OPPENHEIMER STEELPATH Standard Deviation

MLPFX Fund  USD 10.42  0.03  0.29%   
OPPENHEIMER STEELPATH standard deviation lookup summarizes this and related technical indicators for Oppenheimer Steelpath Mlp. Coverage depends on data availability and normalization; Equity Screeners provides additional screening context. Use Correlation Analysis to better understand diversified portfolio construction. Clearer exposure analysis supports long-term portfolio balance. This includes a position in Oppenheimer Steelpath Mlp in the portfolio view. Also, note that the market value of any mutual fund could be closely tied with the direction of predictive economic indicators such as signals in price.
  
Oppenheimer Steelpath Mlp has current Standard Deviation of 0.7429. 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)

 = 
0.7429
SQRT = Square root notation
V =   Variance of OPPENHEIMER STEELPATH returns

OPPENHEIMER STEELPATH Standard Deviation Peers Comparison

OPPENHEIMER Standard Deviation Relative To Other Indicators

Oppenheimer Steelpath Mlp is rated below average in standard deviation among similar funds. It is currently under evaluation in maximum drawdown among similar funds reporting about 3.80 of Maximum Drawdown per Standard Deviation. At 3.80 , Oppenheimer Steelpath Mlp's Maximum Drawdown-to-Standard Deviation multiple reflects the spread between these metrics
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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