Loblaw Companies Stock Forecast - Polynomial Regression

L Stock  CAD 181.70  0.25  0.14%   
The Polynomial Regression forecasted value of Loblaw Companies Limited on the next trading day is expected to be 180.46 with a mean absolute deviation of 2.37 and the sum of the absolute errors of 144.40. Loblaw Stock Forecast is based on your current time horizon.
  
Loblaw Companies polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Loblaw Companies Limited as well as the accuracy indicators are determined from the period prices.

Loblaw Companies Polynomial Regression Price Forecast For the 30th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Loblaw Companies Limited on the next trading day is expected to be 180.46 with a mean absolute deviation of 2.37, mean absolute percentage error of 8.70, and the sum of the absolute errors of 144.40.
Please note that although there have been many attempts to predict Loblaw 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 Loblaw Companies' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Loblaw Companies Stock Forecast Pattern

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Loblaw Companies Forecasted Value

In the context of forecasting Loblaw Companies' 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. Loblaw Companies' downside and upside margins for the forecasting period are 179.34 and 181.58, respectively. We have considered Loblaw Companies' 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
181.70
179.34
Downside
180.46
Expected Value
181.58
Upside

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 Loblaw Companies stock data series using in forecasting. Note that when a statistical model is used to represent Loblaw Companies 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 Criteria120.2743
BiasArithmetic mean of the errors None
MADMean absolute deviation2.3673
MAPEMean absolute percentage error0.0133
SAESum of the absolute errors144.4028
A single variable polynomial regression model attempts to put a curve through the Loblaw Companies 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 + ... + am*Xm

Predictive Modules for Loblaw Companies

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Loblaw Companies. 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.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Loblaw Companies' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
180.95182.08183.21
Details
Intrinsic
Valuation
LowRealHigh
179.40180.53200.15
Details

Other Forecasting Options for Loblaw Companies

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

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

Loblaw Companies 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 Loblaw Companies' 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 Loblaw Companies' current price.

Loblaw Companies Market Strength Events

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

Loblaw Companies Risk Indicators

The analysis of Loblaw Companies' 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 Loblaw Companies' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting loblaw 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.

Pair Trading with Loblaw Companies

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 Loblaw Companies 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 Loblaw Companies will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Loblaw Companies could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Loblaw Companies when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Loblaw Companies - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Loblaw Companies Limited to buy it.
The correlation of Loblaw Companies is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Loblaw Companies moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Loblaw Companies moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Loblaw Companies can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching

Other Information on Investing in Loblaw Stock

Loblaw Companies financial ratios help investors to determine whether Loblaw Stock 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 Loblaw with respect to the benefits of owning Loblaw Companies security.