype Price Volatility
In the context of predicting Automotive Properties' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Automotive Properties' historical news coverage. Automotive Properties' after-hype downside and upside margins for the prediction period are 10.83 and 12.01, respectively. We have considered Automotive 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
Automotive Properties is very steady at this time. Analysis and calculation of next after-hype price of Automotive Properties is based on 3 months time horizon.
Automotive Properties Stock Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Automotive Properties is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Automotive 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 Automotive 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 |
0.08 | 0.59 | 0.00 | 0.00 | 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 | ||
11.42 | 11.42 | 0.00 |
|
Automotive Properties Hype Timeline
Automotive Properties is presently traded for 11.42on Toronto Exchange of Canada. The entity stock is not elastic to its hype. The average elasticity to hype of competition is 0.0. Automotive is projected 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 projected to be very small, whereas the daily expected return is presently at 0.08%. %. The volatility of related hype on Automotive Properties is about 4916.67%, with the expected price after the next announcement by competition of 11.42. About 49.0% of the company shares are held by company insiders. The company has price-to-book (P/B) ratio of 0.93. Some equities with similar Price to Book (P/B) outperform the market in the long run. Automotive Properties last dividend was issued on the 30th of January 2026. The entity had 959:1000 split on the 31st of December 2024. Assuming the 90 days trading horizon the next projected press release will be in about 7 days. Check out Automotive Properties Basic Forecasting Models to cross-verify your projections.Automotive Properties Related Hype Analysis
Having access to credible news sources related to Automotive Properties' direct competition is more important than ever and may enhance your ability to predict Automotive Properties' future price movements. Getting to know how Automotive 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 Automotive Properties may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| NXR-UN | Nexus Real Estate | (0.03) | 3 per month | 1.13 | (0.01) | 1.84 | (2.03) | 5.66 | |
| MI-UN | Minto Apartment Real | 0.01 | 5 per month | 0.28 | 0.10 | 1.64 | (1.47) | 27.63 | |
| WFC | Wall Financial | 0.00 | 7 per month | 1.42 | 0.04 | 3.99 | (2.95) | 14.07 | |
| PLZ-UN | Plaza Retail REIT | (0.06) | 8 per month | 0.69 | 0.02 | 1.47 | (1.49) | 5.21 | |
| AX-UN | Artis Real Estate | 0.25 | 9 per month | 1.47 | 0.32 | 4.18 | (1.66) | 18.40 | |
| MRG-UN | Morguard North American | (0.32) | 4 per month | 0.81 | 0.01 | 1.64 | (1.41) | 4.18 | |
| PRV-UN | Pro Real Estate | 0.04 | 2 per month | 0.65 | 0.13 | 1.52 | (1.23) | 5.72 | |
| HOM-U | BSR Real Estate | (0.03) | 4 per month | 1.68 | 0.01 | 3.22 | (2.96) | 10.39 | |
| BTB-UN | BTB Real Estate | 0.02 | 8 per month | 0.58 | 0.13 | 1.05 | (0.78) | 3.93 | |
| MRT-UN | Morguard Real Estate | 0.24 | 5 per month | 0.63 | 0.11 | 1.76 | (1.55) | 6.12 |
Automotive Properties Additional Predictive Modules
Most predictive techniques to examine Automotive price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Automotive using various technical indicators. When you analyze Automotive 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 Automotive Properties Predictive Indicators
The successful prediction of Automotive 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 Automotive Properties Real, 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 Automotive Properties based on analysis of Automotive Properties hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Automotive Properties's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Automotive Properties's related companies. | 2023 | 2024 | 2025 | 2026 (projected) | Dividend Yield | 0.0746 | 0.0738 | 0.0849 | 0.087 | Price To Sales Ratio | 5.72 | 5.69 | 6.55 | 11.91 |
Pair Trading with Automotive Properties
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Automotive Properties position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Automotive Properties will appreciate offsetting losses from the drop in the long position's value.Moving together with Automotive Stock
| 0.86 | BNP | BNP Paribas CDR | PairCorr |
| 0.76 | CITI | CITIGROUP CDR | PairCorr |
| 0.78 | RY | Royal Bank | PairCorr |
| 0.84 | TD | Toronto Dominion Bank | PairCorr |
The ability to find closely correlated positions to Automotive Properties could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Automotive Properties when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Automotive Properties - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Automotive Properties Real to buy it.
The correlation of Automotive Properties is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Automotive Properties moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Automotive Properties moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Automotive Properties can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Complementary Tools for Automotive Stock analysis
When running Automotive Properties' price analysis, check to measure Automotive 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 Automotive Properties is operating at the current time. Most of Automotive Properties' value examination focuses on studying past and present price action to predict the probability of Automotive Properties' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Automotive Properties' price. Additionally, you may evaluate how the addition of Automotive Properties to your portfolios can decrease your overall portfolio volatility.
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