First Credit Stock Forecast - Polynomial Regression

FCIBL Stock   7.78  0.48  6.58%   
The Polynomial Regression forecasted value of First Credit And on the next trading day is expected to be 7.77 with a mean absolute deviation of 0.27 and the sum of the absolute errors of 16.24. First Stock Forecast is based on your current time horizon.
  
First Credit polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for First Credit And as well as the accuracy indicators are determined from the period prices.

First Credit Polynomial Regression Price Forecast For the 2nd of December

Given 90 days horizon, the Polynomial Regression forecasted value of First Credit And on the next trading day is expected to be 7.77 with a mean absolute deviation of 0.27, mean absolute percentage error of 0.15, and the sum of the absolute errors of 16.24.
Please note that although there have been many attempts to predict First 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 First Credit's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

First Credit Stock Forecast Pattern

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First Credit Forecasted Value

In the context of forecasting First Credit'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. First Credit's downside and upside margins for the forecasting period are 3.06 and 12.47, respectively. We have considered First Credit'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.
Market Value
7.78
7.77
Expected Value
12.47
Upside

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 First Credit stock data series using in forecasting. Note that when a statistical model is used to represent First Credit 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.
AICAkaike Information Criteria116.2088
BiasArithmetic mean of the errors None
MADMean absolute deviation0.2662
MAPEMean absolute percentage error0.0353
SAESum of the absolute errors16.2365
A single variable polynomial regression model attempts to put a curve through the First Credit historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for First Credit

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as First Credit And. 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.
Hype
Prediction
LowEstimatedHigh
3.037.7812.53
Details
Intrinsic
Valuation
LowRealHigh
1.646.3911.14
Details

Other Forecasting Options for First Credit

For every potential investor in First, whether a beginner or expert, First Credit's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. First Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in First. Basic forecasting techniques help filter out the noise by identifying First Credit's price trends.

First Credit 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 First Credit stock to make a market-neutral strategy. Peer analysis of First Credit could also be used in its relative valuation, which is a method of valuing First Credit by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

First Credit And 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 First Credit'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 First Credit's current price.

First Credit Market Strength Events

Market strength indicators help investors to evaluate how First Credit stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading First Credit shares will generate the highest return on investment. By undertsting and applying First Credit stock market strength indicators, traders can identify First Credit And entry and exit signals to maximize returns.

First Credit Risk Indicators

The analysis of First Credit'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 First Credit's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting first 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.
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 First Credit

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 First Credit 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 First Credit will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to First Credit could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace First Credit 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 First Credit - 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 First Credit And to buy it.
The correlation of First Credit 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 First Credit moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if First Credit And 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 First Credit 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.
Pair CorrelationCorrelation Matching

Other Information on Investing in First Stock

First Credit financial ratios help investors to determine whether First Stock 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 First with respect to the benefits of owning First Credit security.