Financial Institutions Pink Sheet Forecast - Naive Prediction
| FIISO Stock | USD 140.00 0.00 0.00% |
The Naive Prediction forecasted value of Financial Institutions 848 on the next trading day is expected to be 147.80 with a mean absolute deviation of 3.81 and the sum of the absolute errors of 232.31. Financial Pink Sheet Forecast is based on your current time horizon.
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Financial Institutions Naive Prediction Price Forecast For the 13th of December 2024
Given 90 days horizon, the Naive Prediction forecasted value of Financial Institutions 848 on the next trading day is expected to be 147.80 with a mean absolute deviation of 3.81, mean absolute percentage error of 28.41, and the sum of the absolute errors of 232.31.Please note that although there have been many attempts to predict Financial 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 Financial Institutions' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Financial Institutions Pink Sheet Forecast Pattern
| Backtest Financial Institutions | Financial Institutions Price Prediction | Buy or Sell Advice |
Financial Institutions Forecasted Value
In the context of forecasting Financial Institutions' 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. Financial Institutions' downside and upside margins for the forecasting period are 144.10 and 151.51, 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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Financial Institutions pink sheet data series using in forecasting. Note that when a statistical model is used to represent Financial Institutions 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 | 121.4574 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 3.8084 |
| MAPE | Mean absolute percentage error | 0.0306 |
| SAE | Sum of the absolute errors | 232.3143 |
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 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.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 Pink Sheet 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 pink sheet 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 Technical and Predictive Analytics
The pink sheet 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 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 Financial Institutions shares will generate the highest return on investment. By undertsting and applying Financial Institutions pink sheet market strength indicators, traders can identify Financial Institutions 848 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 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 | 0.9291 | |||
| Standard Deviation | 3.65 | |||
| Variance | 13.32 |
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 Financial Institutions
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 Financial Institutions 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 Financial Institutions will appreciate offsetting losses from the drop in the long position's value.Moving together with Financial Pink Sheet
Moving against Financial Pink Sheet
| 0.84 | DPSTF | Deutsche Post AG | PairCorr |
| 0.82 | VLKAF | Volkswagen AG | PairCorr |
| 0.82 | VWAGY | Volkswagen AG 110 | PairCorr |
| 0.81 | ELCPF | EDP Energias | PairCorr |
| 0.8 | VWAPY | Volkswagen AG Pref | PairCorr |
The ability to find closely correlated positions to Financial Institutions could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Financial Institutions 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 Financial Institutions - 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 Financial Institutions 848 to buy it.
The correlation of Financial Institutions 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 Financial Institutions moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Financial Institutions 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 Financial Institutions 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.Other Information on Investing in Financial Pink Sheet
Financial Institutions financial ratios help investors to determine whether Financial Pink Sheet is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Financial with respect to the benefits of owning Financial Institutions security.