Goldman Sachs Mutual Fund Forecast - Polynomial Regression

GIMSX -  USA Fund  

USD 5.45  0.04  0.73%

Goldman Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Goldman Sachs historical stock prices and determine the direction of Goldman Sachs Local'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 Goldman Sachs historical fundamentals such as revenue growth or operating cash flow patterns.
Please check Historical Fundamental Analysis of Goldman Sachs to cross-verify your projections.

Goldman Mutual Fund Forecast 

 
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Most investors in Goldman Sachs 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 Goldman Sachs' time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Goldman Sachs' price structures and extracts relationships that further increase the generated results' accuracy.
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 Local as well as the accuracy indicators are determined from the period prices.

Goldman Sachs Polynomial Regression Price Forecast For the 25th of October

Given 90 days horizon, the Polynomial Regression forecasted value of Goldman Sachs Local on the next trading day is expected to be 5.42 with a mean absolute deviation of 0.03999, mean absolute percentage error of 0.002162, and the sum of the absolute errors of 2.44. Please note that although there have been many attempts to predict Goldman 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 Goldman Sachs' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Goldman Sachs Mutual Fund Forecast Pattern

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Goldman Sachs Forecasted Value

In the context of forecasting Goldman Sachs' 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. Goldman Sachs' downside and upside margins for the forecasting period are 5.03 and 5.81, respectively. We have considered Goldman Sachs' 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
5.45
24th of October 2021
5.42
Expected Value
5.81
Upside

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.
AICAkaike Information Criteria111.9739
BiasArithmetic mean of the errors None
MADMean absolute deviation0.04
MAPEMean absolute percentage error0.0072
SAESum of the absolute errors2.4394
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 + ... + am*Xm

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 Local. 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 Goldman Sachs' 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 Goldman Sachs in the context of predictive analytics.
Hype
Prediction
LowEstimated ValueHigh
5.065.455.84
Details
Intrinsic
Valuation
LowReal ValueHigh
5.095.485.87
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 towards taking a position in Goldman Sachs Local.

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.

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

Goldman Sachs Local 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 Goldman Sachs' 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 Goldman Sachs' current price.

Goldman Sachs Risk Indicators

The analysis of Goldman Sachs' 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 Goldman Sachs' investment and either accepting that risk or mitigating it. Along with some funamental techniques of forecasting Goldman Sachs 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.

Goldman Sachs Investors Sentiment

The influence of Goldman Sachs' investor sentiment on the probability of its price appreciation or decline could be a good factor in your decision-making process regarding taking a position in Goldman. The overall investor sentiment generally increases the direction of a stock movement in a one-year investment horizon. However, the impact of investor sentiment on the entire stock markets does not have a solid backing from leading economists and market statisticians.

Current Sentiment - GIMSX

Goldman Sachs Local Investor Sentiment

Macroaxis portfolio users are indifferent in their judgment towards investing in Goldman Sachs Local. What is your judgment towards investing in Goldman Sachs Local? Are you bullish or bearish?
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Please check Historical Fundamental Analysis of Goldman Sachs to cross-verify your projections. Note that the Goldman Sachs Local information on this page should be used as a complementary analysis to other Goldman Sachs' 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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.

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When running Goldman Sachs Local price analysis, check to measure Goldman Sachs' 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 Goldman Sachs is operating at the current time. Most of Goldman Sachs' value examination focuses on studying past and present price action to predict the probability of Goldman Sachs' future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move Goldman Sachs' price. Additionally, you may evaluate how the addition of Goldman Sachs to your portfolios can decrease your overall portfolio volatility.
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Please note, there is a significant difference between Goldman Sachs' value and its price as these two are different measures arrived at by different means. Investors typically determine Goldman Sachs value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Goldman Sachs' 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.