Patterson Companies Stock Forecast - Double Exponential Smoothing
| PD2 Stock | EUR 29.40 0.40 1.34% |
The Double Exponential Smoothing forecasted value of Patterson Companies on the next trading day is expected to be 29.73 with a mean absolute deviation of 0.46 and the sum of the absolute errors of 27.40. Patterson Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Patterson Companies' historical fundamentals, such as revenue growth or operating cash flow patterns.
Patterson |
Patterson Companies Double Exponential Smoothing Price Forecast For the 24th of December
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Patterson Companies on the next trading day is expected to be 29.73 with a mean absolute deviation of 0.46, mean absolute percentage error of 1.15, and the sum of the absolute errors of 27.40.Please note that although there have been many attempts to predict Patterson 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 Patterson Companies' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Patterson Companies Stock Forecast Pattern
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Patterson Companies Forecasted Value
In the context of forecasting Patterson Companies' 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. Patterson Companies' downside and upside margins for the forecasting period are 25.03 and 34.43, respectively. We have considered Patterson Companies' 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 Patterson Companies stock data series using in forecasting. Note that when a statistical model is used to represent Patterson Companies 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 | -0.1747 |
| MAD | Mean absolute deviation | 0.4644 |
| MAPE | Mean absolute percentage error | 0.0208 |
| SAE | Sum of the absolute errors | 27.3971 |
Predictive Modules for Patterson Companies
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Patterson Companies. 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 Patterson Companies
For every potential investor in Patterson, whether a beginner or expert, Patterson Companies' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Patterson Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Patterson. Basic forecasting techniques help filter out the noise by identifying Patterson Companies' price trends.Patterson Companies 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 Patterson Companies stock to make a market-neutral strategy. Peer analysis of Patterson Companies could also be used in its relative valuation, which is a method of valuing Patterson Companies by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Patterson Companies 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 Patterson Companies' 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 Patterson Companies' current price.| Cycle Indicators | ||
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| Math Transform | ||
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| Overlap Studies | ||
| Pattern Recognition | ||
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| Volume Indicators |
Patterson Companies Market Strength Events
Market strength indicators help investors to evaluate how Patterson Companies stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Patterson Companies shares will generate the highest return on investment. By undertsting and applying Patterson Companies stock market strength indicators, traders can identify Patterson Companies entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 29.4 | |||
| Day Typical Price | 29.4 | |||
| Price Action Indicator | (0.20) | |||
| Period Momentum Indicator | (0.40) |
Patterson Companies Risk Indicators
The analysis of Patterson Companies' 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 Patterson Companies' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting patterson 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 | 1.98 | |||
| Semi Deviation | 1.37 | |||
| Standard Deviation | 4.67 | |||
| Variance | 21.8 | |||
| Downside Variance | 4.99 | |||
| Semi Variance | 1.87 | |||
| Expected Short fall | (2.73) |
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.
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Additional Information and Resources on Investing in Patterson Stock
When determining whether Patterson Companies offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Patterson Companies' financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Patterson Companies Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Patterson Companies Stock:Check out Historical Fundamental Analysis of Patterson Companies to cross-verify your projections. For more detail on how to invest in Patterson Stock please use our How to Invest in Patterson Companies guide.You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.