New York (Germany) Market Value
| NYT Stock | EUR 45.64 0.61 1.32% |
| Symbol | New |
New York '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 New York'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 New York.
| 04/23/2025 |
| 07/22/2025 |
If you would invest 0.00 in New York on April 23, 2025 and sell it all today you would earn a total of 0.00 from holding The New York or generate 0.0% return on investment in New York over 90 days. New York is related to or competes with RELX PLC, Relx PLC, Wolters Kluwer, WOLTERS KLUWER, Informa PLC, Pearson Plc, and New York. The New York Times Company, together with its subsidiaries, provides news and information for readers and viewers across... More
New York 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 New York'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 New York upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.2 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 7.89 | |||
| Value At Risk | (1.66) | |||
| Potential Upside | 1.41 |
New York Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for New York's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as New York's standard deviation. In reality, there are many statistical measures that can use New York historical prices to predict the future New York's volatility.| Risk Adjusted Performance | 0.1181 | |||
| Jensen Alpha | 0.0922 | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0) | |||
| Treynor Ratio | 0.4662 |
New York Backtested Returns
At this point, New York is very steady. New York has Sharpe Ratio of 0.0642, which conveys that the firm had a 0.0642 % return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for New York, which you can use to evaluate the volatility of the firm. Please verify New York's Market Risk Adjusted Performance of 0.4762, downside deviation of 1.2, and Risk Adjusted Performance of 0.1181 to check out if the risk estimate we provide is consistent with the expected return of 0.0628%. New York has a performance score of 5 on a scale of 0 to 100. The company secures a Beta (Market Risk) of 0.28, which conveys not very significant fluctuations relative to the market. As returns on the market increase, New York's returns are expected to increase less than the market. However, during the bear market, the loss of holding New York is expected to be smaller as well. New York right now secures a risk of 0.98%. Please verify The New York sortino ratio, potential upside, and the relationship between the jensen alpha and maximum drawdown , to decide if The New York will be following its current price movements.
Auto-correlation | -0.33 |
Poor reverse predictability
The New York has poor reverse predictability. Overlapping area represents the amount of predictability between New York time series from 23rd of April 2025 to 7th of June 2025 and 7th of June 2025 to 22nd of July 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 New York price movement. The serial correlation of -0.33 indicates that nearly 33.0% of current New York price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.33 | |
| Spearman Rank Test | -0.28 | |
| Residual Average | 0.0 | |
| Price Variance | 0.47 |
New York lagged returns against current returns
Autocorrelation, which is New York 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 New York's stock expected returns. We can calculate the autocorrelation of New York returns to help us make a trade decision. For example, suppose you find that New York 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 |
New York 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 New York stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if New York stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in New York stock over time.
Current vs Lagged Prices |
| Timeline |
New York Lagged Returns
When evaluating New York's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of New York stock have on its future price. New York 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, New York autocorrelation shows the relationship between New York stock current value and its past values and can show if there is a momentum factor associated with investing in The New York.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Other Information on Investing in New Stock
New York financial ratios help investors to determine whether New 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 New with respect to the benefits of owning New York security.