Great Lakes Mutual Fund Forecast - Polynomial Regression

GLDNXDelisted Fund  USD 9.21  0.00  0.00%   
The Polynomial Regression forecasted value of Great Lakes Disciplined on the next trading day is expected to be 9.21 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. Great Mutual Fund Forecast is based on your current time horizon.
  
Great Lakes polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Great Lakes Disciplined as well as the accuracy indicators are determined from the period prices.

Great Lakes Polynomial Regression Price Forecast For the 10th of January

Given 90 days horizon, the Polynomial Regression forecasted value of Great Lakes Disciplined on the next trading day is expected to be 9.21 with a mean absolute deviation of 0, mean absolute percentage error of 0, and the sum of the absolute errors of 0.
Please note that although there have been many attempts to predict Great 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 Great Lakes' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Great Lakes Mutual Fund Forecast Pattern

Backtest Great LakesGreat Lakes Price PredictionBuy or Sell Advice 

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 Great Lakes mutual fund data series using in forecasting. Note that when a statistical model is used to represent Great Lakes 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 Criteria-12.0955
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0
MAPEMean absolute percentage error0.0
SAESum of the absolute errors0.0
A single variable polynomial regression model attempts to put a curve through the Great Lakes 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 Great Lakes

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Great Lakes Disciplined. 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
9.219.219.21
Details
Intrinsic
Valuation
LowRealHigh
8.528.5210.13
Details

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

Great Lakes Market Strength Events

Market strength indicators help investors to evaluate how Great Lakes 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 Great Lakes shares will generate the highest return on investment. By undertsting and applying Great Lakes mutual fund market strength indicators, traders can identify Great Lakes Disciplined entry and exit signals to maximize returns.

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.
Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any mutual fund could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
You can also try the Portfolio Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.

Other Consideration for investing in Great Mutual Fund

If you are still planning to invest in Great Lakes Disciplined check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Great Lakes' history and understand the potential risks before investing.
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