Ultrasmall Cap Profund Ultrasmall Cap Fund Market Value
| UAPSX Fund | USD 43.51 0.18 0.42% |
| Symbol | Ultrasmall-cap |
Ultrasmall-cap Profund '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 Ultrasmall-cap Profund's mutual fund 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 Ultrasmall-cap Profund.
| 07/28/2023 |
| 04/23/2024 |
If you would invest 0.00 in Ultrasmall-cap Profund on July 28, 2023 and sell it all today you would earn a total of 0.00 from holding Ultrasmall Cap Profund Ultrasmall Cap or generate 0.0% return on investment in Ultrasmall-cap Profund over 270 days. Ultrasmall-cap Profund is related to or competes with Short Real, Short Real, Ultrashort Mid, Ultrashort Mid-cap, Technology Ultrasector, Technology Ultrasector, and Large Cap. The fund invests in financial instruments that the fund Advisors believes, in combination, should produce daily returns ... More
Ultrasmall-cap Profund 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 Ultrasmall-cap Profund's mutual fund 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 Ultrasmall Cap Profund Ultrasmall Cap upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.8 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 12.01 | |||
| Value At Risk | (3.84) | |||
| Potential Upside | 4.01 |
Ultrasmall-cap Profund Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Ultrasmall-cap Profund's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Ultrasmall-cap Profund's standard deviation. In reality, there are many statistical measures that can use Ultrasmall-cap Profund historical prices to predict the future Ultrasmall-cap Profund's volatility.| Risk Adjusted Performance | 0.0194 | |||
| Jensen Alpha | (0.23) | |||
| Total Risk Alpha | (0.27) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.0111 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Ultrasmall-cap Profund'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.
Ultrasmall Cap Profund Backtested Returns
Ultrasmall Cap Profund owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.0108, which indicates the fund had a -0.0108% return per unit of risk over the last 3 months. Ultrasmall Cap Profund Ultrasmall Cap exposes twenty-seven different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Ultrasmall-cap Profund's Coefficient Of Variation of 5196.47, risk adjusted performance of 0.0194, and Semi Deviation of 2.75 to confirm the risk estimate we provide. The entity has a beta of 3.52, which indicates 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, Ultrasmall-cap Profund will likely underperform.
Auto-correlation | -0.51 |
Good reverse predictability
Ultrasmall Cap Profund Ultrasmall Cap has good reverse predictability. Overlapping area represents the amount of predictability between Ultrasmall-cap Profund time series from 28th of July 2023 to 10th of December 2023 and 10th of December 2023 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 Ultrasmall Cap Profund price movement. The serial correlation of -0.51 indicates that about 51.0% of current Ultrasmall-cap Profund price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.51 | |
| Spearman Rank Test | -0.2 | |
| Residual Average | 0.0 | |
| Price Variance | 5.51 |
Ultrasmall Cap Profund lagged returns against current returns
Autocorrelation, which is Ultrasmall-cap Profund mutual fund'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 Ultrasmall-cap Profund's mutual fund expected returns. We can calculate the autocorrelation of Ultrasmall-cap Profund returns to help us make a trade decision. For example, suppose you find that Ultrasmall-cap Profund has exhibited high autocorrelation historically, and you observe that the mutual fund 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 |
Ultrasmall-cap Profund 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 Ultrasmall-cap Profund mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Ultrasmall-cap Profund mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Ultrasmall-cap Profund mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Ultrasmall-cap Profund Lagged Returns
When evaluating Ultrasmall-cap Profund's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Ultrasmall-cap Profund mutual fund have on its future price. Ultrasmall-cap Profund 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, Ultrasmall-cap Profund autocorrelation shows the relationship between Ultrasmall-cap Profund mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Ultrasmall Cap Profund Ultrasmall Cap.
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 Ultrasmall-cap Profund 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, Ultrasmall-cap Profund's short interest history, or implied volatility extrapolated from Ultrasmall-cap Profund options trading.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Check out Ultrasmall-cap Profund Correlation, Ultrasmall-cap Profund Volatility and Ultrasmall-cap Profund Alpha and Beta module to complement your research on Ultrasmall-cap Profund. You can also try the Investing Opportunities module to build portfolios using our predefined set of ideas and optimize them against your investing preferences.
Ultrasmall-cap Profund technical mutual fund 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, fund market cycles, or different charting patterns.