Catalyst/smh Total Mutual Fund Forecast - Double Exponential Smoothing
| TRICX Fund | USD 4.73 0.01 0.21% |
The Double Exponential Smoothing forecasted value of Catalystsmh Total Return on the next trading day is expected to be 4.73 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.77. Catalyst/smh Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Catalyst/smh Total stock prices and determine the direction of Catalystsmh Total Return's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Catalyst/smh Total's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Catalyst/smh Total to cross-verify your projections. Catalyst/smh |
Most investors in Catalyst/smh Total 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 Catalyst/smh Total's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Catalyst/smh Total's price structures and extracts relationships that further increase the generated results' accuracy.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Catalyst/smh Total works best with periods where there are trends or seasonality. Catalyst/smh Total Double Exponential Smoothing Price Forecast For the 22nd of May
Given 90 days horizon, the Double Exponential Smoothing forecasted value of Catalystsmh Total Return on the next trading day is expected to be 4.73 with a mean absolute deviation of 0.01, mean absolute percentage error of 0.0003, and the sum of the absolute errors of 0.77.Please note that although there have been many attempts to predict Catalyst/smh 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 Catalyst/smh Total's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Catalyst/smh Total Mutual Fund Forecast Pattern
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Catalyst/smh Total Forecasted Value
In the context of forecasting Catalyst/smh Total'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. Catalyst/smh Total's downside and upside margins for the forecasting period are 4.42 and 5.05, respectively. We have considered Catalyst/smh Total'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 Catalyst/smh Total mutual fund data series using in forecasting. Note that when a statistical model is used to represent Catalyst/smh Total 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 | Huge |
| Bias | Arithmetic mean of the errors | -0.0021 |
| MAD | Mean absolute deviation | 0.013 |
| MAPE | Mean absolute percentage error | 0.0028 |
| SAE | Sum of the absolute errors | 0.7679 |
Predictive Modules for Catalyst/smh Total
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Catalystsmh Total Return. 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 Catalyst/smh Total'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 Catalyst/smh Total
For every potential investor in Catalyst/smh, whether a beginner or expert, Catalyst/smh Total's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Catalyst/smh Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Catalyst/smh. Basic forecasting techniques help filter out the noise by identifying Catalyst/smh Total's price trends.Catalyst/smh Total 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 Catalyst/smh Total mutual fund to make a market-neutral strategy. Peer analysis of Catalyst/smh Total could also be used in its relative valuation, which is a method of valuing Catalyst/smh Total by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Catalystsmh Total Return 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 Catalyst/smh Total'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 Catalyst/smh Total's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Catalyst/smh Total Market Strength Events
Market strength indicators help investors to evaluate how Catalyst/smh Total 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 Catalyst/smh Total shares will generate the highest return on investment. By undertsting and applying Catalyst/smh Total mutual fund market strength indicators, traders can identify Catalystsmh Total Return entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 4.73 | |||
| Day Typical Price | 4.73 | |||
| Price Action Indicator | 0.005 | |||
| Period Momentum Indicator | 0.01 |
Catalyst/smh Total Risk Indicators
The analysis of Catalyst/smh Total'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 Catalyst/smh Total's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting catalyst/smh 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 | 0.2588 | |||
| Semi Deviation | 0.1834 | |||
| Standard Deviation | 0.3398 | |||
| Variance | 0.1155 | |||
| Downside Variance | 0.1809 | |||
| Semi Variance | 0.0337 | |||
| Expected Short fall | (0.34) |
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 Catalyst/smh Total to cross-verify your projections. Note that the Catalystsmh Total Return information on this page should be used as a complementary analysis to other Catalyst/smh Total's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Equity Valuation module to check real value of public entities based on technical and fundamental data.