Splunk Stock Forecast - Polynomial Regression

Splunk polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Splunk Inc as well as the accuracy indicators are determined from the period prices.

Splunk Polynomial Regression Price Forecast For the 2nd of December

Given 90 days horizon, the Polynomial Regression forecasted value of Splunk Inc on the next trading day is expected to be 104.44 with a mean absolute deviation of 2.34, mean absolute percentage error of 7.71, and the sum of the absolute errors of 142.47.

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Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of Splunk stock data series using in forecasting. Note that when a statistical model is used to represent Splunk stock, 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. A single variable polynomial regression model attempts to put a curve through the Splunk historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a₀ + a₁*X + a₂*X² + a₃*X³ + ... + a_m*X^m

Predictive Modules for Splunk

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Splunk Inc. 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.

Hype Prediction Low Estimated High 103.58 103.58 103.58 Details

Intrinsic Valuation Low Real High 85.16 85.16 113.94 Details

Bollinger Band Projection (param) Low Middle High 101.17 106.62 112.07 Details

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