Fauji Foods Stock Forecast - Polynomial Regression

Fauji Foods polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Fauji Foods as well as the accuracy indicators are determined from the period prices.

Fauji Foods Polynomial Regression Price Forecast For the 10th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Fauji Foods on the next trading day is expected to be 11.44 with a mean absolute deviation of 0.22, mean absolute percentage error of 0.09, and the sum of the absolute errors of 13.94.

Fauji Foods Stock Forecast Pattern

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Fauji Foods Price Prediction

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Fauji Foods Forecasted Value

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Fauji Foods stock data series using in forecasting. Note that when a statistical model is used to represent Fauji Foods 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. A single variable polynomial regression model attempts to put a curve through the Fauji Foods historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a₀ + a₁*X + a₂*X² + a₃*X³ + ... + a_m*X^m

Predictive Modules for Fauji Foods

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fauji Foods. 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 Low Estimated High 8.22 10.63 13.04 Details

Intrinsic Valuation Low Real High 6.01 8.42 10.83 Details

Bollinger Band Projection (param) Low Middle High 9.02 10.08 11.14 Details

Other Forecasting Options for Fauji Foods

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

Fauji Foods Related Equities

Risk & Return

Correlation

Fauji Foods 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 Fauji Foods' 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 Fauji Foods' current price.

Fauji Foods Market Strength Events

Fauji Foods Risk Indicators

Pair Trading with Fauji Foods

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Fauji Foods position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Fauji Foods will appreciate offsetting losses from the drop in the long position's value.

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