Salesforce Stock Forecast - Polynomial Regression
| FOO Stock | EUR 255.10 4.40 1.70% |
The Polynomial Regression forecasted value of Salesforce on the next trading day is expected to be 254.42 with a mean absolute deviation of 3.75 and the sum of the absolute errors of 228.93. Salesforce Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Salesforce stock prices and determine the direction of Salesforce's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Salesforce's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Salesforce to cross-verify your projections. For more detail on how to invest in Salesforce Stock please use our How to Invest in Salesforce guide.Salesforce |
Most investors in Salesforce 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 Salesforce's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Salesforce's price structures and extracts relationships that further increase the generated results' accuracy.
Salesforce polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Salesforce as well as the accuracy indicators are determined from the period prices. Salesforce Polynomial Regression Price Forecast For the 20th of April
Given 90 days horizon, the Polynomial Regression forecasted value of Salesforce on the next trading day is expected to be 254.42 with a mean absolute deviation of 3.75, mean absolute percentage error of 23.81, and the sum of the absolute errors of 228.93.Please note that although there have been many attempts to predict Salesforce Stock 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 Salesforce's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Salesforce Stock Forecast Pattern
| Backtest Salesforce | Salesforce Price Prediction | Buy or Sell Advice |
Salesforce Forecasted Value
In the context of forecasting Salesforce's Stock 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. Salesforce's downside and upside margins for the forecasting period are 252.62 and 256.21, respectively. We have considered Salesforce's 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.
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 Salesforce stock data series using in forecasting. Note that when a statistical model is used to represent Salesforce stock, 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.| AIC | Akaike Information Criteria | 121.2804 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 3.753 |
| MAPE | Mean absolute percentage error | 0.0138 |
| SAE | Sum of the absolute errors | 228.9347 |
Predictive Modules for Salesforce
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Salesforce. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Salesforce's 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.
Other Forecasting Options for Salesforce
For every potential investor in Salesforce, whether a beginner or expert, Salesforce's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Salesforce Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Salesforce. Basic forecasting techniques help filter out the noise by identifying Salesforce's price trends.Salesforce 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 Salesforce stock to make a market-neutral strategy. Peer analysis of Salesforce could also be used in its relative valuation, which is a method of valuing Salesforce by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Salesforce 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 Salesforce's 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 Salesforce's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Salesforce Market Strength Events
Market strength indicators help investors to evaluate how Salesforce stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Salesforce shares will generate the highest return on investment. By undertsting and applying Salesforce stock market strength indicators, traders can identify Salesforce entry and exit signals to maximize returns.
Salesforce Risk Indicators
The analysis of Salesforce's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Salesforce's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting salesforce stock prices, 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.
| Mean Deviation | 1.24 | |||
| Semi Deviation | 1.93 | |||
| Standard Deviation | 1.81 | |||
| Variance | 3.26 | |||
| Downside Variance | 4.19 | |||
| Semi Variance | 3.74 | |||
| Expected Short fall | (1.30) |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
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Try AI Portfolio ArchitectCheck out Historical Fundamental Analysis of Salesforce to cross-verify your projections. For more detail on how to invest in Salesforce Stock please use our How to Invest in Salesforce guide.You can also try the Premium Stories module to follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope.
Complementary Tools for Salesforce Stock analysis
When running Salesforce's price analysis, check to measure Salesforce's 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 Salesforce is operating at the current time. Most of Salesforce's value examination focuses on studying past and present price action to predict the probability of Salesforce's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Salesforce's price. Additionally, you may evaluate how the addition of Salesforce to your portfolios can decrease your overall portfolio volatility.
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