Financial Institutions Stock Forecast - Simple Moving Average
| FISI Stock | USD 32.02 1.15 3.47% |
Financial Stock outlook is based on your current time horizon. We recommend always using this module together with an analysis of Financial Institutions' historical fundamentals, such as revenue growth or operating cash flow patterns.
As of 26th of January 2026, The relative strength index (RSI) of Financial Institutions' share price is at 53. This usually indicates that the stock is in nutural position, most likellhy at or near its resistance level. The main idea of RSI analysis is to track how fast people are buying or selling Financial Institutions, making its price go up or down. Momentum 53
Impartial
Oversold | Overbought |
Quarterly Earnings Growth 0.179 | EPS Estimate Next Quarter 0.94 | EPS Estimate Current Year 3.57 | EPS Estimate Next Year 3.84 | Wall Street Target Price 34.5 |
Using Financial Institutions hype-based prediction, you can estimate the value of Financial Institutions from the perspective of Financial Institutions response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards Financial Institutions using Financial Institutions' stock options and short interest. It helps to benchmark the overall future attitude of investors towards Financial using crowd psychology based on the activity and movement of Financial Institutions' stock price.
Financial Institutions Short Interest
A significant increase or decrease in Financial Institutions' short interest from the previous month could be a good indicator of investor sentiment towards Financial. Short interest can provide insight into the potential direction of Financial Institutions stock and how bullish or bearish investors feel about the market overall.
200 Day MA 27.5025 | Short Percent 0.0199 | Short Ratio 2.97 | Shares Short Prior Month 470.7 K | 50 Day MA 31.169 |
Financial Relative Strength Index
The Simple Moving Average forecasted value of Financial Institutions on the next trading day is expected to be 32.02 with a mean absolute deviation of 0.42 and the sum of the absolute errors of 24.61.Financial Institutions Hype to Price Pattern
Investor biases related to Financial Institutions' public news can be used to forecast risks associated with an investment in Financial. The trend in average sentiment can be used to explain how an investor holding Financial can time the market purely based on public headlines and social activities around Financial Institutions. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Some investors profit by finding stocks that are overvalued or undervalued based on market sentiment. The correlation of Financial Institutions' market sentiment to its price can help taders to make decisions based on the overall investors consensus about Financial Institutions.
Financial Institutions Implied Volatility | 0.85 |
Financial Institutions' implied volatility exposes the market's sentiment of Financial Institutions stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Financial Institutions' implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Financial Institutions stock will not fluctuate a lot when Financial Institutions' options are near their expiration.
The Simple Moving Average forecasted value of Financial Institutions on the next trading day is expected to be 32.02 with a mean absolute deviation of 0.42 and the sum of the absolute errors of 24.61. Financial Institutions after-hype prediction price | USD 32.02 |
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 stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Financial | Build AI portfolio with Financial Stock |
Prediction based on Rule 16 of the current Financial contract
Based on the Rule 16, the options market is currently suggesting that Financial Institutions will have an average daily up or down price movement of about 0.0531% per day over the life of the 2026-03-20 option contract. With Financial Institutions trading at USD 32.02, that is roughly USD 0.017 . If you think that the market is fully incorporating Financial Institutions' daily price movement you should consider acquiring Financial Institutions options at the current volatility level of 0.85%. But if you have an opposite viewpoint you should avoid it and even consider selling them.
Open Interest Against 2026-03-20 Financial Option Contracts
Although open interest is a measure utilized in the options markets, it could be used to forecast Financial Institutions' spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in Financial Institutions' options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for Financial Institutions stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current Financial Institutions' open interest, investors have to compare it to Financial Institutions' spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of Financial Institutions is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in Financial. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.
Financial Institutions Additional Predictive Modules
Most predictive techniques to examine Financial price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Financial using various technical indicators. When you analyze Financial 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 |
Financial Institutions Simple Moving Average Price Forecast For the 27th of January
Given 90 days horizon, the Simple Moving Average forecasted value of Financial Institutions on the next trading day is expected to be 32.02 with a mean absolute deviation of 0.42, mean absolute percentage error of 0.28, and the sum of the absolute errors of 24.61.Please note that although there have been many attempts to predict Financial 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 Financial Institutions' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Financial Institutions Stock Forecast Pattern
| Backtest Financial Institutions | Financial Institutions Price Prediction | Buy or Sell Advice |
Financial Institutions Forecasted Value
In the context of forecasting Financial Institutions' 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. Financial Institutions' downside and upside margins for the forecasting period are 30.41 and 33.63, respectively. We have considered Financial Institutions' 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 Moving Average forecasting method's relative quality and the estimations of the prediction error of Financial Institutions stock data series using in forecasting. Note that when a statistical model is used to represent Financial Institutions 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 | 113.1702 |
| Bias | Arithmetic mean of the errors | -0.0812 |
| MAD | Mean absolute deviation | 0.4171 |
| MAPE | Mean absolute percentage error | 0.0135 |
| SAE | Sum of the absolute errors | 24.61 |
Predictive Modules for Financial Institutions
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Financial Institutions. 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 Financial Institutions' 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.
Financial Institutions After-Hype Price Density Analysis
As far as predicting the price of Financial Institutions 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 Financial Institutions 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 Stock prices, such as prices of Financial Institutions, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Financial Institutions Estimiated After-Hype Price Volatility
In the context of predicting Financial Institutions' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Financial Institutions' historical news coverage. Financial Institutions' after-hype downside and upside margins for the prediction period are 30.43 and 33.61, respectively. We have considered Financial Institutions' 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
Financial Institutions is very steady at this time. Analysis and calculation of next after-hype price of Financial Institutions is based on 3 months time horizon.
