KraneShares Electric Etf Forecast - Double Exponential Smoothing
| KARS Etf | 16.04 0.09 0.56% |
The Double Exponential Smoothing forecasted value of KraneShares Electric Vehicles on the next trading day is expected to be 16.05 with a mean absolute deviation of 0.33 and the sum of the absolute errors of 19.63. KraneShares Etf Forecast is based on your current time horizon.
KraneShares |
KraneShares Electric Double Exponential Smoothing Price Forecast For the 29th of November
Given 90 days horizon, the Double Exponential Smoothing forecasted value of KraneShares Electric Vehicles on the next trading day is expected to be 16.05 with a mean absolute deviation of 0.33, mean absolute percentage error of 0.16, and the sum of the absolute errors of 19.63.Please note that although there have been many attempts to predict KraneShares 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 KraneShares Electric's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
KraneShares Electric Etf Forecast Pattern
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KraneShares Electric Forecasted Value
In the context of forecasting KraneShares Electric'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. KraneShares Electric's downside and upside margins for the forecasting period are 13.70 and 18.39, respectively. We have considered KraneShares Electric'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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of KraneShares Electric etf data series using in forecasting. Note that when a statistical model is used to represent KraneShares Electric 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.| AIC | Akaike Information Criteria | Huge |
| Bias | Arithmetic mean of the errors | -0.0202 |
| MAD | Mean absolute deviation | 0.3326 |
| MAPE | Mean absolute percentage error | 0.0208 |
| SAE | Sum of the absolute errors | 19.6258 |
Predictive Modules for KraneShares Electric
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as KraneShares Electric. 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.Other Forecasting Options for KraneShares Electric
For every potential investor in KraneShares, whether a beginner or expert, KraneShares Electric's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. KraneShares Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in KraneShares. Basic forecasting techniques help filter out the noise by identifying KraneShares Electric's price trends.KraneShares Electric 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 KraneShares Electric etf to make a market-neutral strategy. Peer analysis of KraneShares Electric could also be used in its relative valuation, which is a method of valuing KraneShares Electric by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
KraneShares Electric 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 KraneShares Electric'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 KraneShares Electric's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
KraneShares Electric Market Strength Events
Market strength indicators help investors to evaluate how KraneShares Electric etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading KraneShares Electric shares will generate the highest return on investment. By undertsting and applying KraneShares Electric etf market strength indicators, traders can identify KraneShares Electric Vehicles entry and exit signals to maximize returns.
KraneShares Electric Risk Indicators
The analysis of KraneShares Electric'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 KraneShares Electric's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting kraneshares 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.
| Mean Deviation | 1.87 | |||
| Semi Deviation | 2.09 | |||
| Standard Deviation | 2.34 | |||
| Variance | 5.49 | |||
| Downside Variance | 5.15 | |||
| Semi Variance | 4.36 | |||
| Expected Short fall | (2.09) |
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.When determining whether KraneShares Electric is a strong investment it is important to analyze KraneShares Electric's competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact KraneShares Electric's future performance. For an informed investment choice regarding KraneShares Etf, refer to the following important reports:Check out Historical Fundamental Analysis of KraneShares Electric to cross-verify your projections. You can also try the Premium Stories module to follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope.