HANetf ICAV Etf Forecast - Polynomial Regression
| M7ES Etf | 5.59 0.00 0.00% |
HANetf |
HANetf ICAV Polynomial Regression Price Forecast For the 27th of December
Given 90 days horizon, the Polynomial Regression forecasted value of HANetf ICAV on the next trading day is expected to be 5.32 with a mean absolute deviation of 0.12, mean absolute percentage error of 0.02, and the sum of the absolute errors of 7.12.Please note that although there have been many attempts to predict HANetf 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 HANetf ICAV's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
HANetf ICAV Etf Forecast Pattern
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 HANetf ICAV etf data series using in forecasting. Note that when a statistical model is used to represent HANetf ICAV 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 | 114.276 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1167 |
| MAPE | Mean absolute percentage error | 0.0219 |
| SAE | Sum of the absolute errors | 7.1171 |
Predictive Modules for HANetf ICAV
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as HANetf ICAV. 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.HANetf ICAV 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 HANetf ICAV etf to make a market-neutral strategy. Peer analysis of HANetf ICAV could also be used in its relative valuation, which is a method of valuing HANetf ICAV by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
HANetf ICAV Market Strength Events
Market strength indicators help investors to evaluate how HANetf ICAV etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading HANetf ICAV shares will generate the highest return on investment. By undertsting and applying HANetf ICAV etf market strength indicators, traders can identify HANetf ICAV entry and exit signals to maximize returns.
HANetf ICAV Risk Indicators
The analysis of HANetf ICAV'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 HANetf ICAV's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting hanetf 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 | 1.37 | |||
| Semi Deviation | 1.59 | |||
| Standard Deviation | 1.78 | |||
| Variance | 3.17 | |||
| Downside Variance | 2.94 | |||
| Semi Variance | 2.52 | |||
| Expected Short fall | (1.61) |
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.