Financial Institutions Stock Forecast - Polynomial Regression
| FISI Stock | USD 26.97 0.35 1.31% |
The Polynomial Regression forecasted value of Financial Institutions on the next trading day is expected to be 26.29 with a mean absolute deviation of 0.66 and the sum of the absolute errors of 40.40. Financial Stock Forecast 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.
Financial |
Open Interest Against 2025-03-21 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 Polynomial Regression Price Forecast For the 19th of January
Given 90 days horizon, the Polynomial Regression forecasted value of Financial Institutions on the next trading day is expected to be 26.29 with a mean absolute deviation of 0.66, mean absolute percentage error of 0.66, and the sum of the absolute errors of 40.40.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 23.71 and 28.87, 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 Polynomial Regression 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 | 117.6925 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.6623 |
| MAPE | Mean absolute percentage error | 0.0252 |
| SAE | Sum of the absolute errors | 40.4002 |
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.
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.View Financial Institutions Related Equities
| Risk & Return | Correlation |
Financial Institutions 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 Financial Institutions' 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 Financial Institutions' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
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 | 1.67 | |||
| Semi Deviation | 1.86 | |||
| Standard Deviation | 2.59 | |||
| Variance | 6.71 | |||
| Downside Variance | 4.16 | |||
| Semi Variance | 3.47 | |||
| Expected Short fall | (1.91) |
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
| BTC | Bitcoin | |
| TRX | TRON | |
| BNB | Binance Coin | |
| ADA | Cardano | |
| XRP | XRP |
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 Stock Screener module to find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook..
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 (0.04) | Dividend Share 1.2 | Earnings Share 3.21 | Revenue Per Share | Quarterly Revenue Growth (0.08) |
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.