Agilysys Stock Forecast - Polynomial Regression

AGYS Stock  USD 137.80  0.32  0.23%   
The Polynomial Regression forecasted value of Agilysys on the next trading day is expected to be 137.68 with a mean absolute deviation of 4.55 and the sum of the absolute errors of 281.84. Agilysys Stock Forecast is based on your current time horizon.
  
Inventory Turnover is likely to drop to 14.28 in 2024. Payables Turnover is likely to drop to 8.39 in 2024. Net Income Applicable To Common Shares is likely to gain to about 12 M in 2024, whereas Common Stock Shares Outstanding is likely to drop slightly above 20.8 M in 2024.
Agilysys polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Agilysys as well as the accuracy indicators are determined from the period prices.

Agilysys Polynomial Regression Price Forecast For the 27th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Agilysys on the next trading day is expected to be 137.68 with a mean absolute deviation of 4.55, mean absolute percentage error of 37.45, and the sum of the absolute errors of 281.84.
Please note that although there have been many attempts to predict Agilysys 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 Agilysys' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Agilysys Stock Forecast Pattern

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Agilysys Forecasted Value

In the context of forecasting Agilysys' 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. Agilysys' downside and upside margins for the forecasting period are 134.79 and 140.57, respectively. We have considered Agilysys' 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.
Market Value
137.80
134.79
Downside
137.68
Expected Value
140.57
Upside

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 Agilysys stock data series using in forecasting. Note that when a statistical model is used to represent Agilysys 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.
AICAkaike Information Criteria123.5714
BiasArithmetic mean of the errors None
MADMean absolute deviation4.5457
MAPEMean absolute percentage error0.0409
SAESum of the absolute errors281.836
A single variable polynomial regression model attempts to put a curve through the Agilysys historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Agilysys

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Agilysys. 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 Agilysys' 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.
Hype
Prediction
LowEstimatedHigh
135.67138.55141.43
Details
Intrinsic
Valuation
LowRealHigh
105.25108.13151.58
Details
Bollinger
Band Projection (param)
LowMiddleHigh
113.70125.91138.11
Details
5 Analysts
Consensus
LowTargetHigh
81.3589.4099.23
Details

Other Forecasting Options for Agilysys

For every potential investor in Agilysys, whether a beginner or expert, Agilysys' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Agilysys Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Agilysys. Basic forecasting techniques help filter out the noise by identifying Agilysys' price trends.

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 Risk & Return  Correlation

Agilysys 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 Agilysys' 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 Agilysys' current price.

Agilysys Market Strength Events

Market strength indicators help investors to evaluate how Agilysys stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Agilysys shares will generate the highest return on investment. By undertsting and applying Agilysys stock market strength indicators, traders can identify Agilysys entry and exit signals to maximize returns.

Agilysys Risk Indicators

The analysis of Agilysys' 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 Agilysys' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting agilysys 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.
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.

Thematic Opportunities

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Additional Tools for Agilysys Stock Analysis

When running Agilysys' price analysis, check to measure Agilysys' 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 Agilysys is operating at the current time. Most of Agilysys' value examination focuses on studying past and present price action to predict the probability of Agilysys' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Agilysys' price. Additionally, you may evaluate how the addition of Agilysys to your portfolios can decrease your overall portfolio volatility.