Bank of New York Mellon (Germany) Market Value
| BN9 Stock | EUR 83.53 1.12 1.36% |
| Symbol | Bank |
Bank of New York Mellon 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Bank of New York Mellon's stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Bank of New York Mellon.
| 03/12/2023 |
| 03/01/2025 |
If you would invest 0.00 in Bank of New York Mellon on March 12, 2023 and sell it all today you would earn a total of 0.00 from holding The Bank of or generate 0.0% return on investment in Bank of New York Mellon over 720 days. Bank of New York Mellon is related to or competes with Sinopec Shanghai, CHEMICAL INDUSTRIES, Clean Harbors, COMM HEALTH, UNIDOC HEALTH, and TRI CHEMICAL. The Bank of New York Mellon Corporation provides a range of financial products and services to institutions, corporation... More
Bank of New York Mellon Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Bank of New York Mellon's stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess The Bank of upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.16 | |||
| Information Ratio | 0.1082 | |||
| Maximum Drawdown | 6.71 | |||
| Value At Risk | (1.73) | |||
| Potential Upside | 2.41 |
Bank of New York Mellon Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Bank of New York Mellon's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Bank of New York Mellon's standard deviation. In reality, there are many statistical measures that can use Bank of New York Mellon historical prices to predict the future Bank of New York Mellon's volatility.| Risk Adjusted Performance | 0.0772 | |||
| Jensen Alpha | 0.1297 | |||
| Total Risk Alpha | 0.1661 | |||
| Sortino Ratio | 0.1266 | |||
| Treynor Ratio | 0.4775 |
Bank of New York Mellon Backtested Returns
At this point, Bank of New York Mellon is very steady. Bank of New York Mellon secures Sharpe Ratio (or Efficiency) of 0.0986, which signifies that the company had a 0.0986 % return per unit of standard deviation over the last 3 months. We have found twenty-eight technical indicators for The Bank of, which you can use to evaluate the volatility of the firm. Please confirm Bank of New York Mellon's Mean Deviation of 1.01, risk adjusted performance of 0.0772, and Semi Deviation of 1.03 to double-check if the risk estimate we provide is consistent with the expected return of 0.13%. Bank of New York Mellon has a performance score of 7 on a scale of 0 to 100. The firm shows a Beta (market volatility) of 0.26, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Bank of New York Mellon's returns are expected to increase less than the market. However, during the bear market, the loss of holding Bank of New York Mellon is expected to be smaller as well. Bank of New York Mellon right now shows a risk of 1.36%. Please confirm Bank of New York Mellon downside deviation, information ratio, and the relationship between the semi deviation and coefficient of variation , to decide if Bank of New York Mellon will be following its price patterns.
Auto-correlation | 0.87 |
Very good predictability
The Bank of has very good predictability. Overlapping area represents the amount of predictability between Bank of New York Mellon time series from 12th of March 2023 to 6th of March 2024 and 6th of March 2024 to 1st of March 2025. 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 Mellon price movement. The serial correlation of 0.87 indicates that approximately 87.0% of current Bank of New York Mellon price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.87 | |
| Spearman Rank Test | 0.79 | |
| Residual Average | 0.0 | |
| Price Variance | 126.18 |
Bank of New York Mellon lagged returns against current returns
Autocorrelation, which is Bank of New York Mellon stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Bank of New York Mellon's stock expected returns. We can calculate the autocorrelation of Bank of New York Mellon returns to help us make a trade decision. For example, suppose you find that Bank of New York Mellon has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Bank of New York Mellon regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Bank of New York Mellon stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Bank of New York Mellon stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Bank of New York Mellon stock over time.
Current vs Lagged Prices |
| Timeline |
Bank of New York Mellon Lagged Returns
When evaluating Bank of New York Mellon's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Bank of New York Mellon stock have on its future price. Bank of New York Mellon autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Bank of New York Mellon autocorrelation shows the relationship between Bank of New York Mellon stock current value and its past values and can show if there is a momentum factor associated with investing in The Bank of.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Other Information on Investing in Bank Stock
Bank of New York Mellon financial ratios help investors to determine whether Bank Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Bank with respect to the benefits of owning Bank of New York Mellon security.