Quantified Market Mutual Fund Forecast - Naive Prediction
| QMLFX Fund | USD 11.65 0.01 0.09% |
The Naive Prediction forecasted value of Quantified Market Leaders on the next trading day is expected to be 11.52 with a mean absolute deviation of 0.16 and the sum of the absolute errors of 9.67. Quantified Mutual Fund Forecast is based on your current time horizon.
Quantified |
Quantified Market Naive Prediction Price Forecast For the 23rd of November
Given 90 days horizon, the Naive Prediction forecasted value of Quantified Market Leaders on the next trading day is expected to be 11.52 with a mean absolute deviation of 0.16, mean absolute percentage error of 0.04, and the sum of the absolute errors of 9.67.Please note that although there have been many attempts to predict Quantified Mutual Fund prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Quantified Market's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Quantified Market Mutual Fund Forecast Pattern
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Quantified Market Forecasted Value
In the context of forecasting Quantified Market's Mutual Fund value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Quantified Market's downside and upside margins for the forecasting period are 10.08 and 12.95, respectively. We have considered Quantified Market's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
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 Quantified Market mutual fund data series using in forecasting. Note that when a statistical model is used to represent Quantified Market 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 | 114.9539 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1585 |
| MAPE | Mean absolute percentage error | 0.0143 |
| SAE | Sum of the absolute errors | 9.6664 |
Predictive Modules for Quantified Market
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Quantified Market Leaders. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Other Forecasting Options for Quantified Market
For every potential investor in Quantified, whether a beginner or expert, Quantified Market's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Quantified Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Quantified. Basic forecasting techniques help filter out the noise by identifying Quantified Market's price trends.Quantified Market Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Quantified Market mutual fund to make a market-neutral strategy. Peer analysis of Quantified Market could also be used in its relative valuation, which is a method of valuing Quantified Market by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Quantified Market Leaders Technical and Predictive Analytics
The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Quantified Market's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Quantified Market's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Quantified Market Market Strength Events
Market strength indicators help investors to evaluate how Quantified Market mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Quantified Market shares will generate the highest return on investment. By undertsting and applying Quantified Market mutual fund market strength indicators, traders can identify Quantified Market Leaders entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 11.65 | |||
| Day Typical Price | 11.65 | |||
| Price Action Indicator | 0.005 | |||
| Period Momentum Indicator | 0.01 |
Quantified Market Risk Indicators
The analysis of Quantified Market's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Quantified Market's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting quantified mutual fund prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 1.04 | |||
| Semi Deviation | 1.33 | |||
| Standard Deviation | 1.46 | |||
| Variance | 2.13 | |||
| Downside Variance | 2.51 | |||
| Semi Variance | 1.77 | |||
| Expected Short fall | (1.11) |
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.
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.Other Information on Investing in Quantified Mutual Fund
Quantified Market financial ratios help investors to determine whether Quantified 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 Quantified with respect to the benefits of owning Quantified Market security.
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