Ssga Sp Mutual Fund Forecast - Simple Exponential Smoothing
| SVSPX Fund | USD 237.02 0.51 0.21% |
The Simple Exponential Smoothing forecasted value of Ssga Sp 500 on the next trading day is expected to be 237.12 with a mean absolute deviation of 1.35 and the sum of the absolute errors of 80.75. Ssga Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Ssga Sp stock prices and determine the direction of Ssga Sp 500's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Ssga Sp's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Ssga Sp to cross-verify your projections. Ssga |
Most investors in Ssga Sp 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 Ssga Sp's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Ssga Sp's price structures and extracts relationships that further increase the generated results' accuracy.
Ssga Sp simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for Ssga Sp 500 are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Ssga Sp 500 prices get older. Ssga Sp Simple Exponential Smoothing Price Forecast For the 19th of April
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Ssga Sp 500 on the next trading day is expected to be 237.12 with a mean absolute deviation of 1.35, mean absolute percentage error of 3.05, and the sum of the absolute errors of 80.75.Please note that although there have been many attempts to predict Ssga 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 Ssga Sp's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Ssga Sp Mutual Fund Forecast Pattern
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Ssga Sp Forecasted Value
In the context of forecasting Ssga Sp'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. Ssga Sp's downside and upside margins for the forecasting period are 236.40 and 237.84, respectively. We have considered Ssga Sp'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 Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Ssga Sp mutual fund data series using in forecasting. Note that when a statistical model is used to represent Ssga Sp 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 | 117.3877 |
| Bias | Arithmetic mean of the errors | -0.1491 |
| MAD | Mean absolute deviation | 1.3459 |
| MAPE | Mean absolute percentage error | 0.0056 |
| SAE | Sum of the absolute errors | 80.7528 |
Predictive Modules for Ssga Sp
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Ssga Sp 500. 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 Ssga Sp'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 Ssga Sp
For every potential investor in Ssga, whether a beginner or expert, Ssga Sp's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Ssga Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Ssga. Basic forecasting techniques help filter out the noise by identifying Ssga Sp's price trends.Ssga Sp 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 Ssga Sp mutual fund to make a market-neutral strategy. Peer analysis of Ssga Sp could also be used in its relative valuation, which is a method of valuing Ssga Sp by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Ssga Sp 500 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 Ssga Sp'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 Ssga Sp's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Ssga Sp Market Strength Events
Market strength indicators help investors to evaluate how Ssga Sp 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 Ssga Sp shares will generate the highest return on investment. By undertsting and applying Ssga Sp mutual fund market strength indicators, traders can identify Ssga Sp 500 entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 237.02 | |||
| Day Typical Price | 237.02 | |||
| Price Action Indicator | (0.25) | |||
| Period Momentum Indicator | (0.51) | |||
| Relative Strength Index | 72.03 |
Ssga Sp Risk Indicators
The analysis of Ssga Sp'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 Ssga Sp's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ssga 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 | 0.5662 | |||
| Semi Deviation | 0.5922 | |||
| Standard Deviation | 0.7319 | |||
| Variance | 0.5357 | |||
| Downside Variance | 0.5088 | |||
| Semi Variance | 0.3507 | |||
| Expected Short fall | (0.61) |
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.
Currently Active Assets on Macroaxis
Check out Historical Fundamental Analysis of Ssga Sp to cross-verify your projections. You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.