CI Munro Etf Forecast - Simple Regression

CMAG Etf  CAD 37.45  0.29  0.78%   
The Simple Regression forecasted value of CI Munro Alternative on the next trading day is expected to be 37.64 with a mean absolute deviation of 0.34 and the sum of the absolute errors of 20.44. CMAG 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 CI Munro 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.

CI Munro Simple Regression Price Forecast For the 1st of December

Given 90 days horizon, the Simple Regression forecasted value of CI Munro Alternative on the next trading day is expected to be 37.64 with a mean absolute deviation of 0.34, mean absolute percentage error of 0.19, and the sum of the absolute errors of 20.44.
Please note that although there have been many attempts to predict CMAG 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 CI Munro's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

CI Munro Etf Forecast Pattern

Backtest CI MunroCI Munro Price PredictionBuy or Sell Advice 

CI Munro Forecasted Value

In the context of forecasting CI Munro'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. CI Munro's downside and upside margins for the forecasting period are 36.60 and 38.68, respectively. We have considered CI Munro'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
37.45
37.64
Expected Value
38.68
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 CI Munro etf data series using in forecasting. Note that when a statistical model is used to represent CI Munro 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 Criteria116.4681
BiasArithmetic mean of the errors None
MADMean absolute deviation0.3351
MAPEMean absolute percentage error0.0095
SAESum of the absolute errors20.4405
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 CI Munro Alternative 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 CI Munro

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as CI Munro Alternative. 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
36.4137.4538.49
Details
Intrinsic
Valuation
LowRealHigh
35.8036.8437.88
Details
Bollinger
Band Projection (param)
LowMiddleHigh
36.6137.1937.78
Details

Other Forecasting Options for CI Munro

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

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

CI Munro Alternative 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 CI Munro'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 CI Munro's current price.

CI Munro Market Strength Events

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

CI Munro Risk Indicators

The analysis of CI Munro'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 CI Munro's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting cmag 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 CI Munro

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 CI Munro 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 CI Munro will appreciate offsetting losses from the drop in the long position's value.

Moving together with CMAG Etf

  0.97XIU iShares SPTSX 60PairCorr
  0.98XSP iShares Core SPPairCorr
  0.97XIC iShares Core SPTSXPairCorr

Moving against CMAG Etf

  0.65TCLB TD Canadian LongPairCorr
  0.46VGV Vanguard CanadianPairCorr
  0.36VLB Vanguard Canadian LongPairCorr
  0.34HBB Global X CanadianPairCorr
  0.33XLB iShares Core CanadianPairCorr
The ability to find closely correlated positions to CI Munro could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace CI Munro 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 CI Munro - 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 CI Munro Alternative to buy it.
The correlation of CI Munro 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 CI Munro moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if CI Munro Alternative 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 CI Munro 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 CMAG Etf

CI Munro financial ratios help investors to determine whether CMAG 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 CMAG with respect to the benefits of owning CI Munro security.