Bank of America Pink Sheet Forecast - Simple Regression
| BACRP Preferred Stock | USD 200.00 0.00 0.00% |
The Simple Regression forecasted value of Bank of America on the next trading day is expected to be 194.93 with a mean absolute deviation of 7.65 and the sum of the absolute errors of 466.93. Bank Pink Sheet Forecast is based on your current time horizon.
As of today the relative strength index (rsi) of Bank of America's share price is below 20 suggesting that the pink sheet is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Using Bank of America hype-based prediction, you can estimate the value of Bank of America from the perspective of Bank of America response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Regression forecasted value of Bank of America on the next trading day is expected to be 194.93 with a mean absolute deviation of 7.65 and the sum of the absolute errors of 466.93. Bank of America after-hype prediction price | USD 200.0 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as pink sheet price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Bank |
Bank of America Additional Predictive Modules
Most predictive techniques to examine Bank price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Bank using various technical indicators. When you analyze Bank charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Bank of America Simple Regression Price Forecast For the 25th of January
Given 90 days horizon, the Simple Regression forecasted value of Bank of America on the next trading day is expected to be 194.93 with a mean absolute deviation of 7.65, mean absolute percentage error of 112.85, and the sum of the absolute errors of 466.93.Please note that although there have been many attempts to predict Bank Pink Sheet 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 Bank of America's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Bank of America Pink Sheet Forecast Pattern
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Bank of America Forecasted Value
In the context of forecasting Bank of America's Pink Sheet 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. Bank of America's downside and upside margins for the forecasting period are 191.70 and 198.15, respectively. We have considered Bank of America'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 Bank of America pink sheet data series using in forecasting. Note that when a statistical model is used to represent Bank of America pink sheet, 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 | 122.8366 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 7.6546 |
| MAPE | Mean absolute percentage error | 0.0359 |
| SAE | Sum of the absolute errors | 466.9284 |
Predictive Modules for Bank of America
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Bank of America. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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.Bank of America After-Hype Price Prediction Density Analysis
As far as predicting the price of Bank of America at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Bank of America or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Pink Sheet prices, such as prices of Bank of America, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Bank of America Estimiated After-Hype Price Volatility
In the context of predicting Bank of America's pink sheet value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Bank of America's historical news coverage. Bank of America's after-hype downside and upside margins for the prediction period are 196.75 and 203.25, respectively. We have considered Bank of America's daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Bank of America is very steady at this time. Analysis and calculation of next after-hype price of Bank of America is based on 3 months time horizon.
Bank of America Pink Sheet Price Prediction Analysis
Have you ever been surprised when a price of a Company such as Bank of America is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Bank of America backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Pink Sheet price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Bank of America, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.07 | 3.22 | 0.12 | 0.02 | 14 Events / Month | 3 Events / Month | In about 14 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
200.00 | 200.00 | 0.00 |
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Bank of America Hype Timeline
Bank of America is currently traded for 200.00. The entity has historical hype elasticity of -0.12, and average elasticity to hype of competition of -0.02. Bank is projected not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is about 186.13%. The immediate return on the next news is projected to be very small, whereas the daily expected return is currently at -0.07%. %. The volatility of related hype on Bank of America is about 936.05%, with the expected price after the next announcement by competition of 199.98. The company last dividend was issued on the 25th of April 2023. Assuming the 90 days horizon the next projected press release will be in about 14 days. Check out Historical Fundamental Analysis of Bank of America to cross-verify your projections. To learn how to invest in Bank Pink Sheet, please use our How to Invest in Bank of America guide.Bank of America Related Hype Analysis
Having access to credible news sources related to Bank of America's direct competition is more important than ever and may enhance your ability to predict Bank of America's future price movements. Getting to know how Bank of America's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Bank of America may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| IDCBF | Industrial and Commercial | 0.00 | 0 per month | 1.47 | (0.03) | 3.95 | (3.75) | 13.68 | |
| IDCBY | Industrial and Commercial | (1.73) | 11 per month | 0.99 | 0.02 | 1.97 | (1.74) | 6.23 | |
| CICHY | China Construction Bank | 0.00 | 0 per month | 1.14 | (0.06) | 1.52 | (1.62) | 7.50 | |
| ACGBY | Agricultural Bank of | 0.38 | 18 per month | 0.00 | (0.09) | 1.94 | (2.74) | 6.48 | |
| ACGBF | Agricultural Bank | (1.73) | 2 per month | 0.00 | (0.04) | 3.90 | (2.82) | 21.53 | |
| HBCYF | HSBC Holdings PLC | (0.12) | 4 per month | 1.68 | 0.14 | 4.61 | (2.78) | 10.08 | |
| BACHY | Bank of China | (0.12) | 4 per month | 0.99 | (0) | 1.54 | (1.17) | 5.91 | |
| CICHF | China Construction Bank | 0.00 | 0 per month | 2.90 | 0.02 | 5.26 | (5.88) | 19.50 | |
| BACHF | Bank of China | 0.00 | 0 per month | 3.38 | 0.06 | 7.27 | (6.90) | 20.39 | |
| CMWAY | Commonwealth Bank of | (0.12) | 4 per month | 0.00 | (0.13) | 2.44 | (2.75) | 9.30 |
Other Forecasting Options for Bank of America
For every potential investor in Bank, whether a beginner or expert, Bank of America's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Bank Pink Sheet price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Bank. Basic forecasting techniques help filter out the noise by identifying Bank of America's price trends.Bank of America 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 Bank of America pink sheet to make a market-neutral strategy. Peer analysis of Bank of America could also be used in its relative valuation, which is a method of valuing Bank of America by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Bank of America Market Strength Events
Market strength indicators help investors to evaluate how Bank of America pink sheet reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Bank of America shares will generate the highest return on investment. By undertsting and applying Bank of America pink sheet market strength indicators, traders can identify Bank of America entry and exit signals to maximize returns.
Bank of America Risk Indicators
The analysis of Bank of America'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 Bank of America's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting bank pink sheet 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 | 0.9181 | |||
| Standard Deviation | 3.15 | |||
| Variance | 9.92 |
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.
Story Coverage note for Bank of America
The number of cover stories for Bank of America depends on current market conditions and Bank of America's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Bank of America is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Bank of America's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios
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Bank of America Short Properties
Bank of America's future price predictability will typically decrease when Bank of America's long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Bank of America often depends not only on the future outlook of the potential Bank of America's 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. Bank of America's indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 8 B | |
| Short Term Investments | 220.8 B |
Additional Tools for Bank Pink Sheet Analysis
When running Bank of America's price analysis, check to measure Bank of America'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 Bank of America is operating at the current time. Most of Bank of America's value examination focuses on studying past and present price action to predict the probability of Bank of America's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Bank of America's price. Additionally, you may evaluate how the addition of Bank of America to your portfolios can decrease your overall portfolio volatility.