Arrow EC Fund Forecast - 8 Period Moving Average
| ADIV Fund | 25.39 0.00 0.00% |
Momentum 75
Buy Stretched
Oversold | Overbought |
Using Arrow EC hype-based prediction, you can estimate the value of Arrow EC Equity from the perspective of Arrow EC response to recently generated media hype and the effects of current headlines on its competitors.
The 8 Period Moving Average forecasted value of Arrow EC Equity on the next trading day is expected to be 25.39 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.09. Arrow EC after-hype prediction price | CAD 25.39 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as fund price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Arrow |
Arrow EC Additional Predictive Modules
Most predictive techniques to examine Arrow price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Arrow using various technical indicators. When you analyze Arrow charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Arrow EC 8 Period Moving Average Price Forecast For the 10th of January
Given 90 days horizon, the 8 Period Moving Average forecasted value of Arrow EC Equity on the next trading day is expected to be 25.39 with a mean absolute deviation of 0.02, mean absolute percentage error of 0, and the sum of the absolute errors of 1.09.Please note that although there have been many attempts to predict Arrow Fund 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 Arrow EC's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Arrow EC Fund Forecast Pattern
Arrow EC Forecasted Value
In the context of forecasting Arrow EC's Fund 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. Arrow EC's downside and upside margins for the forecasting period are 25.26 and 25.52, respectively. We have considered Arrow EC'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 8 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Arrow EC fund data series using in forecasting. Note that when a statistical model is used to represent Arrow EC fund, 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 | 97.2296 |
| Bias | Arithmetic mean of the errors | -0.0204 |
| MAD | Mean absolute deviation | 0.0206 |
| MAPE | Mean absolute percentage error | 8.0E-4 |
| SAE | Sum of the absolute errors | 1.09 |
Predictive Modules for Arrow EC
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Arrow EC Equity. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the fund 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 Arrow EC
For every potential investor in Arrow, whether a beginner or expert, Arrow EC's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Arrow Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Arrow. Basic forecasting techniques help filter out the noise by identifying Arrow EC's price trends.Arrow EC 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 Arrow EC fund to make a market-neutral strategy. Peer analysis of Arrow EC could also be used in its relative valuation, which is a method of valuing Arrow EC by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Arrow EC Equity Technical and Predictive Analytics
The fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Arrow EC'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 Arrow EC's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Arrow EC Market Strength Events
Market strength indicators help investors to evaluate how Arrow EC fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Arrow EC shares will generate the highest return on investment. By undertsting and applying Arrow EC fund market strength indicators, traders can identify Arrow EC Equity entry and exit signals to maximize returns.
Arrow EC Risk Indicators
The analysis of Arrow EC'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 Arrow EC's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting arrow fund 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 | 0.0453 | |||
| Standard Deviation | 0.1254 | |||
| Variance | 0.0157 |
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 Arrow EC
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 Arrow EC 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 Arrow EC will appreciate offsetting losses from the drop in the long position's value.Moving together with Arrow Fund
| 0.65 | 0P0000S9O7 | PIMCO Monthly Income | PairCorr |
| 0.74 | 0P000072KJ | RBC Canadian Dividend | PairCorr |
The ability to find closely correlated positions to Arrow EC could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Arrow EC 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 Arrow EC - 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 Arrow EC Equity to buy it.
The correlation of Arrow EC 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 Arrow EC moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Arrow EC Equity 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 Arrow EC 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.| Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
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