Quantitative U S Fund Market Value
GQSCX Fund | USD 12.78 0.27 2.16% |
Symbol | Quantitative |
Quantitative '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 Quantitative'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 Quantitative.
12/17/2024 |
| 03/17/2025 |
If you would invest 0.00 in Quantitative on December 17, 2024 and sell it all today you would earn a total of 0.00 from holding Quantitative U S or generate 0.0% return on investment in Quantitative over 90 days. Quantitative is related to or competes with Goldman Sachs, Transamerica Mlp, Franklin Natural, Fidelity Advisor, and Blackrock All-cap. Under normal market circumstances, the Portfolio invests at least 80 percent of the value of its net assets in common st... More
Quantitative 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 Quantitative'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 Quantitative U S upside and downside potential and time the market with a certain degree of confidence.
Information Ratio | (0.19) | |||
Maximum Drawdown | 9.22 | |||
Value At Risk | (2.50) | |||
Potential Upside | 1.49 |
Quantitative Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Quantitative's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Quantitative's standard deviation. In reality, there are many statistical measures that can use Quantitative historical prices to predict the future Quantitative's volatility.Risk Adjusted Performance | (0.21) | |||
Jensen Alpha | (0.29) | |||
Total Risk Alpha | (0.20) | |||
Treynor Ratio | (0.38) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Quantitative'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.
Quantitative U S Backtested Returns
Quantitative U S maintains Sharpe Ratio (i.e., Efficiency) of -0.19, which implies the entity had a -0.19 % return per unit of risk over the last 3 months. Quantitative U S exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check Quantitative's Coefficient Of Variation of (401.09), variance of 2.43, and Risk Adjusted Performance of (0.21) to confirm the risk estimate we provide. The fund holds a Beta of 1.04, which implies a somewhat significant risk relative to the market. Quantitative returns are very sensitive to returns on the market. As the market goes up or down, Quantitative is expected to follow.
Auto-correlation | -0.47 |
Modest reverse predictability
Quantitative U S has modest reverse predictability. Overlapping area represents the amount of predictability between Quantitative time series from 17th of December 2024 to 31st of January 2025 and 31st of January 2025 to 17th of March 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Quantitative U S price movement. The serial correlation of -0.47 indicates that about 47.0% of current Quantitative price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.47 | |
Spearman Rank Test | -0.47 | |
Residual Average | 0.0 | |
Price Variance | 0.35 |
Quantitative U S lagged returns against current returns
Autocorrelation, which is Quantitative 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 Quantitative's mutual fund expected returns. We can calculate the autocorrelation of Quantitative returns to help us make a trade decision. For example, suppose you find that Quantitative 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 |
Quantitative 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 Quantitative mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Quantitative mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Quantitative mutual fund over time.
Current vs Lagged Prices |
Timeline |
Quantitative Lagged Returns
When evaluating Quantitative's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Quantitative mutual fund have on its future price. Quantitative 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, Quantitative autocorrelation shows the relationship between Quantitative mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Quantitative U S.
Regressed Prices |
Timeline |
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Quantitative financial ratios help investors to determine whether Quantitative Mutual Fund 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 Quantitative with respect to the benefits of owning Quantitative security.
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