The Short Term Fund Market Value
| CFSTX Fund | USD 15.77 0.01 0.06% |
| Symbol | Short |
Short Term '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 Short Term'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 Short Term.
| 04/23/2024 |
| 05/23/2024 |
If you would invest 0.00 in Short Term on April 23, 2024 and sell it all today you would earn a total of 0.00 from holding The Short Term or generate 0.0% return on investment in Short Term over 30 days. Short Term is related to or competes with Columbia Global, Global Technology, Janus Global, Technology Ultrasector, Blackrock Science, Red Oak, and Franklin Biotechnology. The fund normally invests at least 80 percent of its net assets plus any borrowings for investment purposes in securitie... More
Short Term 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 Short Term'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 The Short Term upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1547 | |||
| Information Ratio | (0.64) | |||
| Maximum Drawdown | 0.6353 | |||
| Value At Risk | (0.13) | |||
| Potential Upside | 0.1274 |
Short Term Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Short Term's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Short Term's standard deviation. In reality, there are many statistical measures that can use Short Term historical prices to predict the future Short Term's volatility.| Risk Adjusted Performance | 0.0108 | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.44) | |||
| Treynor Ratio | 0.003 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Short Term'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.
Short Term Backtested Returns
We consider Short Term out of control. Short Term owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0953, which indicates the fund had a 0.0953% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for The Short Term, which you can use to evaluate the volatility of the fund. Please validate Short Term's Semi Deviation of 0.0432, risk adjusted performance of 0.0108, and Coefficient Of Variation of 1049.08 to confirm if the risk estimate we provide is consistent with the expected return of 0.0102%. The entity has a beta of 0.0512, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Short Term's returns are expected to increase less than the market. However, during the bear market, the loss of holding Short Term is expected to be smaller as well.
Auto-correlation | 0.38 |
Below average predictability
The Short Term has below average predictability. Overlapping area represents the amount of predictability between Short Term time series from 23rd of April 2024 to 8th of May 2024 and 8th of May 2024 to 23rd of May 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 Short Term price movement. The serial correlation of 0.38 indicates that just about 38.0% of current Short Term price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.38 | |
| Spearman Rank Test | 0.69 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Short Term lagged returns against current returns
Autocorrelation, which is Short Term 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 Short Term's mutual fund expected returns. We can calculate the autocorrelation of Short Term returns to help us make a trade decision. For example, suppose you find that Short Term 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 |
Short Term 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 Short Term mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Short Term mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Short Term mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Short Term Lagged Returns
When evaluating Short Term's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Short Term mutual fund have on its future price. Short Term 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, Short Term autocorrelation shows the relationship between Short Term mutual fund current value and its past values and can show if there is a momentum factor associated with investing in The Short Term.
Regressed Prices |
| Timeline |
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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 Short Term Correlation, Short Term Volatility and Short Term Alpha and Beta module to complement your research on Short Term. You can also try the Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
Short Term 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.