Goldman Sachs (Brazil) Probability of Future Stock Price Finishing Over 97.86

GSGI34 Stock  BRL 120.62  1.30  1.07%   
Goldman Sachs' future price is the expected price of Goldman Sachs instrument. It is based on its current growth rate as well as the projected cash flow expected by the investors. This tool provides a mechanism to make assumptions about the upside potential and downside risk of The Goldman Sachs performance during a given time horizon utilizing its historical volatility. Check out Goldman Sachs Backtesting, Goldman Sachs Valuation, Goldman Sachs Correlation, Goldman Sachs Hype Analysis, Goldman Sachs Volatility, Goldman Sachs History as well as Goldman Sachs Performance.
  
Please specify Goldman Sachs' target price for which you would like Goldman Sachs odds to be computed.

Goldman Sachs Target Price Odds to finish over 97.86

The tendency of Goldman Stock price to converge on an average value over time is a known aspect in finance that investors have used since the beginning of the stock market for forecasting. However, many studies suggest that some traded equity instruments are consistently mispriced before traders' demand and supply correct the spread. One possible conclusion to this anomaly is that these stocks have additional risk, for which investors demand compensation in the form of extra returns.
Current PriceHorizonTarget PriceOdds to stay above R$ 97.86  in 90 days
 120.62 90 days 97.86 
about 57.03
Based on a normal probability distribution, the odds of Goldman Sachs to stay above R$ 97.86  in 90 days from now is about 57.03 (This The Goldman Sachs probability density function shows the probability of Goldman Stock to fall within a particular range of prices over 90 days) . Probability of Goldman Sachs price to stay between R$ 97.86  and its current price of R$120.62 at the end of the 90-day period is about 54.17 .
Assuming the 90 days trading horizon Goldman Sachs has a beta of 0.34. This usually indicates as returns on the market go up, Goldman Sachs average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding The Goldman Sachs will be expected to be much smaller as well. Additionally The Goldman Sachs has an alpha of 0.368, implying that it can generate a 0.37 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta).
   Goldman Sachs Price Density   
       Price  

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. Regardless of method or technology, however, to accurately forecast the stock 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.
Hype
Prediction
LowEstimatedHigh
119.53121.92124.31
Details
Intrinsic
Valuation
LowRealHigh
109.73133.99136.38
Details
Naive
Forecast
LowNextHigh
119.38121.76124.15
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
113.90117.44120.98
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.

Goldman Sachs Risk Indicators

For the most part, the last 10-20 years have been a very volatile time for the stock market. Goldman Sachs is not an exception. The market had few large corrections towards the Goldman Sachs' value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold The Goldman Sachs, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Goldman Sachs within the framework of very fundamental risk indicators.
α
Alpha over Dow Jones
0.37
β
Beta against Dow Jones0.34
σ
Overall volatility
10.95
Ir
Information ratio 0.12

Goldman Sachs Price Density Drivers

Market volatility will typically increase when nervous long traders begin to feel the short-sellers pressure to drive the market lower. The future price of Goldman Stock often depends not only on the future outlook of the current and potential Goldman Sachs' investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. Goldman Sachs' indicators that are reflective of the short sentiment are summarized in the table below.
Common Stock Shares Outstanding334.9 M

Goldman Sachs Technical Analysis

Goldman Sachs' future price can be derived by breaking down and analyzing its technical indicators over time. Goldman Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of The Goldman Sachs. In general, you should focus on analyzing Goldman Stock price patterns and their correlations with different microeconomic environments and drivers.

Goldman Sachs Predictive Forecast Models

Goldman Sachs' time-series forecasting models is one of many Goldman Sachs' stock analysis techniques aimed to predict future share value based on previously observed values. Time-series forecasting models are widely used for non-stationary data. Non-stationary data are called the data whose statistical properties, e.g., the mean and standard deviation, are not constant over time, but instead, these metrics vary over time. This non-stationary Goldman Sachs' historical data is usually called time series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the stock market movement and maximize returns from investment trading.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Goldman Sachs in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Goldman Sachs' short interest history, or implied volatility extrapolated from Goldman Sachs options trading.

Other Information on Investing in Goldman Stock

Goldman Sachs financial ratios help investors to determine whether Goldman Stock 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 Goldman with respect to the benefits of owning Goldman Sachs security.