BMO Equal Etf Forecast - Simple Regression

ZUB Etf  CAD 35.70  0.08  0.22%   
The Simple Regression forecasted value of BMO Equal Weight on the next trading day is expected to be 34.83 with a mean absolute deviation of 0.80 and the sum of the absolute errors of 49.31. BMO Etf 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 BMO Equal 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.

BMO Equal Simple Regression Price Forecast For the 28th of November

Given 90 days horizon, the Simple Regression forecasted value of BMO Equal Weight on the next trading day is expected to be 34.83 with a mean absolute deviation of 0.80, mean absolute percentage error of 0.94, and the sum of the absolute errors of 49.31.
Please note that although there have been many attempts to predict BMO Etf 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 BMO Equal's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

BMO Equal Etf Forecast Pattern

Backtest BMO EqualBMO Equal Price PredictionBuy or Sell Advice 

BMO Equal Forecasted Value

In the context of forecasting BMO Equal's Etf 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. BMO Equal's downside and upside margins for the forecasting period are 32.89 and 36.78, respectively. We have considered BMO Equal'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
35.70
34.83
Expected Value
36.78
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 BMO Equal etf data series using in forecasting. Note that when a statistical model is used to represent BMO Equal etf, 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 Criteria119.8882
BiasArithmetic mean of the errors None
MADMean absolute deviation0.7953
MAPEMean absolute percentage error0.0255
SAESum of the absolute errors49.3098
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 BMO Equal Weight 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 BMO Equal

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as BMO Equal Weight. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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
33.7735.7037.63
Details
Intrinsic
Valuation
LowRealHigh
32.1337.8139.74
Details

Other Forecasting Options for BMO Equal

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

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

BMO Equal Weight Technical and Predictive Analytics

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

BMO Equal Market Strength Events

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

BMO Equal Risk Indicators

The analysis of BMO Equal'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 BMO Equal's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting bmo etf 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 BMO Equal

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 BMO Equal 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 BMO Equal will appreciate offsetting losses from the drop in the long position's value.

Moving together with BMO Etf

  0.75ZEB BMO SPTSX EqualPairCorr
  0.83XFN iShares SPTSX CappedPairCorr
  1.0ZBK BMO Equal WeightPairCorr
  0.72HCA Hamilton Canadian BankPairCorr

Moving against BMO Etf

  0.5QDX Mackenzie InternationalPairCorr
The ability to find closely correlated positions to BMO Equal could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace BMO Equal 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 BMO Equal - 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 BMO Equal Weight to buy it.
The correlation of BMO Equal 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 BMO Equal moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if BMO Equal Weight 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 BMO Equal 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 BMO Etf

BMO Equal financial ratios help investors to determine whether BMO Etf 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 BMO with respect to the benefits of owning BMO Equal security.