Tech Leaders Etf Forecast - Simple Regression

TLF Etf  CAD 25.29  0.05  0.20%   
The Simple Regression forecasted value of Tech Leaders Income on the next trading day is expected to be 25.59 with a mean absolute deviation of 0.32 and the sum of the absolute errors of 19.81. Tech 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 Tech Leaders 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.

Tech Leaders Simple Regression Price Forecast For the 24th of November

Given 90 days horizon, the Simple Regression forecasted value of Tech Leaders Income on the next trading day is expected to be 25.59 with a mean absolute deviation of 0.32, mean absolute percentage error of 0.15, and the sum of the absolute errors of 19.81.
Please note that although there have been many attempts to predict Tech 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 Tech Leaders' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Tech Leaders Etf Forecast Pattern

Backtest Tech LeadersTech Leaders Price PredictionBuy or Sell Advice 

Tech Leaders Forecasted Value

In the context of forecasting Tech Leaders' 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. Tech Leaders' downside and upside margins for the forecasting period are 24.42 and 26.75, respectively. We have considered Tech Leaders' 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
25.29
25.59
Expected Value
26.75
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 Tech Leaders etf data series using in forecasting. Note that when a statistical model is used to represent Tech Leaders 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 Criteria116.2395
BiasArithmetic mean of the errors None
MADMean absolute deviation0.3247
MAPEMean absolute percentage error0.0134
SAESum of the absolute errors19.8089
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 Tech Leaders Income 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 Tech Leaders

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Tech Leaders Income. 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
24.1125.2926.47
Details
Intrinsic
Valuation
LowRealHigh
23.7824.9626.14
Details
Bollinger
Band Projection (param)
LowMiddleHigh
24.8725.2025.53
Details

Other Forecasting Options for Tech Leaders

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

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

Tech Leaders Income 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 Tech Leaders' 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 Tech Leaders' current price.

Tech Leaders Market Strength Events

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

Tech Leaders Risk Indicators

The analysis of Tech Leaders' 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 Tech Leaders' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting tech 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 Tech Leaders

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 Tech Leaders 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 Tech Leaders will appreciate offsetting losses from the drop in the long position's value.

Moving together with Tech Etf

  0.88XIT iShares SPTSX CappedPairCorr

Moving against Tech Etf

  0.74XHC iShares Global HealthcarePairCorr
  0.72HHL Harvest HealthcarePairCorr
  0.68TCLB TD Canadian LongPairCorr
  0.66ZUH BMO Equal WeightPairCorr
  0.36ZAG BMO Aggregate BondPairCorr
The ability to find closely correlated positions to Tech Leaders could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Tech Leaders 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 Tech Leaders - 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 Tech Leaders Income to buy it.
The correlation of Tech Leaders 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 Tech Leaders moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Tech Leaders Income 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 Tech Leaders 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 Tech Etf

Tech Leaders financial ratios help investors to determine whether Tech 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 Tech with respect to the benefits of owning Tech Leaders security.