Regions Financial Preferred Stock Forecast - Simple Regression
| RF-PB Preferred Stock | USD 24.92 0.07 0.28% |
The Simple Regression forecasted value of Regions Financial on the next trading day is expected to be 25.09 with a mean absolute deviation of 0.17 and the sum of the absolute errors of 10.34. Regions Preferred Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Regions Financial stock prices and determine the direction of Regions Financial's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Regions Financial's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Regions Financial to cross-verify your projections. Regions |
Most investors in Regions Financial cannot accurately predict what will happen the next trading day because, historically, preferred 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 Regions Financial's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Regions Financial's price structures and extracts relationships that further increase the generated results' accuracy.
Simple Regression model is a single variable regression model that attempts to put a straight line through Regions Financial 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. Regions Financial Simple Regression Price Forecast For the 10th of May
Given 90 days horizon, the Simple Regression forecasted value of Regions Financial on the next trading day is expected to be 25.09 with a mean absolute deviation of 0.17, mean absolute percentage error of 0.04, and the sum of the absolute errors of 10.34.Please note that although there have been many attempts to predict Regions Preferred 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 Regions Financial's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Regions Financial Preferred Stock Forecast Pattern
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Regions Financial Forecasted Value
In the context of forecasting Regions Financial's Preferred 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. Regions Financial's downside and upside margins for the forecasting period are 24.57 and 25.61, respectively. We have considered Regions Financial'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 Simple Regression forecasting method's relative quality and the estimations of the prediction error of Regions Financial preferred stock data series using in forecasting. Note that when a statistical model is used to represent Regions Financial preferred 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 | 116.8005 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1668 |
| MAPE | Mean absolute percentage error | 0.0068 |
| SAE | Sum of the absolute errors | 10.3432 |
Predictive Modules for Regions Financial
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Regions Financial. Regardless of method or technology, however, to accurately forecast the preferred stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the preferred 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 Regions Financial'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 Regions Financial
For every potential investor in Regions, whether a beginner or expert, Regions Financial's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Regions Preferred Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Regions. Basic forecasting techniques help filter out the noise by identifying Regions Financial's price trends.Regions Financial 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 Regions Financial preferred stock to make a market-neutral strategy. Peer analysis of Regions Financial could also be used in its relative valuation, which is a method of valuing Regions Financial by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Regions Financial Technical and Predictive Analytics
The preferred stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Regions Financial'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 Regions Financial's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Regions Financial Market Strength Events
Market strength indicators help investors to evaluate how Regions Financial preferred stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Regions Financial shares will generate the highest return on investment. By undertsting and applying Regions Financial preferred stock market strength indicators, traders can identify Regions Financial entry and exit signals to maximize returns.
| Accumulation Distribution | 200.17 | |||
| Daily Balance Of Power | (0.47) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 24.93 | |||
| Day Typical Price | 24.92 | |||
| Price Action Indicator | (0.04) | |||
| Period Momentum Indicator | (0.07) |
Regions Financial Risk Indicators
The analysis of Regions Financial'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 Regions Financial's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting regions preferred 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 | 0.4086 | |||
| Semi Deviation | 0.3474 | |||
| Standard Deviation | 0.5507 | |||
| Variance | 0.3033 | |||
| Downside Variance | 0.26 | |||
| Semi Variance | 0.1207 | |||
| Expected Short fall | (0.47) |
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.
Currently Active Assets on Macroaxis
Check out Historical Fundamental Analysis of Regions Financial to cross-verify your projections. For information on how to trade Regions Preferred Stock refer to our How to Trade Regions Preferred Stock guide.You can also try the Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
Complementary Tools for Regions Preferred Stock analysis
When running Regions Financial's price analysis, check to measure Regions Financial'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 Regions Financial is operating at the current time. Most of Regions Financial's value examination focuses on studying past and present price action to predict the probability of Regions Financial's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Regions Financial's price. Additionally, you may evaluate how the addition of Regions Financial to your portfolios can decrease your overall portfolio volatility.
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