MaxLinear Stock Forecast - Polynomial Regression
| MXL Stock | USD 19.99 0.72 3.74% |
The Polynomial Regression forecasted value of MaxLinear on the next trading day is expected to be 19.56 with a mean absolute deviation of 1.01 and the sum of the absolute errors of 61.82. MaxLinear Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast MaxLinear stock prices and determine the direction of MaxLinear's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of MaxLinear's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of MaxLinear to cross-verify your projections. MaxLinear |
Most investors in MaxLinear cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the MaxLinear's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets MaxLinear's price structures and extracts relationships that further increase the generated results' accuracy.
MaxLinear polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for MaxLinear as well as the accuracy indicators are determined from the period prices. MaxLinear Polynomial Regression Price Forecast For the 8th of May
Given 90 days horizon, the Polynomial Regression forecasted value of MaxLinear on the next trading day is expected to be 19.56 with a mean absolute deviation of 1.01, mean absolute percentage error of 1.53, and the sum of the absolute errors of 61.82.Please note that although there have been many attempts to predict MaxLinear 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 MaxLinear's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
MaxLinear Stock Forecast Pattern
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MaxLinear Forecasted Value
In the context of forecasting MaxLinear'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. MaxLinear's downside and upside margins for the forecasting period are 16.35 and 22.77, respectively. We have considered MaxLinear'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 Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of MaxLinear stock data series using in forecasting. Note that when a statistical model is used to represent MaxLinear 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 | 118.5355 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 1.0134 |
| MAPE | Mean absolute percentage error | 0.0511 |
| SAE | Sum of the absolute errors | 61.8201 |
Predictive Modules for MaxLinear
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as MaxLinear. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of MaxLinear's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Other Forecasting Options for MaxLinear
For every potential investor in MaxLinear, whether a beginner or expert, MaxLinear's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. MaxLinear Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in MaxLinear. Basic forecasting techniques help filter out the noise by identifying MaxLinear's price trends.MaxLinear 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 MaxLinear stock to make a market-neutral strategy. Peer analysis of MaxLinear could also be used in its relative valuation, which is a method of valuing MaxLinear by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
MaxLinear 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 MaxLinear'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 MaxLinear's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
MaxLinear Market Strength Events
Market strength indicators help investors to evaluate how MaxLinear stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading MaxLinear shares will generate the highest return on investment. By undertsting and applying MaxLinear stock market strength indicators, traders can identify MaxLinear entry and exit signals to maximize returns.
MaxLinear Risk Indicators
The analysis of MaxLinear'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 MaxLinear's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting maxlinear 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 | 2.48 | |||
| Semi Deviation | 3.15 | |||
| Standard Deviation | 3.21 | |||
| Variance | 10.29 | |||
| Downside Variance | 10.92 | |||
| Semi Variance | 9.89 | |||
| Expected Short fall | (2.66) |
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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Try AI Portfolio ArchitectCheck out Historical Fundamental Analysis of MaxLinear to cross-verify your projections. For more information on how to buy MaxLinear Stock please use our How to buy in MaxLinear Stock guide.You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
Complementary Tools for MaxLinear Stock analysis
When running MaxLinear's price analysis, check to measure MaxLinear'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 MaxLinear is operating at the current time. Most of MaxLinear's value examination focuses on studying past and present price action to predict the probability of MaxLinear's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move MaxLinear's price. Additionally, you may evaluate how the addition of MaxLinear to your portfolios can decrease your overall portfolio volatility.
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Is MaxLinear's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of MaxLinear. If investors know MaxLinear will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about MaxLinear listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
The market value of MaxLinear is measured differently than its book value, which is the value of MaxLinear that is recorded on the company's balance sheet. Investors also form their own opinion of MaxLinear's value that differs from its market value or its book value, called intrinsic value, which is MaxLinear's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because MaxLinear's market value can be influenced by many factors that don't directly affect MaxLinear's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between MaxLinear's value and its price as these two are different measures arrived at by different means. Investors typically determine if MaxLinear is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, MaxLinear's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.