Waste Management Standard Deviation
| WAST Stock | | | 21.97 -0.34 -1.52% |
The Standard Deviation signal for Waste Management CDR reflects patterns observed in trading data. Availability can differ across markets, exchanges, and instruments. Waste Management has a market cap of 89.18 B, ROE of 29.31%. See
Your Current Watchlist for portfolio-level analysis. The portfolio reflects a holding in Waste Management CDR. The weighting is visible within the allocation breakdown. 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.
Discover how to invest in Waste Stock by reading our
How to Buy Waste Stock guide. It offers practical guidance on account setup, order types, and timing for Waste Management. Use it as a practical starting point for your Waste Stock investment research.
Waste Management CDR has current Standard Deviation of 1.29. 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) |
| = | 1.29 | |
Standard Deviation Peers Comparison
Standard Deviation Relative To Other Indicators
Waste Management CDR is rated
below average in standard deviation compared to key competitors. It is currently under evaluation in maximum drawdown compared to key competitors producing
5.68 in Maximum Drawdown for each unit of Standard Deviation. The spread between Maximum Drawdown and Standard Deviation for Waste Management CDR sits at
5.68 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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