BioNTech (UK) Market Value
| 0A3M Stock | USD 110.25 4.06 3.55% |
| Symbol | BioNTech |
BioNTech '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 BioNTech'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 BioNTech.
| 11/20/2024 |
| 12/20/2024 |
If you would invest 0.00 in BioNTech on November 20, 2024 and sell it all today you would earn a total of 0.00 from holding BioNTech SE or generate 0.0% return on investment in BioNTech over 30 days. BioNTech is related to or competes with Samsung Electronics, Samsung Electronics, Hyundai, Toyota, State Bank, SoftBank Group, and Reliance Industries. BioNTech SE, a biotechnology company, develops and commercializes immunotherapies for cancer and other infectious diseas... More
BioNTech 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 BioNTech'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 BioNTech SE upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 3.08 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 16.85 | |||
| Value At Risk | (4.01) | |||
| Potential Upside | 4.61 |
BioNTech Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for BioNTech's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as BioNTech's standard deviation. In reality, there are many statistical measures that can use BioNTech historical prices to predict the future BioNTech's volatility.| Risk Adjusted Performance | 0.01 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.09) | |||
| Sortino Ratio | (0.01) |
BioNTech SE Backtested Returns
As of now, BioNTech Stock is very steady. BioNTech SE secures Sharpe Ratio (or Efficiency) of 0.0025, which signifies that the company had a 0.0025% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for BioNTech SE, which you can use to evaluate the volatility of the firm. Please confirm BioNTech's Risk Adjusted Performance of 0.01, downside deviation of 3.08, and Mean Deviation of 2.05 to double-check if the risk estimate we provide is consistent with the expected return of 0.0075%. The firm shows a Beta (market volatility) of 0.55, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, BioNTech's returns are expected to increase less than the market. However, during the bear market, the loss of holding BioNTech is expected to be smaller as well. BioNTech SE right now shows a risk of 3.04%. Please confirm BioNTech SE downside deviation, standard deviation, total risk alpha, as well as the relationship between the coefficient of variation and jensen alpha , to decide if BioNTech SE will be following its price patterns.
Auto-correlation | -0.31 |
Poor reverse predictability
BioNTech SE has poor reverse predictability. Overlapping area represents the amount of predictability between BioNTech time series from 20th of November 2024 to 5th of December 2024 and 5th of December 2024 to 20th of December 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 BioNTech SE price movement. The serial correlation of -0.31 indicates that nearly 31.0% of current BioNTech price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.31 | |
| Spearman Rank Test | -0.68 | |
| Residual Average | 0.0 | |
| Price Variance | 12.76 |
BioNTech SE lagged returns against current returns
Autocorrelation, which is BioNTech 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 BioNTech's stock expected returns. We can calculate the autocorrelation of BioNTech returns to help us make a trade decision. For example, suppose you find that BioNTech 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 |
BioNTech 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 BioNTech stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if BioNTech stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in BioNTech stock over time.
Current vs Lagged Prices |
| Timeline |
BioNTech Lagged Returns
When evaluating BioNTech's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of BioNTech stock have on its future price. BioNTech 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, BioNTech autocorrelation shows the relationship between BioNTech stock current value and its past values and can show if there is a momentum factor associated with investing in BioNTech SE.
Regressed Prices |
| Timeline |
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BioNTech 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.