George Putnam Mutual Fund Forecast - Simple Regression

PGEJX Fund  USD 25.67  0.05  0.19%   
The Simple Regression forecasted value of George Putnam Balanced on the next trading day is expected to be 26.33 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 10.37. George Mutual Fund Forecast is based on your current time horizon.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through George Putnam price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

George Putnam Simple Regression Price Forecast For the 20th of December

Given 90 days horizon, the Simple Regression forecasted value of George Putnam Balanced on the next trading day is expected to be 26.33 with a mean absolute deviation of 0.17, mean absolute percentage error of 0.05, and the sum of the absolute errors of 10.37.
Please note that although there have been many attempts to predict George Mutual Fund 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 George Putnam's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

George Putnam Mutual Fund Forecast Pattern

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George Putnam Forecasted Value

In the context of forecasting George Putnam's Mutual Fund 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. George Putnam's downside and upside margins for the forecasting period are 25.83 and 26.83, respectively. We have considered George Putnam'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
25.67
26.33
Expected Value
26.83
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of George Putnam mutual fund data series using in forecasting. Note that when a statistical model is used to represent George Putnam mutual fund, 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 Criteria115.1134
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1699
MAPEMean absolute percentage error0.0066
SAESum of the absolute errors10.3656
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as George Putnam Balanced historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for George Putnam

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as George Putnam Balanced. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund 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.
Hype
Prediction
LowEstimatedHigh
25.2225.7226.22
Details
Intrinsic
Valuation
LowRealHigh
25.2825.7826.28
Details

Other Forecasting Options for George Putnam

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

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

George Putnam Balanced Technical and Predictive Analytics

The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of George Putnam'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 George Putnam's current price.

George Putnam Market Strength Events

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

George Putnam Risk Indicators

The analysis of George Putnam'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 George Putnam's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting george mutual fund 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Other Information on Investing in George Mutual Fund

George Putnam financial ratios help investors to determine whether George Mutual Fund 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 George with respect to the benefits of owning George Putnam security.
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