Food Moments Stock Forecast - Double Exponential Smoothing
FM Stock | 3.66 0.06 1.61% |
Food |
Food Moments Double Exponential Smoothing Price Forecast For the 28th of December
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Food Moments PCL on the next trading day is expected to be 3.64 with a mean absolute deviation of 0.07, mean absolute percentage error of 0.01, and the sum of the absolute errors of 4.16.Please note that although there have been many attempts to predict Food 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 Food Moments' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Food Moments Stock Forecast Pattern
Food Moments Forecasted Value
In the context of forecasting Food Moments' 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. Food Moments' downside and upside margins for the forecasting period are 1.80 and 5.49, respectively. We have considered Food Moments' 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 Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Food Moments stock data series using in forecasting. Note that when a statistical model is used to represent Food Moments 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 | Huge |
Bias | Arithmetic mean of the errors | -0.0101 |
MAD | Mean absolute deviation | 0.0693 |
MAPE | Mean absolute percentage error | 0.0169 |
SAE | Sum of the absolute errors | 4.1554 |
Predictive Modules for Food Moments
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Food Moments PCL. 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.Please note, it is not enough to conduct a financial or market analysis of a single entity such as Food Moments. Your research has to be compared to or analyzed against Food Moments' peers to derive any actionable benefits. When done correctly, Food Moments' competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Food Moments PCL.Other Forecasting Options for Food Moments
For every potential investor in Food, whether a beginner or expert, Food Moments' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Food Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Food. Basic forecasting techniques help filter out the noise by identifying Food Moments' price trends.Food Moments 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 Food Moments stock to make a market-neutral strategy. Peer analysis of Food Moments could also be used in its relative valuation, which is a method of valuing Food Moments by comparing valuation metrics with similar companies.
Risk & Return | Correlation |
Food Moments PCL 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 Food Moments' 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 Food Moments' current price.Cycle Indicators | ||
Math Operators | ||
Math Transform | ||
Momentum Indicators | ||
Overlap Studies | ||
Pattern Recognition | ||
Price Transform | ||
Statistic Functions | ||
Volatility Indicators | ||
Volume Indicators |
Food Moments Market Strength Events
Market strength indicators help investors to evaluate how Food Moments stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Food Moments shares will generate the highest return on investment. By undertsting and applying Food Moments stock market strength indicators, traders can identify Food Moments PCL entry and exit signals to maximize returns.
Accumulation Distribution | 134031.0 | |||
Daily Balance Of Power | (0.50) | |||
Rate Of Daily Change | 0.98 | |||
Day Median Price | 3.68 | |||
Day Typical Price | 3.67 | |||
Price Action Indicator | (0.05) | |||
Period Momentum Indicator | (0.06) |
Food Moments Risk Indicators
The analysis of Food Moments' 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 Food Moments' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting food 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 | 1.5 | |||
Standard Deviation | 1.88 | |||
Variance | 3.52 |
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.
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio Architect