Macroaxis considers ETFS Bloomberg to be not too volatile. ETFS Bloomberg All
secures Sharpe Ratio (or Efficiency) of -0.1294 which denotes ETFS Bloomberg All
had -0.1294% of return per unit of return volatility over the last 2 months. Macroaxis approach to predicting risk of any etf is to look at both systematic and un-systematic factors of the business, including all available market data and technical indicators
. ETFS Bloomberg All Commodity Strt K 1 Fr exposes twenty-eight different technical indicators
which can help you to evaluate volatility that cannot be diversified away. Please be advised to confirm ETFS Bloomberg All Mean Deviation
of 0.6233 to check risk estimate we provide. The organization shows Beta (market volatility) of 0.1329 which denotes to the fact that as returns on market increase, ETFS Bloomberg returns are expected to increase less than the market. However during bear market, the loss on holding ETFS Bloomberg will be expected to be smaller as well.. Even though it is essential to pay attention to ETFS Bloomberg All
historical returns, it is always good to be careful when utilizing equity current trending patterns. Macroaxis approach to predicting future performance of any etf is to check both, its past performance charts as well as the business as a whole, including all available technical indicators
. ETFS Bloomberg All Commodity Strt K 1 Fr exposes twenty-eight different technical indicators which can help you to evaluate its performance.
ETFS Bloomberg All Commodity Strt K 1 Fr has average predictability. Overlapping area represents the amount of predictability between ETFS Bloomberg time series from October 16, 2018 to November 15, 2018 and November 15, 2018 to December 15, 2018. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of ETFS Bloomberg All price movement. The serial correlation of 0.44 indicates that just about 44.0% of current ETFS Bloomberg price fluctuation can be explain by its past prices.