IShares SMI Etf Forecast - Simple Regression

CSSMI Etf  CHF 121.30  0.22  0.18%   
The Simple Regression forecasted value of iShares SMI ETF on the next trading day is expected to be 120.38 with a mean absolute deviation of 1.18 and the sum of the absolute errors of 71.82. IShares 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 IShares SMI 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.

IShares SMI Simple Regression Price Forecast For the 16th of December 2024

Given 90 days horizon, the Simple Regression forecasted value of iShares SMI ETF on the next trading day is expected to be 120.38 with a mean absolute deviation of 1.18, mean absolute percentage error of 2.02, and the sum of the absolute errors of 71.82.
Please note that although there have been many attempts to predict IShares 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 IShares SMI's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

IShares SMI Etf Forecast Pattern

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IShares SMI Forecasted Value

In the context of forecasting IShares SMI'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. IShares SMI's downside and upside margins for the forecasting period are 119.67 and 121.08, respectively. We have considered IShares SMI'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
121.30
119.67
Downside
120.38
Expected Value
121.08
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 IShares SMI etf data series using in forecasting. Note that when a statistical model is used to represent IShares SMI 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 Criteria118.8156
BiasArithmetic mean of the errors None
MADMean absolute deviation1.1774
MAPEMean absolute percentage error0.0095
SAESum of the absolute errors71.8199
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 iShares SMI ETF 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 IShares SMI

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as iShares SMI ETF. 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
120.60121.30122.00
Details
Intrinsic
Valuation
LowRealHigh
121.22121.92122.62
Details
Bollinger
Band Projection (param)
LowMiddleHigh
120.59121.17121.74
Details

Other Forecasting Options for IShares SMI

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

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

iShares SMI ETF 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 IShares SMI'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 IShares SMI's current price.

IShares SMI Market Strength Events

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

IShares SMI Risk Indicators

The analysis of IShares SMI'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 IShares SMI's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ishares 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Other Information on Investing in IShares Etf

IShares SMI financial ratios help investors to determine whether IShares 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 IShares with respect to the benefits of owning IShares SMI security.