Twitter Stock Forecast - Simple Regression

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TWTR -- USA Stock  

 Earnings Call  In Two Weeks

Twitter Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Twitter historical stock prices and determine the direction of Twitter'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 Twitter historical fundamentals such as revenue growth or operating cash flow patterns. Although Twitter naive historical forecasting may sometimes provide an important future outlook for the firm we recommend to always cross-verify it against solid analysis of Twitter systematic risk associated with finding meaningful patterns of Twitter fundamentals over time. Additionally, take a look at Historical Fundamental Analysis of Twitter to cross-verify your projections.

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Twitter Accounts Payable Turnover is relatively stable at the moment as compared to the past year. Twitter reported last year Accounts Payable Turnover of 22.59. As of 07/03/2020, Accrued Expenses Turnover is likely to grow to 9.60, while Receivables Turnover is likely to drop 3.90. . As of 07/03/2020, Issuance Purchase of Equity Shares is likely to grow to about 29.5 M, while Weighted Average Shares is likely to drop slightly above 612.1 M.
Simple Regression model is a single variable regression model that attempts to put a straight line through Twitter 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.

Twitter Simple Regression Price Forecast For the 4th of July

Given 30 days horizon, the forecasted value of Twitter on the next trading day is expected to be  33.99  with a mean absolute deviation of  1.53 , mean absolute percentage error of  3.76 , and the sum of the absolute errors of  93.55 
 33.99 

Twitter Stock Forecast Pattern

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Twitter Forecasted Value

Market Value
30.89
3rd of July 2020
33.99
Expected Value
37.71
Upside

Model Predictive Factors

AICAkaike Information Criteria119.4348
BiasArithmetic mean of the errors None
MADMean absolute deviation1.5336
MAPEMean absolute percentage error0.0491
SAESum of the absolute errors93.5504
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 Twitter 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 Twitter

There are currently many different techniques concerning forecasting the market as a whole as well as predicting future values of individual securities such as Twitter. 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.
Earnings
Estimates (7)
LowProjected EPSHigh
-0.32-0.10.08
Details
Hype
Prediction
LowEstimated ValueHigh
27.1330.8534.57
Details
Intrinsic
Valuation
LowReal ValueHigh
27.9831.7035.42
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
28.9132.9536.99
Details
24 Analysts
Consensus
LowTarget PriceHigh
24.0032.3847.00
Details

Other Forecasting Options for Twitter

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Twitter Technical and Predictive Analytics

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Additionally, take a look at Historical Fundamental Analysis of Twitter to cross-verify your projections. Please also try Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
Macroaxis is not a registered investment advisor or broker/dealer. All investments, including stocks, funds, ETFs, or cryptocurrencies, are speculative and involve substantial risk of loss. We encourage our investors to invest carefully. Much of our information is derived directly from data published by companies or submitted to governmental agencies which we believe are reliable, but are without our independent verification. Therefore, we cannot assure you that the information is accurate or complete. We do not in any way warrant or guarantee the success of any action you take in reliance on our statements or recommendations. Also, note that past performance is not necessarily indicative of future results. All investments carry risk, and all investment decisions of an individual remain the responsibility of that individual. There is no guarantee that systems, indicators, or signals will result in profits or that they will not result in losses. All investors are advised to fully understand all risks associated with any investing they choose to do. Hypothetical or simulated performance is not indicative of future results. We make no representations or warranties that any investor will, or is likely to, achieve profits similar to those shown because hypothetical or simulated performance is not necessarily indicative of future results. For more information please visit our terms and condition page