Automotive Properties Real Stock Technical Analysis
| APR-UN Stock | CAD 11.74 0.15 1.29% |
As of the 5th of March, Automotive Properties shows the Mean Deviation of 0.4285, risk adjusted performance of 0.1507, and Downside Deviation of 0.65. Automotive Properties technical analysis gives you the methodology to make use of historical prices and volume patterns to determine a pattern that approximates the direction of the firm's future prices.
Automotive Properties Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Automotive, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to AutomotiveAutomotive |
Automotive 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 Automotive 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 Automotive Properties.
| 12/05/2025 |
| 03/05/2026 |
If you would invest 0.00 in Automotive Properties on December 5, 2025 and sell it all today you would earn a total of 0.00 from holding Automotive Properties Real or generate 0.0% return on investment in Automotive Properties over 90 days. Automotive Properties is related to or competes with Parkit Enterprise, Invesque, Bridgemarq Real, Urbanfund Corp, Firm Capital, Genesis Land, and Halmont Properties. Automotive Properties REIT is an unincorporated, open-ended real estate investment trust focused on owning and acquiring... More
Automotive 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 Automotive 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 Automotive Properties Real upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.65 | |||
| Information Ratio | 0.134 | |||
| Maximum Drawdown | 3.88 | |||
| Value At Risk | (0.94) | |||
| Potential Upside | 1.19 |
Automotive Properties Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Automotive Properties' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Automotive Properties' standard deviation. In reality, there are many statistical measures that can use Automotive Properties historical prices to predict the future Automotive Properties' volatility.| Risk Adjusted Performance | 0.1507 | |||
| Jensen Alpha | 0.1174 | |||
| Total Risk Alpha | 0.0911 | |||
| Sortino Ratio | 0.1325 | |||
| Treynor Ratio | 1.46 |
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 March 5, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.1507 | |||
| Market Risk Adjusted Performance | 1.47 | |||
| Mean Deviation | 0.4285 | |||
| Semi Deviation | 0.3208 | |||
| Downside Deviation | 0.65 | |||
| Coefficient Of Variation | 493.34 | |||
| Standard Deviation | 0.6426 | |||
| Variance | 0.413 | |||
| Information Ratio | 0.134 | |||
| Jensen Alpha | 0.1174 | |||
| Total Risk Alpha | 0.0911 | |||
| Sortino Ratio | 0.1325 | |||
| Treynor Ratio | 1.46 | |||
| Maximum Drawdown | 3.88 | |||
| Value At Risk | (0.94) | |||
| Potential Upside | 1.19 | |||
| Downside Variance | 0.4224 | |||
| Semi Variance | 0.1029 | |||
| Expected Short fall | (0.53) | |||
| Skewness | 1.05 | |||
| Kurtosis | 5.44 |
Automotive Properties Backtested Returns
At this point, Automotive Properties is very steady. Automotive Properties secures Sharpe Ratio (or Efficiency) of 0.23, which signifies that the company had a 0.23 % return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Automotive Properties Real, which you can use to evaluate the volatility of the firm. Please confirm Automotive Properties' Risk Adjusted Performance of 0.1507, downside deviation of 0.65, and Mean Deviation of 0.4285 to double-check if the risk estimate we provide is consistent with the expected return of 0.16%. Automotive Properties has a performance score of 18 on a scale of 0 to 100. The firm shows a Beta (market volatility) of 0.0824, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Automotive Properties' returns are expected to increase less than the market. However, during the bear market, the loss of holding Automotive Properties is expected to be smaller as well. Automotive Properties right now shows a risk of 0.67%. Please confirm Automotive Properties semi variance, and the relationship between the maximum drawdown and accumulation distribution , to decide if Automotive Properties will be following its price patterns.
Auto-correlation | 0.66 |
Good predictability
Automotive Properties Real has good predictability. Overlapping area represents the amount of predictability between Automotive Properties time series from 5th of December 2025 to 19th of January 2026 and 19th of January 2026 to 5th of March 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Automotive Properties price movement. The serial correlation of 0.66 indicates that around 66.0% of current Automotive Properties price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.66 | |
| Spearman Rank Test | 0.63 | |
| Residual Average | 0.0 | |
| Price Variance | 0.03 |
Automotive 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.
Automotive Properties Technical Analysis
The output start index for this execution was two with a total number of output elements of fifty-nine. The Normalized Average True Range is used to analyze tradable apportunities for Automotive Properties across different markets.
About Automotive Properties Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Automotive Properties Real on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Automotive Properties Real based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Automotive Properties price pattern first instead of the macroeconomic environment surrounding Automotive Properties. By analyzing Automotive Properties's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Automotive Properties's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Automotive Properties specific price patterns or momentum indicators. Please read more on our technical analysis page.
| 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 |
Automotive Properties March 5, 2026 Technical Indicators
Most technical analysis of Automotive help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Automotive from various momentum indicators to cycle indicators. When you analyze Automotive charts, please remember that the event formation may indicate an entry point for a short seller, and look at different 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 |
| Risk Adjusted Performance | 0.1507 | |||
| Market Risk Adjusted Performance | 1.47 | |||
| Mean Deviation | 0.4285 | |||
| Semi Deviation | 0.3208 | |||
| Downside Deviation | 0.65 | |||
| Coefficient Of Variation | 493.34 | |||
| Standard Deviation | 0.6426 | |||
| Variance | 0.413 | |||
| Information Ratio | 0.134 | |||
| Jensen Alpha | 0.1174 | |||
| Total Risk Alpha | 0.0911 | |||
| Sortino Ratio | 0.1325 | |||
| Treynor Ratio | 1.46 | |||
| Maximum Drawdown | 3.88 | |||
| Value At Risk | (0.94) | |||
| Potential Upside | 1.19 | |||
| Downside Variance | 0.4224 | |||
| Semi Variance | 0.1029 | |||
| Expected Short fall | (0.53) | |||
| Skewness | 1.05 | |||
| Kurtosis | 5.44 |
Automotive Properties March 5, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Automotive stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 1,448 | ||
| Daily Balance Of Power | 0.75 | ||
| Rate Of Daily Change | 1.01 | ||
| Day Median Price | 11.69 | ||
| Day Typical Price | 11.71 | ||
| Price Action Indicator | 0.13 |
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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