Science Technology Fund Market Value
| VCSTX Fund | USD 26.90 0.59 2.24% |
| Symbol | Science |
Science Technology '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 Science Technology'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 Science Technology.
| 03/25/2024 |
| 04/24/2024 |
If you would invest 0.00 in Science Technology on March 25, 2024 and sell it all today you would earn a total of 0.00 from holding Science Technology Fund or generate 0.0% return on investment in Science Technology over 30 days. Science Technology is related to or competes with Vanguard Information, Columbia Seligman, Columbia Seligman, Ivy Science, and Ivy Science. The fund normally invests at least 80 percent of net assets in the common stocks of companies that are expected to benef... More
Science Technology 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 Science Technology'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 Science Technology Fund upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.34 | |||
| Information Ratio | (0.02) | |||
| Maximum Drawdown | 7.52 | |||
| Value At Risk | (2.11) | |||
| Potential Upside | 2.24 |
Science Technology Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Science Technology's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Science Technology's standard deviation. In reality, there are many statistical measures that can use Science Technology historical prices to predict the future Science Technology's volatility.| Risk Adjusted Performance | 0.0374 | |||
| Jensen Alpha | (0.05) | |||
| Total Risk Alpha | (0.13) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.0473 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Science Technology'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.
Science Technology Backtested Returns
We consider Science Technology very steady. Science Technology owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0327, which indicates the fund had a 0.0327% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Science Technology Fund, which you can use to evaluate the volatility of the fund. Please validate Science Technology's Semi Deviation of 1.27, coefficient of variation of 1966.73, and Risk Adjusted Performance of 0.0374 to confirm if the risk estimate we provide is consistent with the expected return of 0.0483%. The entity has a beta of 1.34, 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, Science Technology will likely underperform.
Auto-correlation | 0.24 |
Weak predictability
Science Technology Fund has weak predictability. Overlapping area represents the amount of predictability between Science Technology time series from 25th of March 2024 to 9th of April 2024 and 9th of April 2024 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 Science Technology price movement. The serial correlation of 0.24 indicates that over 24.0% of current Science Technology price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.24 | |
| Spearman Rank Test | 0.18 | |
| Residual Average | 0.0 | |
| Price Variance | 0.6 |
Science Technology lagged returns against current returns
Autocorrelation, which is Science Technology 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 Science Technology's mutual fund expected returns. We can calculate the autocorrelation of Science Technology returns to help us make a trade decision. For example, suppose you find that Science Technology 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 |
Science Technology 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 Science Technology mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Science Technology mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Science Technology mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Science Technology Lagged Returns
When evaluating Science Technology's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Science Technology mutual fund have on its future price. Science Technology 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, Science Technology autocorrelation shows the relationship between Science Technology mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Science Technology Fund.
Regressed Prices |
| Timeline |
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 Science Technology Correlation, Science Technology Volatility and Science Technology Alpha and Beta module to complement your research on Science Technology. You can also try the Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.
Science Technology 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.