P A Stock Forecast - Naive Prediction

PTSI -  USA Stock  

USD 68.85  0.93  1.37%

P A Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast P A historical stock prices and determine the direction of P A M's future trends based on various well-known forecasting models. However, solely looking at the historical price movement is usually misleading. Macroaxis recommends to always use this module together with analysis of P A historical fundamentals such as revenue growth or operating cash flow patterns. Although P A naive historical forecasting may sometimes provide an important future outlook for the firm we recommend to always cross-verify it against solid analysis of P A M systematic risk associated with finding meaningful patterns of P A fundamentals over time.
Please check Historical Fundamental Analysis of P A to cross-verify your projections.

P A Stock Forecast 

 
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P A Accounts Payable Turnover is most likely to increase slightly in the upcoming years. The last year's value of Accounts Payable Turnover was reported at 13.94. The current Accrued Expenses Turnover is estimated to increase to 31.22, while Inventory Turnover is projected to decrease to 155.02. . P A Weighted Average Shares is most likely to decrease significantly in the upcoming years. The last year's value of Weighted Average Shares was reported at 13.23 Million. The current Weighted Average Shares Diluted is estimated to increase to about 15.1 M, while Issuance Purchase of Equity Shares is projected to decrease to (56.7 M).
Most investors in P A 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 P A's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets P A's price structures and extracts relationships that further increase the generated results' accuracy.
A naive forecasting model for P A is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of P A M 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.

P A Naive Prediction Price Forecast For the 27th of January

Given 90 days horizon, the Naive Prediction forecasted value of P A M on the next trading day is expected to be 65.94 with a mean absolute deviation of 2.82, mean absolute percentage error of 11.05, and the sum of the absolute errors of 172.32. Please note that although there have been many attempts to predict P A 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 P A's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

P A Stock Forecast Pattern

Backtest P AP A Price PredictionBuy or Sell Advice 

P A Forecasted Value

In the context of forecasting P A'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. P A's downside and upside margins for the forecasting period are 61.99 and 69.89, respectively. We have considered P A'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 68.85
65.94
Expected Value
69.89
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 P A stock data series using in forecasting. Note that when a statistical model is used to represent P A 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 Criteria120.5128
BiasArithmetic mean of the errors None
MADMean absolute deviation2.8249
MAPEMean absolute percentage error0.0412
SAESum of the absolute errors172.3214
This model is not at all useful as a medium-long range forecasting tool of P A M. 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 P A. 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 P A

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as P A M. Regardless of method or technology, however, to accurately forecast the stock or bond 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, frequently view the market will even out over time. This tendency of P A'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. Please use the tools below to analyze the current value of P A in the context of predictive analytics.
Hype
Prediction
LowEstimated ValueHigh
62.9567.8072.65
Details
Intrinsic
Valuation
LowReal ValueHigh
65.8870.7375.58
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
10.0044.3778.74
Details
1 Analysts
Consensus
LowTarget PriceHigh
85.0085.0085.00
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as P A. Your research has to be compared to or analyzed against P A's peers to derive any actionable benefits. When done correctly, P A's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy towards taking a position in P A M.

Other Forecasting Options for P A

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

View Currently 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 P A stock to make a market-neutral strategy. Peer analysis of P A could also be used in its relative valuation, which is a method of valuing P A by comparing valuation metrics with similar companies.

P A M 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 P A'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 P A's current price.

P A Market Strength Events

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

P A Risk Indicators

The analysis of P A's basic risk indicators is one of the essential steps in helping accuretelly forecast its future price. The process involves identifying the amount of risk involved in P A's investment and either accepting that risk or mitigating it. Along with some funamental techniques of forecasting P A stock price, 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 stock investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Be your own money manager

Our tools can tell you how much better you can do entering a position in P A without increasing your portfolio risk or giving up expected return. As an individual investor, you need to find a reliable way to track all your investment portfolios. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing all investors analytical transparency into all their portfolios, our tools can evaluate.risk-adjusted returns of your individual positions relative to your overall portfolio.

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Please check Historical Fundamental Analysis of P A to cross-verify your projections. Note that the P A M information on this page should be used as a complementary analysis to other P A's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try Balance Of Power module to check stock momentum by analyzing Balance Of Power indicator and other technical ratios.

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When running P A M price analysis, check to measure P A'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 P A is operating at the current time. Most of P A's value examination focuses on studying past and present price action to predict the probability of P A's future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move P A's price. Additionally, you may evaluate how the addition of P A to your portfolios can decrease your overall portfolio volatility.
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Is P A'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 P A. If investors know P A 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 P A 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 P A M is measured differently than its book value, which is the value of P A that is recorded on the company's balance sheet. Investors also form their own opinion of P A's value that differs from its market value or its book value, called intrinsic value, which is P A'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 P A's market value can be influenced by many factors that don't directly affect P A'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 P A's value and its price as these two are different measures arrived at by different means. Investors typically determine P A value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, P A'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.