Jason Furniture Stock Forecast - Polynomial Regression
603816 Stock | 28.89 0.56 1.98% |
The Polynomial Regression forecasted value of Jason Furniture on the next trading day is expected to be 29.92 with a mean absolute deviation of 1.09 and the sum of the absolute errors of 67.51. Jason Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Jason Furniture stock prices and determine the direction of Jason Furniture's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Jason Furniture's historical fundamentals, such as revenue growth or operating cash flow patterns.
Jason |
Jason Furniture Polynomial Regression Price Forecast For the 19th of December
Given 90 days horizon, the Polynomial Regression forecasted value of Jason Furniture on the next trading day is expected to be 29.92 with a mean absolute deviation of 1.09, mean absolute percentage error of 1.89, and the sum of the absolute errors of 67.51.Please note that although there have been many attempts to predict Jason 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 Jason Furniture's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Jason Furniture Stock Forecast Pattern
Backtest Jason Furniture | Jason Furniture Price Prediction | Buy or Sell Advice |
Jason Furniture Forecasted Value
In the context of forecasting Jason Furniture'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. Jason Furniture's downside and upside margins for the forecasting period are 26.26 and 33.59, respectively. We have considered Jason Furniture'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 Jason Furniture stock data series using in forecasting. Note that when a statistical model is used to represent Jason Furniture 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 | 120.5824 |
Bias | Arithmetic mean of the errors | None |
MAD | Mean absolute deviation | 1.0889 |
MAPE | Mean absolute percentage error | 0.037 |
SAE | Sum of the absolute errors | 67.5125 |
Predictive Modules for Jason Furniture
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Jason Furniture. 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 Jason Furniture
For every potential investor in Jason, whether a beginner or expert, Jason Furniture's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Jason Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Jason. Basic forecasting techniques help filter out the noise by identifying Jason Furniture's price trends.Jason Furniture 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 Jason Furniture stock to make a market-neutral strategy. Peer analysis of Jason Furniture could also be used in its relative valuation, which is a method of valuing Jason Furniture by comparing valuation metrics with similar companies.
Risk & Return | Correlation |
Jason Furniture 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 Jason Furniture'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 Jason Furniture's current price.Cycle Indicators | ||
Math Operators | ||
Math Transform | ||
Momentum Indicators | ||
Overlap Studies | ||
Pattern Recognition | ||
Price Transform | ||
Statistic Functions | ||
Volatility Indicators | ||
Volume Indicators |
Jason Furniture Market Strength Events
Market strength indicators help investors to evaluate how Jason Furniture stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Jason Furniture shares will generate the highest return on investment. By undertsting and applying Jason Furniture stock market strength indicators, traders can identify Jason Furniture entry and exit signals to maximize returns.
Accumulation Distribution | 249324.0 | |||
Daily Balance Of Power | 0.4786 | |||
Rate Of Daily Change | 1.02 | |||
Day Median Price | 28.77 | |||
Day Typical Price | 28.81 | |||
Price Action Indicator | 0.41 | |||
Period Momentum Indicator | 0.56 |
Jason Furniture Risk Indicators
The analysis of Jason Furniture'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 Jason Furniture's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting jason 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 | 2.85 | |||
Semi Deviation | 2.85 | |||
Standard Deviation | 3.58 | |||
Variance | 12.79 | |||
Downside Variance | 9.94 | |||
Semi Variance | 8.1 | |||
Expected Short fall | (3.12) |
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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Other Information on Investing in Jason Stock
Jason Furniture financial ratios help investors to determine whether Jason 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 Jason with respect to the benefits of owning Jason Furniture security.