QRF SCA Stock Forecast - Simple Regression

QRF Stock  EUR 10.40  0.15  1.46%   
The Simple Regression forecasted value of QRF SCA on the next trading day is expected to be 10.37 with a mean absolute deviation of 0.09 and the sum of the absolute errors of 5.74. QRF Stock Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through QRF SCA price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

QRF SCA Simple Regression Price Forecast For the 3rd of March

Given 90 days horizon, the Simple Regression forecasted value of QRF SCA on the next trading day is expected to be 10.37 with a mean absolute deviation of 0.09, mean absolute percentage error of 0.01, and the sum of the absolute errors of 5.74.
Please note that although there have been many attempts to predict QRF Stock 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 QRF SCA's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

QRF SCA Stock Forecast Pattern

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QRF SCA Forecasted Value

In the context of forecasting QRF SCA's Stock 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. QRF SCA's downside and upside margins for the forecasting period are 9.09 and 11.66, respectively. We have considered QRF SCA'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.
Market Value
10.40
10.37
Expected Value
11.66
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of QRF SCA stock data series using in forecasting. Note that when a statistical model is used to represent QRF SCA stock, 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.
AICAkaike Information Criteria113.8666
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0941
MAPEMean absolute percentage error0.0091
SAESum of the absolute errors5.7382
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as QRF SCA historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for QRF SCA

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as QRF SCA. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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.
Hype
Prediction
LowEstimatedHigh
9.1110.4011.69
Details
Intrinsic
Valuation
LowRealHigh
9.1010.3911.68
Details
Bollinger
Band Projection (param)
LowMiddleHigh
10.1510.3710.59
Details

Other Forecasting Options for QRF SCA

For every potential investor in QRF, whether a beginner or expert, QRF SCA's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. QRF Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in QRF. Basic forecasting techniques help filter out the noise by identifying QRF SCA's price trends.

QRF SCA 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 QRF SCA stock to make a market-neutral strategy. Peer analysis of QRF SCA could also be used in its relative valuation, which is a method of valuing QRF SCA by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

QRF SCA Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of QRF SCA'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 QRF SCA's current price.

QRF SCA Market Strength Events

Market strength indicators help investors to evaluate how QRF SCA stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading QRF SCA shares will generate the highest return on investment. By undertsting and applying QRF SCA stock market strength indicators, traders can identify QRF SCA entry and exit signals to maximize returns.

QRF SCA Risk Indicators

The analysis of QRF SCA'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 QRF SCA's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting qrf stock 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.
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.

Additional Tools for QRF Stock Analysis

When running QRF SCA's price analysis, check to measure QRF SCA's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy QRF SCA is operating at the current time. Most of QRF SCA's value examination focuses on studying past and present price action to predict the probability of QRF SCA's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move QRF SCA's price. Additionally, you may evaluate how the addition of QRF SCA to your portfolios can decrease your overall portfolio volatility.