Bank of America Stock Forecast - Double Exponential Smoothing
| BOFA Stock | 24.88 0.12 0.48% |
The Double Exponential Smoothing forecasted value of Bank of America on the next trading day is expected to be 24.98 with a mean absolute deviation of 0.27 and the sum of the absolute errors of 15.69. Bank Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Bank of America stock prices and determine the direction of Bank of America's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Bank of America's historical fundamentals, such as revenue growth or operating cash flow patterns.
Bank |
Bank of America Double Exponential Smoothing Price Forecast For the 3rd of December
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Bank of America on the next trading day is expected to be 24.98 with a mean absolute deviation of 0.27, mean absolute percentage error of 0.15, and the sum of the absolute errors of 15.69.Please note that although there have been many attempts to predict Bank 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 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 Stock Forecast Pattern
| Backtest Bank of America | Bank of America Price Prediction | Buy or Sell Advice |
Bank of America Forecasted Value
In the context of forecasting Bank of America'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. Bank of America's downside and upside margins for the forecasting period are 23.33 and 26.62, 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 Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Bank of America stock data series using in forecasting. Note that when a statistical model is used to represent Bank of America 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 | Huge |
| Bias | Arithmetic mean of the errors | 0.0547 |
| MAD | Mean absolute deviation | 0.2659 |
| MAPE | Mean absolute percentage error | 0.0121 |
| SAE | Sum of the absolute errors | 15.6877 |
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 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.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 Stock 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 stock 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 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 Bank of America'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 Bank of America's current price.| Cycle Indicators | ||
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| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Bank of America Market Strength Events
Market strength indicators help investors to evaluate how Bank of America stock 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 stock 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 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 | 1.08 | |||
| Semi Deviation | 0.662 | |||
| Standard Deviation | 1.63 | |||
| Variance | 2.66 | |||
| Downside Variance | 0.9144 | |||
| Semi Variance | 0.4382 | |||
| Expected Short fall | (1.37) |
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.
Pair Trading with Bank of America
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Bank of America position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Bank of America will appreciate offsetting losses from the drop in the long position's value.Moving against Bank Stock
| 0.92 | HPQ | HPQ Silicon Resources | PairCorr |
| 0.6 | IZ | International Zeolite | PairCorr |
| 0.52 | NG | NovaGold Resources | PairCorr |
The ability to find closely correlated positions to Bank of America could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Bank of America when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Bank of America - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Bank of America to buy it.
The correlation of Bank of America is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Bank of America moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Bank of America moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Bank of America can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Historical Fundamental Analysis of Bank of America to cross-verify your projections. For information on how to trade Bank Stock refer to our How to Trade Bank Stock guide.You can also try the Cryptocurrency Center module to build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency.