Waste Management Stock Forecast - Simple Regression
| WAST Stock | 20.67 0.23 1.10% |
The Simple Regression forecasted value of Waste Management CDR on the next trading day is expected to be 21.05 with a mean absolute deviation of 0.45 and the sum of the absolute errors of 28.03. Waste Stock Forecast is based on your current time horizon. Although Waste Management's naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Waste Management's systematic risk associated with finding meaningful patterns of Waste Management fundamentals over time.
As of today the relative strength index (rsi) of Waste Management's share price is below 20 . This entails that the stock is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Using Waste Management hype-based prediction, you can estimate the value of Waste Management CDR from the perspective of Waste Management response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Regression forecasted value of Waste Management CDR on the next trading day is expected to be 21.05 with a mean absolute deviation of 0.45 and the sum of the absolute errors of 28.03. Waste Management after-hype prediction price | CAD 20.67 |
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 stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Waste |
Waste Management Additional Predictive Modules
Most predictive techniques to examine Waste price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Waste using various technical indicators. When you analyze Waste 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 |
Waste Management Simple Regression Price Forecast For the 15th of January 2026
Given 90 days horizon, the Simple Regression forecasted value of Waste Management CDR on the next trading day is expected to be 21.05 with a mean absolute deviation of 0.45, mean absolute percentage error of 0.30, and the sum of the absolute errors of 28.03.Please note that although there have been many attempts to predict Waste 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 Waste Management's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Waste Management Stock Forecast Pattern
| Backtest Waste Management | Waste Management Price Prediction | Buy or Sell Advice |
Waste Management Forecasted Value
In the context of forecasting Waste Management'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. Waste Management's downside and upside margins for the forecasting period are 19.71 and 22.39, respectively. We have considered Waste Management'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 Simple Regression forecasting method's relative quality and the estimations of the prediction error of Waste Management stock data series using in forecasting. Note that when a statistical model is used to represent Waste Management 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 | 118.7494 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.4521 |
| MAPE | Mean absolute percentage error | 0.0225 |
| SAE | Sum of the absolute errors | 28.03 |
Predictive Modules for Waste Management
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Waste Management CDR. 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 Waste Management
For every potential investor in Waste, whether a beginner or expert, Waste Management's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Waste Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Waste. Basic forecasting techniques help filter out the noise by identifying Waste Management's price trends.Waste Management 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 Waste Management stock to make a market-neutral strategy. Peer analysis of Waste Management could also be used in its relative valuation, which is a method of valuing Waste Management by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Waste Management CDR 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 Waste Management'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 Waste Management's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Waste Management Market Strength Events
Market strength indicators help investors to evaluate how Waste Management stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Waste Management shares will generate the highest return on investment. By undertsting and applying Waste Management stock market strength indicators, traders can identify Waste Management CDR entry and exit signals to maximize returns.
| Accumulation Distribution | 59.07 | |||
| Daily Balance Of Power | (0.88) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 20.68 | |||
| Day Typical Price | 20.68 | |||
| Market Facilitation Index | 1.0E-4 | |||
| Price Action Indicator | (0.12) | |||
| Period Momentum Indicator | (0.23) |
Waste Management Risk Indicators
The analysis of Waste Management'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 Waste Management's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting waste 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 | 1.05 | |||
| Semi Deviation | 1.51 | |||
| Standard Deviation | 1.32 | |||
| Variance | 1.75 | |||
| Downside Variance | 2.35 | |||
| Semi Variance | 2.27 | |||
| Expected Short fall | (0.99) |
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 Waste Management
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 Waste Management 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 Waste Management will appreciate offsetting losses from the drop in the long position's value.Moving against Waste Stock
| 0.71 | CMC | Cielo Waste Solutions | PairCorr |
| 0.52 | ROOF | Northstar Clean Tech | PairCorr |
| 0.5 | AMZN | Amazon CDR | PairCorr |
| 0.5 | AMZN | Amazon CDR | PairCorr |
| 0.43 | BLM | BluMetric Environmental | PairCorr |
The ability to find closely correlated positions to Waste Management could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Waste Management 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 Waste Management - 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 Waste Management CDR to buy it.
The correlation of Waste Management 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 Waste Management moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Waste Management CDR 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 Waste Management 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.Other Information on Investing in Waste Stock
Waste Management financial ratios help investors to determine whether Waste Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Waste with respect to the benefits of owning Waste Management security.