Quantitative Longshort Equity Fund Market Value
| GTLSX Fund | USD 13.68 0.02 0.15% |
| 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.
| 03/20/2024 |
| 04/19/2024 |
If you would invest 0.00 in Quantitative on March 20, 2024 and sell it all today you would earn a total of 0.00 from holding Quantitative Longshort Equity or generate 0.0% return on investment in Quantitative over 30 days. Quantitative is related to or competes with Glenmede International, Equity Income, Woman In, High Yield, Responsible Esg, Secured Options, and Quantitative. The fund normally invests at least 80 percent of the value of its net assets in long and short positions with respect to... 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 Longshort Equity upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.339 | |||
| Information Ratio | (0.07) | |||
| Maximum Drawdown | 1.65 | |||
| Value At Risk | (0.51) | |||
| Potential Upside | 0.6002 |
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 | 0.0761 | |||
| Jensen Alpha | 0.039 | |||
| Total Risk Alpha | 0.004 | |||
| Sortino Ratio | (0.07) | |||
| Treynor Ratio | (0.60) |
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 Longshort Backtested Returns
We consider Quantitative very steady. Quantitative Longshort maintains Sharpe Ratio (i.e., Efficiency) of 0.13, which implies the entity had a 0.13% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Quantitative Longshort, which you can use to evaluate the volatility of the fund. Please check Quantitative's Semi Deviation of 0.1916, coefficient of variation of 729.26, and Risk Adjusted Performance of 0.0761 to confirm if the risk estimate we provide is consistent with the expected return of 0.0436%. The fund holds a Beta of -0.059, which implies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Quantitative are expected to decrease at a much lower rate. During the bear market, Quantitative is likely to outperform the market.
Auto-correlation | -0.52 |
Good reverse predictability
Quantitative Longshort Equity has good reverse predictability. Overlapping area represents the amount of predictability between Quantitative time series from 20th of March 2024 to 4th of April 2024 and 4th of April 2024 to 19th 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 Quantitative Longshort price movement. The serial correlation of -0.52 indicates that about 52.0% of current Quantitative price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.52 | |
| Spearman Rank Test | -0.31 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Quantitative Longshort 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 Longshort Equity.
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 Quantitative 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, Quantitative's short interest history, or implied volatility extrapolated from Quantitative options trading.
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Quantitative 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.