QS GROWTH Mutual Fund Forward View
| LLLRX Fund | USD 17.12 -0.30 -1.72% |
The Naive Prediction reference data for QS GROWTH is derived from the equity's published trading history. The resulting forecast and deviation statistics are presented as reference data for informational context. Forecast values and accuracy statistics are presented for informational purposes. All values shown are derived from publicly available market data.
The Naive Prediction forecasted value of Qs Growth Fund on the next trading day is expected to be 17.25 with a mean absolute deviation of 0.10 and the sum of the absolute errors of 6.35.This model is not at all useful as a medium-long range forecasting tool of Qs Growth Fund. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict QS GROWTH. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights. The forecast reference data presented here for Qs Growth Fund reflects Naive Prediction model output and is intended as reference material for analytical use. Naive Prediction Price Forecast For the 28th of March
Given 90 days horizon, the Naive Prediction forecasted value of Qs Growth Fund on the next trading day is expected to be 17.25 with a mean absolute deviation of 0.10 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 6.35 .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
Forecasting Qs Growth Fund for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The projected forecast band currently runs from roughly 16.31 on the downside to about 18.20 on the upside.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Naive Prediction 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 | 115.8377 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1024 |
| MAPE | Mean absolute percentage error | 0.0057 |
| SAE | Sum of the absolute errors | 6.3469 |
Other Forecasting Options for QS GROWTH
Fibonacci retracement levels applied to LLLRX Mutual Fund price swings identify potential support and resistance zones. Extreme price moves in LLLRX occur more frequently than standard risk models assume. Support and resistance levels derived from QS GROWTH's historical data identify zones where buying or selling pressure has stalled moves. A volume spike without a corresponding price move can signal accumulation or distribution ahead of a directional breakout.QS GROWTH Related Equities
QS GROWTH's market space within the Allocation--85%+ Equity space is best grasped by looking at the firms listed below. Return on equity across these peers shows how well each firm turns capital into profit.
| Risk & Return | Correlation |
QS GROWTH Market Strength Events
Tracking market strength indicators for QS GROWTH provides context for understanding mutual fund momentum dynamics. Tracking these indicators helps identify periods where trading QS GROWTH is likely to be most rewarding. These tools are essential for timing trades in Qs Growth Fund with a quantitative framework. Market strength indicators for Qs Growth Fund are most useful when viewed as part of a broader analytical framework.
| Rate Of Daily Change | 0.98 | |||
| Day Median Price | 17.12 | |||
| Day Typical Price | 17.12 | |||
| Price Action Indicator | -0.15 | |||
| Period Momentum Indicator | -0.30 | |||
| Relative Strength Index | 40.96 |
QS GROWTH Risk Indicators
Properly assessing QS GROWTH's risk indicators is a prerequisite for building reliable price forecasts. This analysis provides context for determining the appropriate level of risk to accept when holding QS GROWTH's. Analyzing QS GROWTH's risk indicators provides a critical input for investment risk management. By quantifying the risk in QS GROWTH's investment, investors can make more informed decisions about hedging strategies.
| Mean Deviation | 0.6706 | |||
| Standard Deviation | 0.912 | |||
| Variance | 0.8318 |
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
A coverage review of Qs Growth Fund shows when the security is attracting above-average attention from contributors and market observers. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.
Other Macroaxis Stories
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.