Quotient Technology Stock Forecast - Polynomial Regression

QUOTDelisted Stock  USD 3.88  0.02  0.51%   
The Polynomial Regression forecasted value of Quotient Technology on the next trading day is expected to be 3.74 with a mean absolute deviation of 0.12 and the sum of the absolute errors of 7.13. Quotient Stock Forecast is based on your current time horizon.
  
Quotient Technology polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Quotient Technology as well as the accuracy indicators are determined from the period prices.

Quotient Technology Polynomial Regression Price Forecast For the 27th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Quotient Technology on the next trading day is expected to be 3.74 with a mean absolute deviation of 0.12, mean absolute percentage error of 0.02, and the sum of the absolute errors of 7.13.
Please note that although there have been many attempts to predict Quotient Stock 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 Quotient Technology's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Quotient Technology Stock Forecast Pattern

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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 Quotient Technology stock data series using in forecasting. Note that when a statistical model is used to represent Quotient Technology 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.
AICAkaike Information Criteria114.2714
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1168
MAPEMean absolute percentage error0.0365
SAESum of the absolute errors7.1261
A single variable polynomial regression model attempts to put a curve through the Quotient Technology 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 + ... + am*Xm

Predictive Modules for Quotient Technology

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Quotient Technology. 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
LowEstimatedHigh
3.883.883.88
Details
Intrinsic
Valuation
LowRealHigh
3.013.014.27
Details

Quotient Technology 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 Quotient Technology stock to make a market-neutral strategy. Peer analysis of Quotient Technology could also be used in its relative valuation, which is a method of valuing Quotient Technology by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Quotient Technology Market Strength Events

Market strength indicators help investors to evaluate how Quotient Technology stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Quotient Technology shares will generate the highest return on investment. By undertsting and applying Quotient Technology stock market strength indicators, traders can identify Quotient Technology entry and exit signals to maximize returns.

Quotient Technology Risk Indicators

The analysis of Quotient Technology'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 Quotient Technology's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting quotient stock 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.
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.

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Other Consideration for investing in Quotient Stock

If you are still planning to invest in Quotient Technology check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Quotient Technology's history and understand the potential risks before investing.
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