Agrogeneration Stock Forecast - Naive Prediction
ALAGR Stock | EUR 0.05 0.0002 0.42% |
The Naive Prediction forecasted value of Agrogeneration on the next trading day is expected to be 0.05 with a mean absolute deviation of 0 and the sum of the absolute errors of 0.15. Agrogeneration Stock Forecast is based on your current time horizon.
Agrogeneration |
Agrogeneration Naive Prediction Price Forecast For the 25th of November
Given 90 days horizon, the Naive Prediction forecasted value of Agrogeneration on the next trading day is expected to be 0.05 with a mean absolute deviation of 0, mean absolute percentage error of 0.00000999, and the sum of the absolute errors of 0.15.Please note that although there have been many attempts to predict Agrogeneration Stock 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 Agrogeneration's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Agrogeneration Stock Forecast Pattern
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Agrogeneration Forecasted Value
In the context of forecasting Agrogeneration's Stock 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. Agrogeneration's downside and upside margins for the forecasting period are 0.0005 and 5.61, respectively. We have considered Agrogeneration'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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Agrogeneration stock data series using in forecasting. Note that when a statistical model is used to represent Agrogeneration stock, 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 | 106.5971 |
Bias | Arithmetic mean of the errors | None |
MAD | Mean absolute deviation | 0.0025 |
MAPE | Mean absolute percentage error | 0.046 |
SAE | Sum of the absolute errors | 0.1505 |
Predictive Modules for Agrogeneration
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Agrogeneration. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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 Agrogeneration
For every potential investor in Agrogeneration, whether a beginner or expert, Agrogeneration's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Agrogeneration Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Agrogeneration. Basic forecasting techniques help filter out the noise by identifying Agrogeneration's price trends.Agrogeneration 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 Agrogeneration stock to make a market-neutral strategy. Peer analysis of Agrogeneration could also be used in its relative valuation, which is a method of valuing Agrogeneration by comparing valuation metrics with similar companies.
Risk & Return | Correlation |
Agrogeneration Technical and Predictive Analytics
The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Agrogeneration'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 Agrogeneration's current price.Cycle Indicators | ||
Math Operators | ||
Math Transform | ||
Momentum Indicators | ||
Overlap Studies | ||
Pattern Recognition | ||
Price Transform | ||
Statistic Functions | ||
Volatility Indicators | ||
Volume Indicators |
Agrogeneration Market Strength Events
Market strength indicators help investors to evaluate how Agrogeneration stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Agrogeneration shares will generate the highest return on investment. By undertsting and applying Agrogeneration stock market strength indicators, traders can identify Agrogeneration entry and exit signals to maximize returns.
Accumulation Distribution | 0.0424 | |||
Daily Balance Of Power | (0.10) | |||
Rate Of Daily Change | 1.0 | |||
Day Median Price | 0.0462 | |||
Day Typical Price | 0.0465 | |||
Market Facilitation Index | 0.002 | |||
Price Action Indicator | 7.0E-4 | |||
Period Momentum Indicator | (0.0002) | |||
Relative Strength Index | 57.08 |
Agrogeneration Risk Indicators
The analysis of Agrogeneration'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 Agrogeneration's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting agrogeneration stock 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 | 3.47 | |||
Standard Deviation | 5.56 | |||
Variance | 30.96 |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Additional Tools for Agrogeneration Stock Analysis
When running Agrogeneration's price analysis, check to measure Agrogeneration's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Agrogeneration is operating at the current time. Most of Agrogeneration's value examination focuses on studying past and present price action to predict the probability of Agrogeneration's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Agrogeneration's price. Additionally, you may evaluate how the addition of Agrogeneration to your portfolios can decrease your overall portfolio volatility.