Gerresheimer Ag Stock Market Value
| GRRMF Stock | USD 105.35 1.30 1.25% |
| Symbol | Gerresheimer |
Gerresheimer '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 Gerresheimer's pink sheet 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 Gerresheimer.
| 05/05/2022 |
| 04/24/2024 |
If you would invest 0.00 in Gerresheimer on May 5, 2022 and sell it all today you would earn a total of 0.00 from holding Gerresheimer AG or generate 0.0% return on investment in Gerresheimer over 720 days. Gerresheimer is related to or competes with GlucoTrack, Sharps Technology, Utah Medical, Innovative Eyewear, and Microbot Medical. Gerresheimer AG, together with its subsidiaries, manufactures and sells packaging products, and drug delivery-devices an... More
Gerresheimer 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 Gerresheimer's pink sheet 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 Gerresheimer AG upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 4.25 | |||
| Information Ratio | 0.0075 | |||
| Maximum Drawdown | 20.25 | |||
| Value At Risk | (3.81) | |||
| Potential Upside | 3.01 |
Gerresheimer Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Gerresheimer's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Gerresheimer's standard deviation. In reality, there are many statistical measures that can use Gerresheimer historical prices to predict the future Gerresheimer's volatility.| Risk Adjusted Performance | 0.0343 | |||
| Jensen Alpha | 0.1048 | |||
| Total Risk Alpha | (0.22) | |||
| Sortino Ratio | 0.0044 | |||
| Treynor Ratio | (1.10) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Gerresheimer'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.
Gerresheimer AG Backtested Returns
We consider Gerresheimer very steady. Gerresheimer AG holds Efficiency (Sharpe) Ratio of 0.0269, which attests that the entity had a 0.0269% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Gerresheimer AG, which you can use to evaluate the volatility of the firm. Please check out Gerresheimer's Downside Deviation of 4.25, risk adjusted performance of 0.0343, and Market Risk Adjusted Performance of (1.09) to validate if the risk estimate we provide is consistent with the expected return of 0.0687%. Gerresheimer has a performance score of 2 on a scale of 0 to 100. The company retains a Market Volatility (i.e., Beta) of -0.089, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Gerresheimer are expected to decrease at a much lower rate. During the bear market, Gerresheimer is likely to outperform the market. Gerresheimer AG right now retains a risk of 2.55%. Please check out Gerresheimer semi variance, and the relationship between the maximum drawdown and daily balance of power , to decide if Gerresheimer will be following its current trending patterns.
Auto-correlation | -0.46 |
Modest reverse predictability
Gerresheimer AG has modest reverse predictability. Overlapping area represents the amount of predictability between Gerresheimer time series from 5th of May 2022 to 30th of April 2023 and 30th of April 2023 to 24th 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 Gerresheimer AG price movement. The serial correlation of -0.46 indicates that about 46.0% of current Gerresheimer price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.46 | |
| Spearman Rank Test | 0.21 | |
| Residual Average | 0.0 | |
| Price Variance | 164.39 |
Gerresheimer AG lagged returns against current returns
Autocorrelation, which is Gerresheimer pink sheet'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 Gerresheimer's pink sheet expected returns. We can calculate the autocorrelation of Gerresheimer returns to help us make a trade decision. For example, suppose you find that Gerresheimer has exhibited high autocorrelation historically, and you observe that the pink sheet 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 |
Gerresheimer 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 Gerresheimer pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Gerresheimer pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Gerresheimer pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Gerresheimer Lagged Returns
When evaluating Gerresheimer's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Gerresheimer pink sheet have on its future price. Gerresheimer 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, Gerresheimer autocorrelation shows the relationship between Gerresheimer pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Gerresheimer AG.
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 Gerresheimer 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, Gerresheimer's short interest history, or implied volatility extrapolated from Gerresheimer options trading.
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Complementary Tools for Gerresheimer Pink Sheet analysis
When running Gerresheimer's price analysis, check to measure Gerresheimer'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 Gerresheimer is operating at the current time. Most of Gerresheimer's value examination focuses on studying past and present price action to predict the probability of Gerresheimer's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Gerresheimer's price. Additionally, you may evaluate how the addition of Gerresheimer to your portfolios can decrease your overall portfolio volatility.
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Gerresheimer technical pink sheet 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, pink sheet market cycles, or different charting patterns.