HAN GINS Etf Forecast - Polynomial Regression
| WELL Etf | 6.54 0.12 1.80% |
HAN |
HAN GINS Polynomial Regression Price Forecast For the 19th of December
Given 90 days horizon, the Polynomial Regression forecasted value of HAN GINS Indxx Healthcare on the next trading day is expected to be 6.72 with a mean absolute deviation of 0.06, mean absolute percentage error of 0.01, and the sum of the absolute errors of 3.66.Please note that although there have been many attempts to predict HAN 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 HAN GINS's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
HAN GINS Etf Forecast Pattern
HAN GINS Forecasted Value
In the context of forecasting HAN GINS'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. HAN GINS's downside and upside margins for the forecasting period are 5.67 and 7.78, respectively. We have considered HAN GINS'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 Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of HAN GINS etf data series using in forecasting. Note that when a statistical model is used to represent HAN GINS 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 | 113.1137 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0599 |
| MAPE | Mean absolute percentage error | 0.0089 |
| SAE | Sum of the absolute errors | 3.6557 |
Predictive Modules for HAN GINS
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as HAN GINS Indxx. 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 HAN GINS
For every potential investor in HAN, whether a beginner or expert, HAN GINS's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. HAN Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in HAN. Basic forecasting techniques help filter out the noise by identifying HAN GINS's price trends.HAN GINS 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 HAN GINS etf to make a market-neutral strategy. Peer analysis of HAN GINS could also be used in its relative valuation, which is a method of valuing HAN GINS by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
HAN GINS Indxx 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 HAN GINS'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 HAN GINS's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
HAN GINS Market Strength Events
Market strength indicators help investors to evaluate how HAN GINS etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading HAN GINS shares will generate the highest return on investment. By undertsting and applying HAN GINS etf market strength indicators, traders can identify HAN GINS Indxx Healthcare entry and exit signals to maximize returns.
HAN GINS Risk Indicators
The analysis of HAN GINS'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 HAN GINS's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting han 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 | 0.3917 | |||
| Standard Deviation | 1.04 | |||
| Variance | 1.08 |
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.