Patrangsit Healthcare Stock Forecast - Naive Prediction

PHG Stock   15.50  0.10  0.65%   
The Naive Prediction forecasted value of Patrangsit Healthcare Group on the next trading day is expected to be 15.35 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 10.32. Investors can use prediction functions to forecast Patrangsit Healthcare's stock prices and determine the direction of Patrangsit Healthcare Group's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading. We recommend always using this module together with an analysis of Patrangsit Healthcare's historical fundamentals, such as revenue growth or operating cash flow patterns. Check out Your Equity Center to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
  
A naive forecasting model for Patrangsit Healthcare is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Patrangsit Healthcare Group value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Patrangsit Healthcare Naive Prediction Price Forecast For the 5th of December

Given 90 days horizon, the Naive Prediction forecasted value of Patrangsit Healthcare Group on the next trading day is expected to be 15.35 with a mean absolute deviation of 0.17, mean absolute percentage error of 0.04, and the sum of the absolute errors of 10.32.
Please note that although there have been many attempts to predict Patrangsit 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 Patrangsit Healthcare's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Patrangsit Healthcare Stock Forecast Pattern

Patrangsit Healthcare Forecasted Value

In the context of forecasting Patrangsit Healthcare'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. Patrangsit Healthcare's downside and upside margins for the forecasting period are 13.80 and 16.90, respectively. We have considered Patrangsit Healthcare'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.
Market Value
15.50
15.35
Expected Value
16.90
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Patrangsit Healthcare stock data series using in forecasting. Note that when a statistical model is used to represent Patrangsit Healthcare 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 Criteria114.9916
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1692
MAPEMean absolute percentage error0.0104
SAESum of the absolute errors10.3187
This model is not at all useful as a medium-long range forecasting tool of Patrangsit Healthcare Group. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Patrangsit Healthcare. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Patrangsit Healthcare

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Patrangsit Healthcare. 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 Patrangsit Healthcare

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

Patrangsit Healthcare 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 Patrangsit Healthcare stock to make a market-neutral strategy. Peer analysis of Patrangsit Healthcare could also be used in its relative valuation, which is a method of valuing Patrangsit Healthcare by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Patrangsit Healthcare 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 Patrangsit Healthcare'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 Patrangsit Healthcare's current price.

Patrangsit Healthcare Market Strength Events

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

Patrangsit Healthcare Risk Indicators

The analysis of Patrangsit Healthcare'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 Patrangsit Healthcare's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting patrangsit 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.

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