Goldman Sachs Mutual Fund Forecast - Polynomial Regression

Goldman Sachs Additional Predictive Modules

Most predictive techniques to examine Goldman price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Goldman using various technical indicators. When you analyze Goldman charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur. Goldman Sachs polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Goldman Sachs Balanced as well as the accuracy indicators are determined from the period prices.

Goldman Sachs Polynomial Regression Price Forecast For the 24th of January

Given 90 days horizon, the Polynomial Regression forecasted value of Goldman Sachs Balanced on the next trading day is expected to be 12.72 with a mean absolute deviation of 0.06, mean absolute percentage error of 0.01, and the sum of the absolute errors of 3.77.

Goldman Sachs Mutual Fund Forecast Pattern

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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 Goldman Sachs mutual fund data series using in forecasting. Note that when a statistical model is used to represent Goldman Sachs 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. A single variable polynomial regression model attempts to put a curve through the Goldman Sachs 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 + ... + a_m*X^m

Predictive Modules for Goldman Sachs

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Goldman Sachs 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 Low Estimated High 12.24 12.78 13.32 Details

Intrinsic Valuation Low Real High 12.15 12.69 13.23 Details

Bollinger Band Projection (param) Low Middle High 12.30 12.65 13.01 Details

Please note, it is not enough to conduct a financial or market analysis of a single entity such as Goldman Sachs. Your research has to be compared to or analyzed against Goldman Sachs' peers to derive any actionable benefits. When done correctly, Goldman Sachs' competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Goldman Sachs Balanced.

Goldman Sachs After-Hype Price Prediction Density Analysis

Goldman Sachs Estimiated After-Hype Price Volatility

Goldman Sachs Mutual Fund Price Prediction Analysis

Goldman Sachs Hype Timeline

Goldman Sachs Balanced is currently traded for 12.79. The entity has historical hype elasticity of -0.01, and average elasticity to hype of competition of -0.07. Goldman is forecasted to decline in value after the next headline, with the price expected to drop to 12.78. The average volatility of media hype impact on the company price is over 100%. The price reduction on the next news is expected to be -0.08%, whereas the daily expected return is currently at 0.07%. The volatility of related hype on Goldman Sachs is about 55.38%, with the expected price after the next announcement by competition of 12.72. The company has price-to-book (P/B) ratio of 1.65. Some equities with similar Price to Book (P/B) outperform the market in the long run. Goldman Sachs Balanced last dividend was issued on the 30th of March 2020. Assuming the 90 days horizon the next forecasted press release will be in about 6 days. Check out Historical Fundamental Analysis of Goldman Sachs to cross-verify your projections.

Goldman Sachs Related Hype Analysis

Other Forecasting Options for Goldman Sachs

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

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