QS GROWTH Mutual Fund Forward View - Double Exponential Smoothing
| LLLRX Fund | USD 17.44 -0.10 -0.57% |
Momentum
Sell Peaked
Oversold | Overbought |
This view relates QS GROWTH's headline activity to recent price response context.
The Double Exponential Smoothing forecasted value of Qs Growth Fund on the next trading day is expected to be 17.38 with a mean absolute deviation of 0.12 and the sum of the absolute errors of 6.97.QS GROWTH after-hype prediction price | $ 17.44 |
The sentiment view is a companion to forecasting, technical studies, analyst estimates, and earnings trends.
LLLRX |
QS GROWTH Additional Predictive Modules
Most predictive techniques to examine LLLRX price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for LLLRX using various technical indicators. When you analyze LLLRX charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Double Exponential Smoothing Price Forecast For the 15th of March 2026
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Qs Growth Fund on the next trading day is expected to be 17.38 with a mean absolute deviation of 0.12 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 6.97 .Please note that although there have been many attempts to predict LLLRX Mutual Fund prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that QS GROWTH's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest QS GROWTH | QS GROWTH Price Prediction | Research Analysis |
Forecasted Value
This next-day forecast for Qs Growth Fund uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. Investors should still remember that no empirical framework consistently proves that one family of forecasting models will outperform all other approaches in live markets.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of QS GROWTH mutual fund data series using in forecasting. Note that when a statistical model is used to represent QS GROWTH mutual fund, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | Huge |
| Bias | Arithmetic mean of the errors | 0.0049 |
| MAD | Mean absolute deviation | 0.1161 |
| MAPE | Mean absolute percentage error | 0.0065 |
| SAE | Sum of the absolute errors | 6.9673 |
Experienced QS GROWTH's investors use mean reversion as a complement to momentum analysis: momentum identifies the trend; mean reversion identifies when that trend has extended beyond sustainable levels.
After-Hype Price Density Analysis
This probability distribution for QS GROWTH is built from Monte Carlo simulations that incorporate QS GROWTH's historical volatility, mean reversion tendencies, and jump risk. The resulting distribution captures a broader range of QS GROWTH outcomes than simple linear.
Next price density |
| Expected price to next headline |
Estimiated After-Hype Price Volatility
The boundaries derived from QS GROWTH's historical news analysis represent the range within which QS GROWTH's price has typically settled after comparable headline events. QS GROWTH's after-hype downside and upside margins for the prediction period are 16.57 and 18.31, respectively. Outcomes outside these boundaries are less common but not rare for QS GROWTH.
Current Value
The after-hype framework applied to Qs Growth Fund assumes a 3 months review window and focuses on post-sentiment normalization rather than raw momentum. This view is most useful when investors want to compare sentiment-driven price extension with a more measured post-news scenario.
Price Outlook Analysis
Have you ever been surprised when a price of a Mutual Fund such as QS GROWTH is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading QS GROWTH backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Fund price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with QS GROWTH, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.04 | 0.87 | 0.00 | 0.23 | 0 Events | 1 Events | Uncertain |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
17.44 | 17.44 | 0.00 |
|
Hype Timeline
Qs Growth Fund is now traded for 17.44. The fund stock is not elastic to its hype. The average elasticity to hype of competition is -0.23. LLLRX is projected not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is projected to be very small, whereas the daily expected return is now at 0.04%. %. The volatility of related hype on QS GROWTH is about 14.93%, with the expected price after the next announcement by competition of 17.21. The fund last dividend was issued on the 27th of December 2019. Assuming a 90-day horizon the next projected press release will be uncertain. Cross-verify projections for QS GROWTH using Historical Fundamental Analysis of QS GROWTH. The view supplies historical context for the projection discussion.Related Hype Analysis
Understanding QS GROWTH's position within its competitive set helps investors assess whether news affecting a peer is a headwind or tailwind for QS GROWTH. This distinction requires knowledge of the competitive dynamics specific to QS GROWTH's industry.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| GCFSX | Gabelli Global Financial | -12.68 | 3 per month | 0.89 | 0.05 | 1.13 | -1.34 | 4.16 | |
| RMBKX | Rmb Mendon Financial | 0.18 | 1 per month | 1.17 | 0.12 | 2.62 | -1.76 | 8.81 | |
| BTO | John Hancock Financial | 1.46 | 8 per month | 0.00 | 0.01 | 1.90 | -1.97 | 9.02 | |
| VFAIX | Vanguard Financials Index | 0.05 | 1 per month | 0.00 | -0.08 | 1.69 | -2.00 | 5.68 | |
| FIKBX | Fidelity Advisor Financial | -29.79 | 4 per month | 0.00 | 0.01 | 1.90 | -1.87 | 10.33 | |
| IAAEX | Transamerica Financial Life | -0.02 | 1 per month | 0.51 | 0.13 | 1.78 | -1.32 | 19.97 | |
| XFINX | Angel Oak Financial | 0.00 | 2 per month | 0.00 | 0.05 | 0.22 | -0.43 | 1.29 |
Other Forecasting Options for QS GROWTH
Understanding QS GROWTH's price movement is a prerequisite for any investor considering LLLRX as a position. LLLRX Mutual Fund price charts are frequently cluttered with noise that can interfere with accurate interpretation.QS GROWTH Related Equities
The following equities are related to QS GROWTH within the Allocation--85%+ Equity space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing QS GROWTH against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
| Risk & Return | Correlation |
QS GROWTH Market Strength Events
For traders and investors in Qs Growth Fund, market strength indicators offer a quantitative framework for evaluating the mutual fund's responsiveness to market conditions. These tools help identify when trading QS GROWTH shares is most likely to generate favorable returns.
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 17.44 | |||
| Day Typical Price | 17.44 | |||
| Price Action Indicator | -0.05 | |||
| Period Momentum Indicator | -0.10 |
QS GROWTH Risk Indicators
Analyzing QS GROWTH's risk indicators provides a critical input for price forecasting and investment risk management. By quantifying the risk in QS GROWTH's investment, investors can make more informed decisions about their exposure and hedging strategies.
| Mean Deviation | 0.6136 | |||
| Semi Deviation | 0.7641 | |||
| Standard Deviation | 0.8489 | |||
| Variance | 0.7207 | |||
| Downside Variance | 0.6811 | |||
| Semi Variance | 0.5838 | |||
| Expected Short fall | -0.65 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for QS GROWTH
Coverage intensity for Qs Growth Fund matters because narrative visibility can influence sentiment, participation, and volatility around the name. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.
Other Macroaxis Stories
Story coverage on Macroaxis is built for readers who approach markets from different levels of experience but share the same need for disciplined investment context. Used well, these stories become part of a broader workflow built around idea generation, validation, and risk-adjusted portfolio design.