Amundi Index Etf Forecast - Polynomial Regression
| CEU Etf | EUR 326.43 3.61 1.12% |
The Polynomial Regression forecasted value of Amundi Index Solutions on the next trading day is expected to be 321.09 with a mean absolute deviation of 1.87 and the sum of the absolute errors of 114.01. Amundi Etf Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Amundi Index stock prices and determine the direction of Amundi Index Solutions's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Amundi Index's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Amundi Index to cross-verify your projections. Amundi |
Most investors in Amundi Index cannot accurately predict what will happen the next trading day because, historically, etf markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Amundi Index's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Amundi Index's price structures and extracts relationships that further increase the generated results' accuracy.
Amundi Index polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Amundi Index Solutions as well as the accuracy indicators are determined from the period prices. Amundi Index Polynomial Regression Price Forecast For the 29th of April
Given 90 days horizon, the Polynomial Regression forecasted value of Amundi Index Solutions on the next trading day is expected to be 321.09 with a mean absolute deviation of 1.87, mean absolute percentage error of 5.32, and the sum of the absolute errors of 114.01.Please note that although there have been many attempts to predict Amundi 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 Amundi Index's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Amundi Index Etf Forecast Pattern
| Backtest Amundi Index | Amundi Index Price Prediction | Buy or Sell Advice |
Amundi Index Forecasted Value
In the context of forecasting Amundi Index'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. Amundi Index's downside and upside margins for the forecasting period are 320.56 and 321.62, respectively. We have considered Amundi Index'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 Amundi Index etf data series using in forecasting. Note that when a statistical model is used to represent Amundi Index 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 | 119.7825 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.8691 |
| MAPE | Mean absolute percentage error | 0.0059 |
| SAE | Sum of the absolute errors | 114.0123 |
Predictive Modules for Amundi Index
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Amundi Index Solutions. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Amundi Index's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Other Forecasting Options for Amundi Index
For every potential investor in Amundi, whether a beginner or expert, Amundi Index's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Amundi Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Amundi. Basic forecasting techniques help filter out the noise by identifying Amundi Index's price trends.Amundi Index 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 Amundi Index etf to make a market-neutral strategy. Peer analysis of Amundi Index could also be used in its relative valuation, which is a method of valuing Amundi Index by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Amundi Index Solutions 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 Amundi Index'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 Amundi Index's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Amundi Index Market Strength Events
Market strength indicators help investors to evaluate how Amundi Index etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Amundi Index shares will generate the highest return on investment. By undertsting and applying Amundi Index etf market strength indicators, traders can identify Amundi Index Solutions entry and exit signals to maximize returns.
Amundi Index Risk Indicators
The analysis of Amundi Index'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 Amundi Index's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting amundi 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 | 0.3978 | |||
| Semi Deviation | 0.3571 | |||
| Standard Deviation | 0.5425 | |||
| Variance | 0.2943 | |||
| Downside Variance | 0.3268 | |||
| Semi Variance | 0.1276 | |||
| Expected Short fall | (0.40) |
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.
Pair Trading with Amundi Index
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Amundi Index position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Amundi Index will appreciate offsetting losses from the drop in the long position's value.Moving together with Amundi Etf
| 0.89 | JPNH | Lyxor UCITS Japan | PairCorr |
| 0.82 | JPN | Lyxor UCITS Japan | PairCorr |
| 0.98 | MSE | Lyxor UCITS Stoxx | PairCorr |
| 0.97 | CAC | Lyxor UCITS CAC | PairCorr |
The ability to find closely correlated positions to Amundi Index could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Amundi Index when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Amundi Index - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Amundi Index Solutions to buy it.
The correlation of Amundi Index is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Amundi Index moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Amundi Index Solutions moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Amundi Index can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Historical Fundamental Analysis of Amundi Index to cross-verify your projections. You can also try the Insider Screener module to find insiders across different sectors to evaluate their impact on performance.