Macroaxis considers Bank of New York to be not too risky. Bank of New York
secures Sharpe Ratio (or Efficiency) of -0.2248 which signifies that Bank of New York
had -0.2248% of return per unit of standard deviation over the last 1 month. Macroaxis philosophy in foreseeing risk of any stock is to look at both systematic and un-systematic factors of the business, including all available market data and technical indicators
. The Bank of New York Mellon Corporation exposes twenty-one different technical indicators
which can help you to evaluate volatility that cannot be diversified away. Please be advised to confirm Bank of New York Mean Deviation
of 1.04 and Risk Adjusted Performance
of 0.11 to double-check risk estimate we provide. Macroaxis gives Bank of New York performance score of 0 on a scale of 0 to 100. The firm shows Beta (market volatility) of -0.2733 which signifies that as returns on market increase, returns on owning Bank of New York are expected to decrease at a much smaller rate. During bear market, Bank of New York is likely to outperform the market.. Even though it is essential to pay attention to Bank of New York historical returns, it is always good to be careful when utilizing equity current trending patterns. Macroaxis philosophy in foreseeing future performance of any stock is to check both, its past performance charts as well as the business as a whole, including all available technical indicators. The Bank of New York Mellon Corporation exposes twenty-one different technical indicators which can help you to evaluate its performance. Bank of New York has expected return of -0.3611%. Please be advised to confirm Bank of New York Downside Deviation, Treynor Ratio, Expected Short fall, as well as the relationship between Variance and Potential Upside to decide if Bank of New York past performance will be repeated at some point in the near future.
|15 days auto-correlation|| 0.17 |
Very weak predictability
The Bank of New York Mellon Corporation has very weak predictability. Overlapping area represents the amount of predictability between Bank of New York time series from June 22, 2018 to July 7, 2018 and July 7, 2018 to July 22, 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 Bank of New York price movement. The serial correlation of 0.17 indicates that over 17.0% of current Bank of New York price fluctuation can be explain by its past prices.
|Correlation Coefficient|| 0.17|
|Spearman Rank Test|| 0.3|
|Price Variance|| 0.78|
|Lagged Price Variance|| 1.14|