Fuse Science Stock Market Value
| DROP Stock | USD 0.01 0 29.09% |
| Symbol | Fuse |
Fuse Science '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 Fuse Science'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 Fuse Science.
| 12/09/2022 |
| 11/28/2024 |
If you would invest 0.00 in Fuse Science on December 9, 2022 and sell it all today you would earn a total of 0.00 from holding Fuse Science or generate 0.0% return on investment in Fuse Science over 720 days. Fuse Science, Inc. operates a cloud-based customer service software platform More
Fuse Science 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 Fuse Science'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 Fuse Science upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 17.84 | |||
| Information Ratio | 0.0916 | |||
| Maximum Drawdown | 172.55 | |||
| Value At Risk | (23.08) | |||
| Potential Upside | 36.54 |
Fuse Science Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Fuse Science's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Fuse Science's standard deviation. In reality, there are many statistical measures that can use Fuse Science historical prices to predict the future Fuse Science's volatility.| Risk Adjusted Performance | 0.0836 | |||
| Jensen Alpha | 2.04 | |||
| Total Risk Alpha | (1.58) | |||
| Sortino Ratio | 0.1323 | |||
| Treynor Ratio | 0.6836 |
Fuse Science Backtested Returns
Fuse Science is out of control given 3 months investment horizon. Fuse Science secures Sharpe Ratio (or Efficiency) of 0.13, which denotes the company had a 0.13% return per unit of risk over the last 3 months. We were able to break down and interpolate data for twenty-seven different technical indicators, which can help you to evaluate if expected returns of 3.31% are justified by taking the suggested risk. Use Fuse Science Mean Deviation of 14.72, downside deviation of 17.84, and Coefficient Of Variation of 1034.16 to evaluate company specific risk that cannot be diversified away. Fuse Science holds a performance score of 9 on a scale of zero to a hundred. The firm shows a Beta (market volatility) of 3.63, which means a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Fuse Science will likely underperform. Use Fuse Science value at risk, as well as the relationship between the skewness and day typical price , to analyze future returns on Fuse Science.
Auto-correlation | 0.58 |
Modest predictability
Fuse Science has modest predictability. Overlapping area represents the amount of predictability between Fuse Science time series from 9th of December 2022 to 4th of December 2023 and 4th of December 2023 to 28th of November 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 Fuse Science price movement. The serial correlation of 0.58 indicates that roughly 58.0% of current Fuse Science price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.58 | |
| Spearman Rank Test | 0.52 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Fuse Science lagged returns against current returns
Autocorrelation, which is Fuse Science 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 Fuse Science's pink sheet expected returns. We can calculate the autocorrelation of Fuse Science returns to help us make a trade decision. For example, suppose you find that Fuse Science 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 |
Fuse Science 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 Fuse Science pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Fuse Science pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Fuse Science pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Fuse Science Lagged Returns
When evaluating Fuse Science's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Fuse Science pink sheet have on its future price. Fuse Science 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, Fuse Science autocorrelation shows the relationship between Fuse Science pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Fuse Science.
Regressed Prices |
| Timeline |
Pair Trading with Fuse Science
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Fuse Science position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Fuse Science will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Fuse Science could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Fuse Science when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Fuse Science - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Fuse Science to buy it.
The correlation of Fuse Science is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Fuse Science moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Fuse Science moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Fuse Science can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Additional Tools for Fuse Pink Sheet Analysis
When running Fuse Science's price analysis, check to measure Fuse Science'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 Fuse Science is operating at the current time. Most of Fuse Science's value examination focuses on studying past and present price action to predict the probability of Fuse Science's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Fuse Science's price. Additionally, you may evaluate how the addition of Fuse Science to your portfolios can decrease your overall portfolio volatility.