Swiss Helvetia Fund Forecast - Double Exponential Smoothing
| SWZ Fund | USD 6.22 0.04 0.64% |
The Double Exponential Smoothing forecasted value of Swiss Helvetia Closed on the next trading day is expected to be 6.22 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.84. Swiss Fund Forecast is based on your current time horizon.
At this time the relative strength index (rsi) of Swiss Helvetia's share price is below 20 . This usually implies that the 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 Swiss Helvetia hype-based prediction, you can estimate the value of Swiss Helvetia Closed from the perspective of Swiss Helvetia response to recently generated media hype and the effects of current headlines on its competitors.
The Double Exponential Smoothing forecasted value of Swiss Helvetia Closed on the next trading day is expected to be 6.22 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.84. Swiss Helvetia after-hype prediction price | USD 6.22 |
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.
Swiss |
Swiss Helvetia Additional Predictive Modules
Most predictive techniques to examine Swiss price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Swiss using various technical indicators. When you analyze Swiss 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 |
Swiss Helvetia Double Exponential Smoothing Price Forecast For the 3rd of January
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Swiss Helvetia Closed on the next trading day is expected to be 6.22 with a mean absolute deviation of 0.03, mean absolute percentage error of 0, and the sum of the absolute errors of 1.84.Please note that although there have been many attempts to predict Swiss 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 Swiss Helvetia's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Swiss Helvetia Fund Forecast Pattern
| Backtest Swiss Helvetia | Swiss Helvetia Price Prediction | Buy or Sell Advice |
Swiss Helvetia Forecasted Value
In the context of forecasting Swiss Helvetia's 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. Swiss Helvetia's downside and upside margins for the forecasting period are 5.60 and 6.85, respectively. We have considered Swiss Helvetia'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 Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Swiss Helvetia fund data series using in forecasting. Note that when a statistical model is used to represent Swiss Helvetia 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.0058 |
| MAD | Mean absolute deviation | 0.0311 |
| MAPE | Mean absolute percentage error | 0.0051 |
| SAE | Sum of the absolute errors | 1.8354 |
Predictive Modules for Swiss Helvetia
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Swiss Helvetia Closed. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the 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 Swiss Helvetia'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 Swiss Helvetia
For every potential investor in Swiss, whether a beginner or expert, Swiss Helvetia's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Swiss Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Swiss. Basic forecasting techniques help filter out the noise by identifying Swiss Helvetia's price trends.Swiss Helvetia 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 Swiss Helvetia fund to make a market-neutral strategy. Peer analysis of Swiss Helvetia could also be used in its relative valuation, which is a method of valuing Swiss Helvetia by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Swiss Helvetia Closed Technical and Predictive Analytics
The fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Swiss Helvetia'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 Swiss Helvetia's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Swiss Helvetia Market Strength Events
Market strength indicators help investors to evaluate how Swiss Helvetia fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Swiss Helvetia shares will generate the highest return on investment. By undertsting and applying Swiss Helvetia fund market strength indicators, traders can identify Swiss Helvetia Closed entry and exit signals to maximize returns.
Swiss Helvetia Risk Indicators
The analysis of Swiss Helvetia'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 Swiss Helvetia's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting swiss 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 | 0.4806 | |||
| Semi Deviation | 0.5695 | |||
| Standard Deviation | 0.6076 | |||
| Variance | 0.3692 | |||
| Downside Variance | 0.4522 | |||
| Semi Variance | 0.3243 | |||
| Expected Short fall | (0.55) |
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.| JBL | Jabil Circuit | |
| MRK | Merck Company | |
| AMGN | Amgen Inc |
Other Information on Investing in Swiss Fund
Swiss Helvetia financial ratios help investors to determine whether Swiss 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 Swiss with respect to the benefits of owning Swiss Helvetia security.
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