FS Credit Stock Forecast - Polynomial Regression
| FSCO Stock | 6.50 0.01 0.15% |
The Polynomial Regression forecasted value of FS Credit Opportunities on the next trading day is expected to be 6.40 with a mean absolute deviation of 0.06 and the sum of the absolute errors of 3.55. FSCO Stock Forecast is based on your current time horizon. Although FS Credit's naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of FS Credit's systematic risk associated with finding meaningful patterns of FS Credit fundamentals over time.
FSCO |
FS Credit Polynomial Regression Price Forecast For the 26th of November
Given 90 days horizon, the Polynomial Regression forecasted value of FS Credit Opportunities on the next trading day is expected to be 6.40 with a mean absolute deviation of 0.06, mean absolute percentage error of 0, and the sum of the absolute errors of 3.55.Please note that although there have been many attempts to predict FSCO 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 FS Credit's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
FS Credit Stock Forecast Pattern
| Backtest FS Credit | FS Credit Price Prediction | Buy or Sell Advice |
FS Credit Forecasted Value
In the context of forecasting FS 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. FS Credit's downside and upside margins for the forecasting period are 5.50 and 7.30, respectively. We have considered FS 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.
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 FS Credit stock data series using in forecasting. Note that when a statistical model is used to represent FS 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.| AIC | Akaike Information Criteria | 112.7759 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0581 |
| MAPE | Mean absolute percentage error | 0.0091 |
| SAE | Sum of the absolute errors | 3.547 |
Predictive Modules for FS 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 FS Credit Opportunities. 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 FS Credit's 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 FS Credit
For every potential investor in FSCO, whether a beginner or expert, FS Credit's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. FSCO Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in FSCO. Basic forecasting techniques help filter out the noise by identifying FS Credit's price trends.View FS Credit Related Equities
| Risk & Return | Correlation |
FS Credit Opportunities 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 FS 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 FS Credit's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
FS Credit Market Strength Events
Market strength indicators help investors to evaluate how FS 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 FS Credit shares will generate the highest return on investment. By undertsting and applying FS Credit stock market strength indicators, traders can identify FS Credit Opportunities entry and exit signals to maximize returns.
FS Credit Risk Indicators
The analysis of FS 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 FS Credit's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting fsco 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 | 0.6674 | |||
| Semi Deviation | 0.6385 | |||
| Standard Deviation | 0.9323 | |||
| Variance | 0.8692 | |||
| Downside Variance | 0.6208 | |||
| Semi Variance | 0.4077 | |||
| Expected Short fall | (0.88) |
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 FS 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 FS 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 FS Credit will appreciate offsetting losses from the drop in the long position's value.Moving together with FSCO Stock
| 0.63 | DIST | Distoken Acquisition | PairCorr |
| 0.79 | AB | AllianceBernstein | PairCorr |
| 0.87 | AC | Associated Capital | PairCorr |
Moving against FSCO Stock
The ability to find closely correlated positions to FS 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 FS 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 FS 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 FS Credit Opportunities to buy it.
The correlation of FS 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 FS Credit moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if FS Credit Opportunities 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 FS 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.Check out Historical Fundamental Analysis of FS Credit to cross-verify your projections. You can also try the Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
Is Asset Management & Custody 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 FS Credit. If investors know FSCO 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 FS Credit listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share 1.16 |
The market value of FS Credit Opportunities is measured differently than its book value, which is the value of FSCO that is recorded on the company's balance sheet. Investors also form their own opinion of FS Credit's value that differs from its market value or its book value, called intrinsic value, which is FS Credit's 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 FS Credit's market value can be influenced by many factors that don't directly affect FS Credit's 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 FS Credit's value and its price as these two are different measures arrived at by different means. Investors typically determine if FS Credit is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, FS Credit's 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.