We consider UBS ETRACS not too volatile. UBS ETRACS SP
owns Efficiency Ratio (i.e. Sharpe Ratio) of 0.0134 which indicates UBS ETRACS SP
had 0.0134% of return per unit of standard deviation over the last 1 month. Our approach into measuring volatility of an etf is to use all available market data together with etf specific technical indicators
that cannot be diversified away. We have found twenty-one technical indicators
for UBS ETRACS SP GSCI Crd OilTtl Rt ETN which you can use to evaluate future volatility of the entity. Please validate UBS ETRACS Risk Adjusted Performance
of 0.1103 and Market Risk Adjusted Performance
of 1.28 to confirm if risk estimate we provide are consistent with the epected return of 0.0331%. The entity has beta of -0.2528 which indicates as returns on market increase, returns on owning UBS ETRACS are expected to decrease at a much smaller rate. During bear market, UBS ETRACS is likely to outperform the market.. Although it is extremely important to respect UBS ETRACS SP current price movements, it is better to be realistic regarding the information on equity historical returns. The approach into measuring future performance of any etf is to evaluate the business as a whole together with its past performance including all available fundamental and technical indicators. By examining UBS ETRACS SP technical indicators you can now evaluate if the expected return of 0.0331% will be sustainable into the future.
|15 days auto-correlation|| 0.00 |
No correlation between past and present
UBS ETRACS SP GSCI Crd OilTtl Rt ETN has no correlation between past and present. Overlapping area represents the amount of predictability between UBS ETRACS time series from August 22, 2018 to September 6, 2018 and September 6, 2018 to September 21, 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 UBS ETRACS SP price movement. The serial correlation of 0.0 indicates that just 0.0% of current UBS ETRACS price fluctuation can be explain by its past prices.
|Spearman Rank Test||0.0|