Autocanada Standard Deviation
| ACQ Stock | | | CAD 17.15 0.15 0.88% |
The Standard Deviation indicator for Autocanada is derived from observed market data. The calculation draws on time-series market data across available periods. Exchange-specific data schedules may affect the recency of readings. For broader technical screening across instruments, see
Equity Screeners. Autocanada has a market cap of 396.14 M, operating margin of 0.18%, ROE of 4.79%. See
Trending Equities for portfolio-level analysis. Portfolio positioning is summarized for reference. Position-level data supports the allocation summary. The information is presented without directional commentary. The allocation shows a weighting toward Autocanada. The position is captured in the allocation summary. Each holding is sized according to the methodology applied to the portfolio. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as
signals in inflation.
Autocanada has current Standard Deviation of 3.22. The Standard Deviation is a measure of how spread out the prices or returns of an asset are on average. It is the most widely used risk indicator in the field of investing and finance. Standard Deviation is commonly used to measure confidence in statistical conclusions regarding certain equity instruments or portfolios of equities.
Standard Deviation | = | SQRT(V) |
| = | 3.22 | |
Standard Deviation Peers Comparison
Standard Deviation Relative To Other Indicators
Autocanada takes the leading position in standard deviation compared to key competitors. It is currently under evaluation in maximum drawdown compared to key competitors producing
6.09 in Maximum Drawdown for each unit of Standard Deviation. The spread between Maximum Drawdown and Standard Deviation for Autocanada sits at
6.09 Standard deviation is applied to the annual rate of return of an investment to measure the investment's volatility. Standard deviation is also known as historical volatility and is used by investors as a gauge for the amount of expected market volatility. A large standard deviation usually indicates that the data points are far from the mean and a small standard deviation indicates that they are clustered closely around the mean.
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