Scharf ETF Etf Forecast - Simple Regression

KAT Etf   55.42  0.20  0.36%   
The Simple Regression forecasted value of Scharf ETF on the next trading day is expected to be 53.67 with a mean absolute deviation of 0.76 and the sum of the absolute errors of 47.23. Scharf 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 Scharf ETF 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.

Scharf ETF Simple Regression Price Forecast For the 26th of December

Given 90 days horizon, the Simple Regression forecasted value of Scharf ETF on the next trading day is expected to be 53.67 with a mean absolute deviation of 0.76, mean absolute percentage error of 0.81, and the sum of the absolute errors of 47.23.
Please note that although there have been many attempts to predict Scharf 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 Scharf ETF's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Scharf ETF Etf Forecast Pattern

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Scharf ETF Forecasted Value

In the context of forecasting Scharf ETF'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. Scharf ETF's downside and upside margins for the forecasting period are 53.00 and 54.34, respectively. We have considered Scharf ETF'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
55.42
53.67
Expected Value
54.34
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 Scharf ETF etf data series using in forecasting. Note that when a statistical model is used to represent Scharf ETF 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 Criteria119.7367
BiasArithmetic mean of the errors None
MADMean absolute deviation0.7617
MAPEMean absolute percentage error0.014
SAESum of the absolute errors47.2266
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 Scharf 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 Scharf ETF

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Scharf 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
54.7555.4256.09
Details
Intrinsic
Valuation
LowRealHigh
54.5755.2455.91
Details
Bollinger
Band Projection (param)
LowMiddleHigh
52.5554.7656.96
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Scharf ETF. Your research has to be compared to or analyzed against Scharf ETF's peers to derive any actionable benefits. When done correctly, Scharf ETF's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Scharf ETF.

Other Forecasting Options for Scharf ETF

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

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

Scharf 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 Scharf ETF'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 Scharf ETF's current price.

Scharf ETF Market Strength Events

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

Scharf ETF Risk Indicators

The analysis of Scharf ETF'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 Scharf ETF's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting scharf 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.

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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When determining whether Scharf ETF is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Scharf Etf is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Scharf Etf. Highlighted below are key reports to facilitate an investment decision about Scharf Etf:
Check out Historical Fundamental Analysis of Scharf ETF to cross-verify your projections.
For more information on how to buy Scharf Etf please use our How to Invest in Scharf ETF guide.
You can also try the My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
The market value of Scharf ETF is measured differently than its book value, which is the value of Scharf that is recorded on the company's balance sheet. Investors also form their own opinion of Scharf ETF's value that differs from its market value or its book value, called intrinsic value, which is Scharf ETF's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Scharf ETF's market value can be influenced by many factors that don't directly affect Scharf ETF's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Scharf ETF's value and its price as these two are different measures arrived at by different means. Investors typically determine if Scharf ETF is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Scharf ETF's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.