Swan Defined Mutual Fund Forecast - Simple Regression
| SDRIX Fund | USD 14.74 0.02 0.14% |
The Simple Regression forecasted value of Swan Defined Risk on the next trading day is expected to be 14.50 with a mean absolute deviation of 0.15 and the sum of the absolute errors of 9.61. Swan Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Swan Defined stock prices and determine the direction of Swan Defined Risk's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Swan Defined's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Swan Defined to cross-verify your projections. Swan |
Most investors in Swan Defined cannot accurately predict what will happen the next trading day because, historically, fund markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Swan Defined's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Swan Defined's price structures and extracts relationships that further increase the generated results' accuracy.
Simple Regression model is a single variable regression model that attempts to put a straight line through Swan Defined price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X. Swan Defined Simple Regression Price Forecast For the 22nd of May
Given 90 days horizon, the Simple Regression forecasted value of Swan Defined Risk on the next trading day is expected to be 14.50 with a mean absolute deviation of 0.15, mean absolute percentage error of 0.03, and the sum of the absolute errors of 9.61.Please note that although there have been many attempts to predict Swan 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 Swan Defined's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Swan Defined Mutual Fund Forecast Pattern
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Swan Defined Forecasted Value
In the context of forecasting Swan Defined's 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. Swan Defined's downside and upside margins for the forecasting period are 13.96 and 15.03, respectively. We have considered Swan Defined'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 Simple Regression forecasting method's relative quality and the estimations of the prediction error of Swan Defined mutual fund data series using in forecasting. Note that when a statistical model is used to represent Swan Defined 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 | 116.5401 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.1549 |
| MAPE | Mean absolute percentage error | 0.0107 |
| SAE | Sum of the absolute errors | 9.6067 |
Predictive Modules for Swan Defined
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Swan Defined Risk. 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 Swan Defined'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 Swan Defined
For every potential investor in Swan, whether a beginner or expert, Swan Defined's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Swan Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Swan. Basic forecasting techniques help filter out the noise by identifying Swan Defined's price trends.Swan Defined 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 Swan Defined mutual fund to make a market-neutral strategy. Peer analysis of Swan Defined could also be used in its relative valuation, which is a method of valuing Swan Defined by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Swan Defined Risk Technical and Predictive Analytics
The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Swan Defined'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 Swan Defined's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Swan Defined Market Strength Events
Market strength indicators help investors to evaluate how Swan Defined 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 Swan Defined shares will generate the highest return on investment. By undertsting and applying Swan Defined mutual fund market strength indicators, traders can identify Swan Defined Risk entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 14.74 | |||
| Day Typical Price | 14.74 | |||
| Price Action Indicator | 0.01 | |||
| Period Momentum Indicator | 0.02 |
Swan Defined Risk Indicators
The analysis of Swan Defined'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 Swan Defined's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting swan 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 | 0.4137 | |||
| Semi Deviation | 0.4612 | |||
| Standard Deviation | 0.5315 | |||
| Variance | 0.2825 | |||
| Downside Variance | 0.348 | |||
| Semi Variance | 0.2127 | |||
| Expected Short fall | (0.48) |
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.
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.Check out Historical Fundamental Analysis of Swan Defined to cross-verify your projections. You can also try the Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.