S-E BANKEN (Germany) Market Value
SEBA Stock | EUR 12.59 0.13 1.04% |
Symbol | S-E |
S-E BANKEN '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 S-E BANKEN'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 S-E BANKEN.
02/23/2024 |
| 04/23/2024 |
If you would invest 0.00 in S-E BANKEN on February 23, 2024 and sell it all today you would earn a total of 0.00 from holding S E BANKEN A or generate 0.0% return on investment in S-E BANKEN over 60 days. S-E BANKEN is related to or competes with MeVis Medical, SK TELECOM, DXC Technology, Ribbon Communications, SAFETY MEDICAL, and XTANT MEDICAL. More
S-E BANKEN 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 S-E BANKEN'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 S E BANKEN A upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.11 | |||
Information Ratio | 0.1245 | |||
Maximum Drawdown | 24.06 | |||
Value At Risk | (1.77) | |||
Potential Upside | 2.67 |
S-E BANKEN Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for S-E BANKEN's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as S-E BANKEN's standard deviation. In reality, there are many statistical measures that can use S-E BANKEN historical prices to predict the future S-E BANKEN's volatility.Risk Adjusted Performance | 0.1031 | |||
Jensen Alpha | 0.4225 | |||
Total Risk Alpha | 0.0667 | |||
Sortino Ratio | 0.3309 | |||
Treynor Ratio | 1.43 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of S-E BANKEN's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
S E BANKEN Backtested Returns
S-E BANKEN appears to be not too volatile, given 3 months investment horizon. S E BANKEN owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.16, which indicates the company had a 0.16% return per unit of volatility over the last 3 months. We have found twenty-eight technical indicators for S E BANKEN A , which you can use to evaluate the volatility of the entity. Please review S-E BANKEN's Market Risk Adjusted Performance of 1.44, downside deviation of 1.11, and Risk Adjusted Performance of 0.1031 to confirm if our risk estimates are consistent with your expectations. On a scale of 0 to 100, S-E BANKEN holds a performance score of 12. The firm has a beta of 0.31, which indicates possible diversification benefits within a given portfolio. As returns on the market increase, S-E BANKEN's returns are expected to increase less than the market. However, during the bear market, the loss of holding S-E BANKEN is expected to be smaller as well. Please check S-E BANKEN's information ratio, total risk alpha, and the relationship between the coefficient of variation and jensen alpha , to make a quick decision on whether S-E BANKEN's existing price patterns will revert.
Auto-correlation | -0.21 |
Weak reverse predictability
S E BANKEN A has weak reverse predictability. Overlapping area represents the amount of predictability between S-E BANKEN time series from 23rd of February 2024 to 24th of March 2024 and 24th of March 2024 to 23rd of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of S E BANKEN price movement. The serial correlation of -0.21 indicates that over 21.0% of current S-E BANKEN price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.21 | |
Spearman Rank Test | -0.48 | |
Residual Average | 0.0 | |
Price Variance | 0.05 |
S E BANKEN lagged returns against current returns
Autocorrelation, which is S-E BANKEN 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 S-E BANKEN's stock expected returns. We can calculate the autocorrelation of S-E BANKEN returns to help us make a trade decision. For example, suppose you find that S-E BANKEN 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 |
S-E BANKEN 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 S-E BANKEN stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if S-E BANKEN stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in S-E BANKEN stock over time.
Current vs Lagged Prices |
Timeline |
S-E BANKEN Lagged Returns
When evaluating S-E BANKEN's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of S-E BANKEN stock have on its future price. S-E BANKEN 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, S-E BANKEN autocorrelation shows the relationship between S-E BANKEN stock current value and its past values and can show if there is a momentum factor associated with investing in S E BANKEN A .
Regressed Prices |
Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards S-E BANKEN in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, S-E BANKEN's short interest history, or implied volatility extrapolated from S-E BANKEN options trading.
Currently Active Assets on Macroaxis
Check out S-E BANKEN Correlation, S-E BANKEN Volatility and S-E BANKEN Alpha and Beta module to complement your research on S-E BANKEN. You can also try the AI Portfolio Architect module to use AI to generate optimal portfolios and find profitable investment opportunities.
Complementary Tools for S-E Stock analysis
When running S-E BANKEN's price analysis, check to measure S-E BANKEN's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy S-E BANKEN is operating at the current time. Most of S-E BANKEN's value examination focuses on studying past and present price action to predict the probability of S-E BANKEN's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move S-E BANKEN's price. Additionally, you may evaluate how the addition of S-E BANKEN to your portfolios can decrease your overall portfolio volatility.
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S-E BANKEN technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.