Appswarm Stock Market Value
| SWRM Stock | USD 0.0003 0.0001 50.00% |
| Symbol | Appswarm |
Appswarm '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 Appswarm'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 Appswarm.
| 12/10/2023 |
| 12/04/2024 |
If you would invest 0.00 in Appswarm on December 10, 2023 and sell it all today you would earn a total of 0.00 from holding Appswarm or generate 0.0% return on investment in Appswarm over 360 days. Appswarm is related to or competes with Salesforce, S A P, ServiceNow, Intuit, Uber Technologies, Shopify, and Applovin Corp. App Swarm, Inc., an application incubation company, engages in acquiring and marketing applications for various forms of... More
Appswarm 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 Appswarm'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 Appswarm upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | 0.0692 | |||
| Maximum Drawdown | 83.33 | |||
| Value At Risk | (33.33) | |||
| Potential Upside | 50.0 |
Appswarm Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Appswarm's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Appswarm's standard deviation. In reality, there are many statistical measures that can use Appswarm historical prices to predict the future Appswarm's volatility.| Risk Adjusted Performance | 0.0675 | |||
| Jensen Alpha | 1.22 | |||
| Total Risk Alpha | (1.00) | |||
| Treynor Ratio | 3.58 |
Appswarm Backtested Returns
Appswarm is out of control given 3 months investment horizon. Appswarm secures Sharpe Ratio (or Efficiency) of 0.069, which signifies that the company had a 0.069% return per unit of risk over the last 3 months. We were able to interpolate data for twenty-four different technical indicators, which can help you to evaluate if expected returns of 1.04% are justified by taking the suggested risk. Use Appswarm Mean Deviation of 7.38, standard deviation of 16.62, and Risk Adjusted Performance of 0.0675 to evaluate company specific risk that cannot be diversified away. Appswarm holds a performance score of 5 on a scale of zero to a hundred. The firm shows a Beta (market volatility) of 0.35, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, Appswarm's returns are expected to increase less than the market. However, during the bear market, the loss of holding Appswarm is expected to be smaller as well. Use Appswarm treynor ratio, accumulation distribution, as well as the relationship between the Accumulation Distribution and price action indicator , to analyze future returns on Appswarm.
Auto-correlation | 0.51 |
Modest predictability
Appswarm has modest predictability. Overlapping area represents the amount of predictability between Appswarm time series from 10th of December 2023 to 7th of June 2024 and 7th of June 2024 to 4th 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 Appswarm price movement. The serial correlation of 0.51 indicates that about 51.0% of current Appswarm price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.51 | |
| Spearman Rank Test | 0.27 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Appswarm lagged returns against current returns
Autocorrelation, which is Appswarm 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 Appswarm's pink sheet expected returns. We can calculate the autocorrelation of Appswarm returns to help us make a trade decision. For example, suppose you find that Appswarm 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 |
Appswarm 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 Appswarm pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Appswarm pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Appswarm pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Appswarm Lagged Returns
When evaluating Appswarm's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Appswarm pink sheet have on its future price. Appswarm 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, Appswarm autocorrelation shows the relationship between Appswarm pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Appswarm.
Regressed Prices |
| Timeline |
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Appswarm financial ratios help investors to determine whether Appswarm Pink Sheet 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 Appswarm with respect to the benefits of owning Appswarm security.