Financial Services Mutual Fund Forecast - Simple Regression
| FIDSX Fund | USD 16.09 0.13 0.81% |
The Simple Regression forecasted value of Financial Services Portfolio on the next trading day is expected to be 16.43 with a mean absolute deviation of 0.22 and the sum of the absolute errors of 13.65. Financial Mutual Fund Forecast is based on your current time horizon.
At this time the relative strength index (rsi) of Financial Services' share price is below 20 . This usually indicates that the mutual fund is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards. Momentum 0
Sell Peaked
Oversold | Overbought |
Using Financial Services hype-based prediction, you can estimate the value of Financial Services Portfolio from the perspective of Financial Services response to recently generated media hype and the effects of current headlines on its competitors.
The Simple Regression forecasted value of Financial Services Portfolio on the next trading day is expected to be 16.43 with a mean absolute deviation of 0.22 and the sum of the absolute errors of 13.65. Financial Services after-hype prediction price | USD 16.1 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as fund price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Financial |
Financial Services Additional Predictive Modules
Most predictive techniques to examine Financial price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Financial using various technical indicators. When you analyze Financial charts, please remember that the event formation may indicate an entry point for a short seller, and look at 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 |
Financial Services Simple Regression Price Forecast For the 24th of January
Given 90 days horizon, the Simple Regression forecasted value of Financial Services Portfolio on the next trading day is expected to be 16.43 with a mean absolute deviation of 0.22, mean absolute percentage error of 0.07, and the sum of the absolute errors of 13.65.Please note that although there have been many attempts to predict Financial Mutual Fund 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 Services' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Financial Services Mutual Fund Forecast Pattern
| Backtest Financial Services | Financial Services Price Prediction | Buy or Sell Advice |
Financial Services Forecasted Value
In the context of forecasting Financial Services' Mutual Fund 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 Services' downside and upside margins for the forecasting period are 15.55 and 17.31, respectively. We have considered Financial Services' 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 Simple Regression forecasting method's relative quality and the estimations of the prediction error of Financial Services mutual fund data series using in forecasting. Note that when a statistical model is used to represent Financial Services mutual fund, 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 | 117.3373 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.2202 |
| MAPE | Mean absolute percentage error | 0.0141 |
| SAE | Sum of the absolute errors | 13.6515 |
Predictive Modules for Financial Services
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 Services. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund 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 Services' 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 Services After-Hype Price Prediction Density Analysis
As far as predicting the price of Financial Services at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Financial Services or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Mutual Fund prices, such as prices of Financial Services, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Financial Services Estimiated After-Hype Price Volatility
In the context of predicting Financial Services' mutual fund value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Financial Services' historical news coverage. Financial Services' after-hype downside and upside margins for the prediction period are 15.22 and 16.98, respectively. We have considered Financial Services' daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Financial Services is very steady at this time. Analysis and calculation of next after-hype price of Financial Services is based on 3 months time horizon.
Financial Services Mutual Fund Price Prediction Analysis
Have you ever been surprised when a price of a Mutual Fund such as Financial Services is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Financial Services backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Fund price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Financial Services, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.10 | 0.88 | 0.01 | 0.02 | 1 Events / Month | 3 Events / Month | Very soon |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | ||
16.09 | 16.10 | 0.06 |
|
Financial Services Hype Timeline
Financial Services is currently traded for 16.09. The entity has historical hype elasticity of 0.01, and average elasticity to hype of competition of -0.02. Financial is projected to increase in value after the next headline, with the price projected to jump to 16.1 or above. The average volatility of media hype impact on the company the price is over 100%. The price jump on the next news is projected to be 0.06%, whereas the daily expected return is currently at 0.1%. The volatility of related hype on Financial Services is about 440.0%, with the expected price after the next announcement by competition of 16.07. Assuming the 90 days horizon the next projected press release will be very soon. Check out Historical Fundamental Analysis of Financial Services to cross-verify your projections.Financial Services Related Hype Analysis
Having access to credible news sources related to Financial Services' direct competition is more important than ever and may enhance your ability to predict Financial Services' future price movements. Getting to know how Financial Services' peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Financial Services may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| FDFAX | Consumer Staples Portfolio | (2.92) | 17 per month | 0.63 | (0.04) | 1.25 | (0.98) | 3.00 | |
| FDCPX | Computers Portfolio Puters | 0.00 | 1 per month | 1.41 | 0.02 | 1.91 | (2.56) | 5.50 | |
| FBSOX | It Services Portfolio | 1.67 | 4 per month | 0.00 | (0.14) | 1.64 | (2.22) | 4.77 | |
| GPIQ | Goldman Sachs Nasdaq 100 | 0.11 | 4 per month | 0.91 | (0.05) | 1.37 | (1.67) | 4.24 | |
| FCYIX | Industrials Portfolio Industrials | (0.18) | 1 per month | 0.64 | (0.13) | 1.57 | (1.10) | 4.14 | |
| WINN | Harbor Long Term Growers | 0.13 | 3 per month | 0.00 | (0.13) | 1.64 | (1.93) | 5.05 | |
| DFGX | Dimensional Global ex | (0.06) | 4 per month | 0.00 | (0.62) | 0.23 | (0.32) | 0.74 | |
| STRV | EA Series Trust | (0.35) | 3 per month | 0.77 | (0.06) | 1.14 | (1.31) | 3.68 |
Other Forecasting Options for Financial Services
For every potential investor in Financial, whether a beginner or expert, Financial Services' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Financial Mutual Fund 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 Services' price trends.Financial Services 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 Services mutual fund to make a market-neutral strategy. Peer analysis of Financial Services could also be used in its relative valuation, which is a method of valuing Financial Services by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Financial Services Market Strength Events
Market strength indicators help investors to evaluate how Financial Services mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Financial Services shares will generate the highest return on investment. By undertsting and applying Financial Services mutual fund market strength indicators, traders can identify Financial Services Portfolio entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 16.09 | |||
| Day Typical Price | 16.09 | |||
| Price Action Indicator | 0.065 | |||
| Period Momentum Indicator | 0.13 |
Financial Services Risk Indicators
The analysis of Financial Services' 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 Services' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting financial mutual fund 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 | 0.6435 | |||
| Semi Deviation | 0.7621 | |||
| Standard Deviation | 0.8664 | |||
| Variance | 0.7506 | |||
| Downside Variance | 0.9315 | |||
| Semi Variance | 0.5808 | |||
| Expected Short fall | (0.67) |
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.
Story Coverage note for Financial Services
The number of cover stories for Financial Services depends on current market conditions and Financial Services' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Financial Services is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Financial Services' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios
Story Categories
Currently Trending Categories
Other Information on Investing in Financial Mutual Fund
Financial Services financial ratios help investors to determine whether Financial Mutual Fund 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 Services security.
| Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years | |
| Portfolio Backtesting Avoid under-diversification and over-optimization by backtesting your portfolios | |
| Technical Analysis Check basic technical indicators and analysis based on most latest market data | |
| Crypto Correlations Use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins |