FDO INV Fund Forecast - 20 Period Moving Average
| AGRX11 Fund | 7.22 0.18 2.56% |
FDO |
FDO INV 20 Period Moving Average Price Forecast For the 26th of November
Given 90 days horizon, the 20 Period Moving Average forecasted value of FDO INV CAD on the next trading day is expected to be 7.27 with a mean absolute deviation of 0.73, mean absolute percentage error of 0.64, and the sum of the absolute errors of 29.90.Please note that although there have been many attempts to predict FDO 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 FDO INV's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
FDO INV Fund Forecast Pattern
FDO INV Forecasted Value
In the context of forecasting FDO INV'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. FDO INV's downside and upside margins for the forecasting period are 4.68 and 9.86, respectively. We have considered FDO INV'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 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of FDO INV fund data series using in forecasting. Note that when a statistical model is used to represent FDO INV 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 | 80.9134 |
| Bias | Arithmetic mean of the errors | 0.7294 |
| MAD | Mean absolute deviation | 0.7294 |
| MAPE | Mean absolute percentage error | 0.0931 |
| SAE | Sum of the absolute errors | 29.9035 |
Predictive Modules for FDO INV
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as FDO INV CAD. 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 FDO INV
For every potential investor in FDO, whether a beginner or expert, FDO INV's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. FDO Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in FDO. Basic forecasting techniques help filter out the noise by identifying FDO INV's price trends.FDO INV 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 FDO INV fund to make a market-neutral strategy. Peer analysis of FDO INV could also be used in its relative valuation, which is a method of valuing FDO INV by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
FDO INV CAD 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 FDO INV'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 FDO INV's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
FDO INV Market Strength Events
Market strength indicators help investors to evaluate how FDO INV fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading FDO INV shares will generate the highest return on investment. By undertsting and applying FDO INV fund market strength indicators, traders can identify FDO INV CAD entry and exit signals to maximize returns.
FDO INV Risk Indicators
The analysis of FDO INV'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 FDO INV's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fdo 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 | 1.54 | |||
| Standard Deviation | 2.39 | |||
| Variance | 5.74 |
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.
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