Financial Institutions Stock Technical Analysis
| FISI Stock | USD 33.67 0.15 0.44% |
As of the 19th of February, Financial Institutions shows the Downside Deviation of 1.23, mean deviation of 1.17, and Coefficient Of Variation of 641.83. Financial Institutions technical analysis allows you to utilize historical prices and volume patterns in order to determine a pattern that computes the direction of the firm's future prices.
Financial Institutions Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Financial, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to FinancialFinancial | Build AI portfolio with Financial Stock |
Is there potential for Regional Banks market expansion? Will Financial introduce new products? Factors like these will boost the valuation of Financial Institutions. Market participants price Financial higher when confident in its future expansion prospects. Understanding fair value requires weighing current performance against future potential. 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.
Investors evaluate Financial Institutions using market value (trading price) and book value (balance sheet equity), each telling a different story. Calculating Financial Institutions' intrinsic value - the estimated true worth - helps identify when the stock trades at a discount or premium to fair value. Analysts utilize numerous techniques to assess fundamental value, seeking to purchase shares when trading prices fall beneath estimated intrinsic worth. External factors like market trends, sector rotation, and investor psychology can cause Financial Institutions' market price to deviate significantly 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. Conversely, Financial Institutions' market price signifies the transaction level at which participants voluntarily complete trades.
Financial Institutions 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Financial Institutions' stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Financial Institutions.
| 11/21/2025 |
| 02/19/2026 |
If you would invest 0.00 in Financial Institutions on November 21, 2025 and sell it all today you would earn a total of 0.00 from holding Financial Institutions or generate 0.0% return on investment in Financial Institutions over 90 days. Financial Institutions is related to or competes with MidWestOne Financial, Shore Bancshares, Alerus Financial, Southern California, Third Coast, Midland States, and Farmers National. Financial Institutions, Inc. operates as a holding company for the Five Star Bank, a chartered bank that provides bankin... More
Financial Institutions Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Financial Institutions' stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Financial Institutions upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.23 | |||
| Information Ratio | 0.1163 | |||
| Maximum Drawdown | 8.79 | |||
| Value At Risk | (1.90) | |||
| Potential Upside | 3.07 |
Financial Institutions Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Financial Institutions' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Financial Institutions' standard deviation. In reality, there are many statistical measures that can use Financial Institutions historical prices to predict the future Financial Institutions' volatility.| Risk Adjusted Performance | 0.1246 | |||
| Jensen Alpha | 0.1919 | |||
| Total Risk Alpha | 0.128 | |||
| Sortino Ratio | 0.1514 | |||
| Treynor Ratio | 0.2658 |
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 February 19, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.1246 | |||
| Market Risk Adjusted Performance | 0.2758 | |||
| Mean Deviation | 1.17 | |||
| Semi Deviation | 0.9855 | |||
| Downside Deviation | 1.23 | |||
| Coefficient Of Variation | 641.83 | |||
| Standard Deviation | 1.61 | |||
| Variance | 2.58 | |||
| Information Ratio | 0.1163 | |||
| Jensen Alpha | 0.1919 | |||
| Total Risk Alpha | 0.128 | |||
| Sortino Ratio | 0.1514 | |||
| Treynor Ratio | 0.2658 | |||
| Maximum Drawdown | 8.79 | |||
| Value At Risk | (1.90) | |||
| Potential Upside | 3.07 | |||
| Downside Variance | 1.52 | |||
| Semi Variance | 0.9713 | |||
| Expected Short fall | (1.42) | |||
| Skewness | 0.7207 | |||
| Kurtosis | 1.31 |
Financial Institutions Backtested Returns
Financial Institutions appears to be very steady, given 3 months investment horizon. Financial Institutions secures Sharpe Ratio (or Efficiency) of 0.16, which denotes the company had a 0.16 % return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Financial Institutions, which you can use to evaluate the volatility of the firm. Please utilize Financial Institutions' Downside Deviation of 1.23, coefficient of variation of 641.83, and Mean Deviation of 1.17 to check if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Financial Institutions holds a performance score of 12. The firm shows a Beta (market volatility) of 0.9, which means possible diversification benefits within a given portfolio. Financial Institutions returns are very sensitive to returns on the market. As the market goes up or down, Financial Institutions is expected to follow. Please check Financial Institutions' semi variance, and the relationship between the treynor ratio and daily balance of power , to make a quick decision on whether Financial Institutions' price patterns will revert.
Auto-correlation | 0.49 |
Average predictability
Financial Institutions has average predictability. Overlapping area represents the amount of predictability between Financial Institutions time series from 21st of November 2025 to 5th of January 2026 and 5th of January 2026 to 19th of February 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Financial Institutions price movement. The serial correlation of 0.49 indicates that about 49.0% of current Financial Institutions price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.49 | |
| Spearman Rank Test | 0.51 | |
| Residual Average | 0.0 | |
| Price Variance | 1.7 |
Financial Institutions technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.
Financial Institutions Technical Analysis
The output start index for this execution was ten with a total number of output elements of fifty-one. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Financial Institutions volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Financial Institutions Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Financial Institutions on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Financial Institutions based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Financial Institutions price pattern first instead of the macroeconomic environment surrounding Financial Institutions. By analyzing Financial Institutions's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Financial Institutions's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Financial Institutions specific price patterns or momentum indicators. Please read more on our technical analysis page.
Financial Institutions February 19, 2026 Technical Indicators
Most technical analysis of Financial help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Financial from various momentum indicators to cycle indicators. When you analyze Financial charts, please remember that the event formation may indicate an entry point for a short seller, and look at different 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 |
| Risk Adjusted Performance | 0.1246 | |||
| Market Risk Adjusted Performance | 0.2758 | |||
| Mean Deviation | 1.17 | |||
| Semi Deviation | 0.9855 | |||
| Downside Deviation | 1.23 | |||
| Coefficient Of Variation | 641.83 | |||
| Standard Deviation | 1.61 | |||
| Variance | 2.58 | |||
| Information Ratio | 0.1163 | |||
| Jensen Alpha | 0.1919 | |||
| Total Risk Alpha | 0.128 | |||
| Sortino Ratio | 0.1514 | |||
| Treynor Ratio | 0.2658 | |||
| Maximum Drawdown | 8.79 | |||
| Value At Risk | (1.90) | |||
| Potential Upside | 3.07 | |||
| Downside Variance | 1.52 | |||
| Semi Variance | 0.9713 | |||
| Expected Short fall | (1.42) | |||
| Skewness | 0.7207 | |||
| Kurtosis | 1.31 |
Financial Institutions February 19, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Financial stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 5,521 | ||
| Daily Balance Of Power | (0.17) | ||
| Rate Of Daily Change | 1.00 | ||
| Day Median Price | 33.54 | ||
| Day Typical Price | 33.58 | ||
| Price Action Indicator | 0.06 |
Complementary Tools for Financial Stock analysis
When running Financial Institutions' price analysis, check to measure Financial Institutions' 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 Financial Institutions is operating at the current time. Most of Financial Institutions' value examination focuses on studying past and present price action to predict the probability of Financial Institutions' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Financial Institutions' price. Additionally, you may evaluate how the addition of Financial Institutions to your portfolios can decrease your overall portfolio volatility.
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