Amazon Stock Forecast - Simple Exponential Smoothing

AMZ Stock  EUR 216.95  0.05  0.02%   
The Simple Exponential Smoothing forecasted value of Amazon Inc on the next trading day is expected to be 216.95 with a mean absolute deviation of 2.32 and the sum of the absolute errors of 139.33. Amazon Stock Forecast is based on your current time horizon.
  
Amazon simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for Amazon Inc are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Amazon Inc prices get older.

Amazon Simple Exponential Smoothing Price Forecast For the 27th of December

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Amazon Inc on the next trading day is expected to be 216.95 with a mean absolute deviation of 2.32, mean absolute percentage error of 9.03, and the sum of the absolute errors of 139.33.
Please note that although there have been many attempts to predict Amazon 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 Amazon's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Amazon Stock Forecast Pattern

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Amazon Forecasted Value

In the context of forecasting Amazon'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. Amazon's downside and upside margins for the forecasting period are 215.43 and 218.47, respectively. We have considered Amazon'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.
Market Value
216.95
215.43
Downside
216.95
Expected Value
218.47
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Amazon stock data series using in forecasting. Note that when a statistical model is used to represent Amazon 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.
AICAkaike Information Criteria118.4728
BiasArithmetic mean of the errors -0.8475
MADMean absolute deviation2.3222
MAPEMean absolute percentage error0.0122
SAESum of the absolute errors139.33
This simple exponential smoothing model begins by setting Amazon Inc forecast for the second period equal to the observation of the first period. In other words, recent Amazon observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Amazon

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Amazon Inc. 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.
Hype
Prediction
LowEstimatedHigh
215.43216.95218.47
Details
Intrinsic
Valuation
LowRealHigh
195.26241.91243.43
Details

Other Forecasting Options for Amazon

For every potential investor in Amazon, whether a beginner or expert, Amazon's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Amazon Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Amazon. Basic forecasting techniques help filter out the noise by identifying Amazon's price trends.

Amazon 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 Amazon stock to make a market-neutral strategy. Peer analysis of Amazon could also be used in its relative valuation, which is a method of valuing Amazon by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Amazon Inc 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 Amazon'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 Amazon's current price.

Amazon Market Strength Events

Market strength indicators help investors to evaluate how Amazon stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Amazon shares will generate the highest return on investment. By undertsting and applying Amazon stock market strength indicators, traders can identify Amazon Inc entry and exit signals to maximize returns.

Amazon Risk Indicators

The analysis of Amazon'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 Amazon's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting amazon 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.
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.

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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Additional Tools for Amazon Stock Analysis

When running Amazon's price analysis, check to measure Amazon'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 Amazon is operating at the current time. Most of Amazon's value examination focuses on studying past and present price action to predict the probability of Amazon's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Amazon's price. Additionally, you may evaluate how the addition of Amazon to your portfolios can decrease your overall portfolio volatility.