Waste Connections Stock Forecast - Simple Regression
| WCN Stock | CAD 263.24 0.88 0.33% |
The Simple Regression forecasted value of Waste Connections on the next trading day is expected to be 269.14 with a mean absolute deviation of 3.76 and the sum of the absolute errors of 233.40. Waste Stock Forecast is based on your current time horizon. Although Waste Connections' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Waste Connections' systematic risk associated with finding meaningful patterns of Waste Connections fundamentals over time.
Waste |
Waste Connections Simple Regression Price Forecast For the 12th of December 2024
Given 90 days horizon, the Simple Regression forecasted value of Waste Connections on the next trading day is expected to be 269.14 with a mean absolute deviation of 3.76, mean absolute percentage error of 22.20, and the sum of the absolute errors of 233.40.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 Connections' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Waste Connections Stock Forecast Pattern
| Backtest Waste Connections | Waste Connections Price Prediction | Buy or Sell Advice |
Waste Connections Forecasted Value
In the context of forecasting Waste Connections' 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 Connections' downside and upside margins for the forecasting period are 268.18 and 270.10, respectively. We have considered Waste Connections' 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 Connections stock data series using in forecasting. Note that when a statistical model is used to represent Waste Connections 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 | 123.0483 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 3.7646 |
| MAPE | Mean absolute percentage error | 0.0149 |
| SAE | Sum of the absolute errors | 233.4045 |
Predictive Modules for Waste Connections
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 Connections. 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 Connections
For every potential investor in Waste, whether a beginner or expert, Waste Connections' 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 Connections' price trends.Waste Connections 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 Connections stock to make a market-neutral strategy. Peer analysis of Waste Connections could also be used in its relative valuation, which is a method of valuing Waste Connections by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Waste Connections 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 Connections' 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 Connections' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Waste Connections Market Strength Events
Market strength indicators help investors to evaluate how Waste Connections 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 Connections shares will generate the highest return on investment. By undertsting and applying Waste Connections stock market strength indicators, traders can identify Waste Connections entry and exit signals to maximize returns.
| Accumulation Distribution | 5293.99 | |||
| Daily Balance Of Power | (0.24) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 264.02 | |||
| Day Typical Price | 263.76 | |||
| Price Action Indicator | (1.22) | |||
| Period Momentum Indicator | (0.88) |
Waste Connections Risk Indicators
The analysis of Waste Connections' 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 Connections' 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 | 0.7365 | |||
| Semi Deviation | 0.8865 | |||
| Standard Deviation | 0.9361 | |||
| Variance | 0.8762 | |||
| Downside Variance | 0.9582 | |||
| Semi Variance | 0.7858 | |||
| Expected Short fall | (0.77) |
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 Connections
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 Connections 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 Connections will appreciate offsetting losses from the drop in the long position's value.Moving against Waste Stock
| 0.91 | CMC | Cielo Waste Solutions Earnings Call This Week | PairCorr |
| 0.52 | AEMC | Alaska Energy Metals | PairCorr |
| 0.34 | PNTI-P | Pentagon I Capital | PairCorr |
The ability to find closely correlated positions to Waste Connections 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 Connections 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 Connections - 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 Connections to buy it.
The correlation of Waste Connections 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 Connections moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Waste Connections 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 Connections 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.Check out Historical Fundamental Analysis of Waste Connections to cross-verify your projections. To learn how to invest in Waste Stock, please use our How to Invest in Waste Connections guide.You can also try the Price Ceiling Movement module to calculate and plot Price Ceiling Movement for different equity instruments.