Financial Institutions Stock Price Outlook Analysis
Have you ever been surprised when a price of a Company such as Financial Institutions is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Financial Institutions 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 Stock 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 Financial Institutions, 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 |
0.16 | 1.61 | 0.05 | 0.05 | 29 Events / Month | 8 Events / Month | In about 29 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
32.02 | 32.02 | 0.00 |
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Financial Institutions Hype Timeline
Financial Institutions is currently traded for 32.02. The entity has historical hype elasticity of 0.05, and average elasticity to hype of competition of 0.05. Financial 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 over 100%. The immediate return on the next news is projected to be very small, whereas the daily expected return is currently at 0.16%. %. The volatility of related hype on Financial Institutions is about 506.29%, with the expected price after the next announcement by competition of 32.07. About 83.0% of the company shares are owned by institutional investors. The company has price-to-book (P/B) ratio of 1.07. Some equities with similar Price to Book (P/B) outperform the market in the long run. Financial Institutions has Price/Earnings To Growth (PEG) ratio of 1.91. The entity recorded a loss per share of 2.67. The firm last dividend was issued on the 15th of December 2025. Given the investment horizon of 90 days the next projected press release will be in about 29 days. Check out Historical Fundamental Analysis of Financial Institutions to cross-verify your projections.Financial Institutions Related Hype Analysis
Having access to credible news sources related to Financial Institutions' direct competition is more important than ever and may enhance your ability to predict Financial Institutions' future price movements. Getting to know how Financial Institutions' 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 Financial Institutions may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| MOFG | MidWestOne Financial Group | (0.23) | 8 per month | 1.10 | 0.14 | 3.39 | (2.70) | 43.86 | |
| SHBI | Shore Bancshares | (0.02) | 7 per month | 1.10 | 0.10 | 3.11 | (1.67) | 6.54 | |
| ALRS | Alerus Financial Corp | 0.79 | 8 per month | 1.22 | 0.05 | 2.92 | (2.24) | 6.31 | |
| BCAL | Southern California Bancorp | 1.77 | 15 per month | 1.08 | 0.07 | 2.27 | (1.97) | 7.59 | |
| TCBX | Third Coast Bancshares | 0.66 | 10 per month | 1.59 | (0.02) | 3.27 | (2.60) | 7.03 | |
| MSBI | Midland States Bancorp | (0.33) | 11 per month | 1.85 | 0.18 | 6.49 | (1.83) | 14.42 | |
| FMNB | Farmers National Banc | 0.22 | 9 per month | 0.00 | (0.05) | 2.82 | (2.64) | 5.78 | |
| FFIC | Flushing Financial | (0.09) | 26 per month | 1.91 | 0.09 | 4.23 | (2.27) | 13.32 | |
| FFWM | First Foundation | 0.1 | 8 per month | 2.08 | 0.04 | 3.08 | (3.12) | 10.78 | |
| SMBK | SmartFinancial | 0.31 | 8 per month | 1.58 | 0.06 | 2.98 | (2.27) | 7.77 |
Other Forecasting Options for Financial Institutions
For every potential investor in Financial, whether a beginner or expert, Financial Institutions' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Financial Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Financial. Basic forecasting techniques help filter out the noise by identifying Financial Institutions' price trends.Financial Institutions 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 Financial Institutions stock to make a market-neutral strategy. Peer analysis of Financial Institutions could also be used in its relative valuation, which is a method of valuing Financial Institutions by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Financial Institutions Market Strength Events
Market strength indicators help investors to evaluate how Financial Institutions stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Financial Institutions shares will generate the highest return on investment. By undertsting and applying Financial Institutions stock market strength indicators, traders can identify Financial Institutions entry and exit signals to maximize returns.
Financial Institutions Risk Indicators
The analysis of Financial Institutions' 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 Financial Institutions' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting financial 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 | 1.31 | |||
| Semi Deviation | 0.8896 | |||
| Standard Deviation | 1.92 | |||
| Variance | 3.7 | |||
| Downside Variance | 1.34 | |||
| Semi Variance | 0.7913 | |||
| Expected Short fall | (1.77) |
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 Financial Institutions
The number of cover stories for Financial Institutions depends on current market conditions and Financial Institutions' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Financial Institutions 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 Financial Institutions' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
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Financial Institutions Short Properties
Financial Institutions' future price predictability will typically decrease when Financial Institutions' long traders begin to feel the short-sellers pressure to drive the price lower. The predictive aspect of Financial Institutions often depends not only on the future outlook of the potential Financial Institutions' 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. Financial Institutions' indicators that are reflective of the short sentiment are summarized in the table below.
| Common Stock Shares Outstanding | 15.7 M | |
| Cash And Short Term Investments | 87.3 M |
Check out Historical Fundamental Analysis of Financial Institutions to cross-verify your projections. For more detail on how to invest in Financial Stock please use our How to Invest in Financial Institutions guide.You can also try the Efficient Frontier module to plot and analyze your portfolio and positions against risk-return landscape of the market..
Is Regional Banks space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Financial Institutions. If investors know Financial will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Financial Institutions listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 0.179 | Dividend Share 1.23 | Earnings Share (2.67) | Revenue Per Share | Quarterly Revenue Growth 0.3 |
The market value of Financial Institutions is measured differently than its book value, which is the value of Financial that is recorded on the company's balance sheet. Investors also form their own opinion of Financial Institutions' value that differs from its market value or its book value, called intrinsic value, which is Financial Institutions' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Financial Institutions' market value can be influenced by many factors that don't directly affect Financial Institutions' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Financial Institutions' value and its price as these two are different measures arrived at by different means. Investors typically determine if Financial Institutions is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Financial Institutions' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.