GROWTH FUND Mutual Fund Forecast - Double Exponential Smoothing

CGFEX
 Fund
  

USD 51.46  1.94  3.63%   

GROWTH Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast GROWTH FUND historical stock prices and determine the direction of GROWTH FUND OF's future trends based on various well-known forecasting models. However, solely looking at the historical price movement is usually misleading. Macroaxis recommends to always use this module together with analysis of GROWTH FUND historical fundamentals such as revenue growth or operating cash flow patterns.
Continue to Historical Fundamental Analysis of GROWTH FUND to cross-verify your projections.
  
Most investors in GROWTH FUND cannot accurately predict what will happen the next trading day because, historically, stock 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 GROWTH FUND's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets GROWTH FUND'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 GROWTH FUND works best with periods where there are trends or seasonality.

GROWTH FUND Double Exponential Smoothing Price Forecast For the 3rd of December

Given 90 days horizon, the Double Exponential Smoothing forecasted value of GROWTH FUND OF on the next trading day is expected to be 51.61 with a mean absolute deviation of 0.80, mean absolute percentage error of 1.07, and the sum of the absolute errors of 47.99.
Please note that although there have been many attempts to predict GROWTH 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 GROWTH FUND's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

GROWTH FUND Mutual Fund Forecast Pattern

Backtest GROWTH FUNDGROWTH FUND Price PredictionBuy or Sell Advice 

GROWTH FUND Forecasted Value

In the context of forecasting GROWTH FUND'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. GROWTH FUND's downside and upside margins for the forecasting period are 49.75 and 53.47, respectively. We have considered GROWTH FUND'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.
Market Value 51.46
51.61
Expected Value
53.47
Upside

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 GROWTH FUND mutual fund data series using in forecasting. Note that when a statistical model is used to represent GROWTH FUND 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 0.1375
MADMean absolute deviation0.7999
MAPEMean absolute percentage error0.0157
SAESum of the absolute errors47.9928
When GROWTH FUND OF prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any GROWTH FUND OF trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent GROWTH FUND observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for GROWTH FUND

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as GROWTH FUND. Regardless of method or technology, however, to accurately forecast the stock or bond market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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, frequently view the market will even out over time. This tendency of GROWTH FUND'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. Please use the tools below to analyze the current value of GROWTH FUND in the context of predictive analytics.
Hype
Prediction
LowEstimated ValueHigh
51.5653.4055.24
Details
Intrinsic
Valuation
LowReal ValueHigh
51.1653.0054.84
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
48.7751.3253.88
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as GROWTH FUND. Your research has to be compared to or analyzed against GROWTH FUND's peers to derive any actionable benefits. When done correctly, GROWTH FUND's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy towards taking a position in GROWTH FUND.

Other Forecasting Options for GROWTH FUND

For every potential investor in GROWTH, whether a beginner or expert, GROWTH FUND's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. GROWTH Mutual Fund price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in GROWTH. Basic forecasting techniques help filter out the noise by identifying GROWTH FUND's price trends.

GROWTH FUND 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 GROWTH FUND mutual fund to make a market-neutral strategy. Peer analysis of GROWTH FUND could also be used in its relative valuation, which is a method of valuing GROWTH FUND by comparing valuation metrics with similar companies.
Nordea Bank AbpAMN Healthcare ServicesTwist Bioscience CorpFreedom Holding CorpGlobal X NASDAQFRANKLIN MUTUAL EUROPEANBHP Group LimitedNatural Health TrendIShares MSCI USABetaPro Canadian GoldAramark HoldingsVanguard Long-TermSeagate Technology PLCVistra Energy CorpExxon Mobil Corp
 Risk & Return  Correlation

GROWTH FUND Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of GROWTH FUND'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 GROWTH FUND's current price.

GROWTH FUND Risk Indicators

The analysis of GROWTH FUND's basic risk indicators is one of the essential steps in helping accuretelly forecast its future price. The process involves identifying the amount of risk involved in GROWTH FUND's investment and either accepting that risk or mitigating it. Along with some funamental techniques of forecasting GROWTH FUND stock price, 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.
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential stock investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Be your own money manager

Our tools can tell you how much better you can do entering a position in GROWTH FUND without increasing your portfolio risk or giving up the expected return. As an individual investor, you need to find a reliable way to track all your investment portfolios. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing all investors analytical transparency into all their portfolios, our tools can evaluate risk-adjusted returns of your individual positions relative to your overall portfolio.

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Pair Trading with GROWTH FUND

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if GROWTH FUND position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in GROWTH FUND will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to GROWTH FUND could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace GROWTH FUND when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back GROWTH FUND - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling GROWTH FUND OF to buy it.
The correlation of GROWTH FUND is a statistical measure of how it moves in relation to other equities. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as GROWTH FUND moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if GROWTH FUND moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for GROWTH FUND can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching
Continue to Historical Fundamental Analysis of GROWTH FUND to cross-verify your projections. Note that the GROWTH FUND information on this page should be used as a complementary analysis to other GROWTH FUND'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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.

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When running GROWTH FUND price analysis, check to measure GROWTH FUND's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy GROWTH FUND is operating at the current time. Most of GROWTH FUND's value examination focuses on studying past and present price action to predict the probability of GROWTH FUND's future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move GROWTH FUND's price. Additionally, you may evaluate how the addition of GROWTH FUND to your portfolios can decrease your overall portfolio volatility.
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Please note, there is a significant difference between GROWTH FUND's value and its price as these two are different measures arrived at by different means. Investors typically determine GROWTH FUND value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, GROWTH FUND's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.