Spark Networks Stock Forecast - 4 Period Moving Average

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LOV -- USA Stock  

USD 3.00  0.09  3.09%

Spark Networks Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Spark Networks historical stock prices and determine the direction of Spark Networks 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 Spark Networks historical fundamentals such as revenue growth or operating cash flow patterns. Although Spark Networks naive historical forecasting may sometimes provide an important future outlook for the firm we recommend to always cross-verify it against solid analysis of Spark Networks systematic risk associated with finding meaningful patterns of Spark Networks fundamentals over time. Additionally, see Historical Fundamental Analysis of Spark Networks to cross-verify your projections.

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Spark Networks Trade and Non Trade Payables is fairly stable at the moment as compared to the last year. Spark Networks reported Trade and Non Trade Payables of 26.48 Million in 2019. Property Plant and Equipment Net is likely to grow to 3,695 in 2020, whereas Current Assets are likely to drop slightly above 9.4 M in 2020.
A four-period moving average forecast model for Spark Networks is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

Spark Networks 4 Period Moving Average Price Forecast For the 30th of May

Given 30 days horizon, the forecasted value of Spark Networks on the next trading day is expected to be  2.95  with a mean absolute deviation of  0.24 , mean absolute percentage error of  0.11 , and the sum of the absolute errors of  13.88 

Spark Networks Stock Forecast Pattern

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Spark Networks Forecasted Value

Market Value
29th of May 2020
Expected Value

Model Predictive Factors

AICAkaike Information Criteria108.5767
BiasArithmetic mean of the errors 0.0597
MADMean absolute deviation0.2436
MAPEMean absolute percentage error0.0834
SAESum of the absolute errors13.885
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Spark Networks. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Spark Networks and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Predictive Modules for Spark Networks

There are currently many different techniques concerning forecasting the market as a whole as well as predicting future values of individual securities such as Spark Networks. Regardless of method or technology, however, to accurately forecast the stock 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.
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Other Forecasting Options for Spark Networks

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Additionally, see Historical Fundamental Analysis of Spark Networks to cross-verify your projections. Please also try Balance Of Power module to check stock momentum by analyzing balance of power indicator and other technical ratios.
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