Lict Pink Sheet Forecast - Polynomial Regression

LICTDelisted Stock  USD 19,700  150.00  0.76%   
The Polynomial Regression forecasted value of Lict Corporation on the next trading day is expected to be 19,751 with a mean absolute deviation of 67.17 and the sum of the absolute errors of 1,545. Lict Pink Sheet Forecast is based on your current time horizon.
  
Lict polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Lict Corporation as well as the accuracy indicators are determined from the period prices.

Lict Polynomial Regression Price Forecast For the 25th of January

Given 90 days horizon, the Polynomial Regression forecasted value of Lict Corporation on the next trading day is expected to be 19,751 with a mean absolute deviation of 67.17, mean absolute percentage error of 7,219, and the sum of the absolute errors of 1,545.
Please note that although there have been many attempts to predict Lict Pink Sheet 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 Lict's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Lict Pink Sheet 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 Lict pink sheet data series using in forecasting. Note that when a statistical model is used to represent Lict pink sheet, 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 Criteria57.1556
BiasArithmetic mean of the errors None
MADMean absolute deviation67.1681
MAPEMean absolute percentage error0.0034
SAESum of the absolute errors1544.8672
A single variable polynomial regression model attempts to put a curve through the Lict 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 Lict

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Lict. Regardless of method or technology, however, to accurately forecast the pink sheet market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the pink sheet 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 Lict'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.
Hype
Prediction
LowEstimatedHigh
19,70019,70019,700
Details
Intrinsic
Valuation
LowRealHigh
16,74516,74521,670
Details
Bollinger
Band Projection (param)
LowMiddleHigh
19,32919,67520,021
Details

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

Lict Market Strength Events

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

Thematic Opportunities

Explore Investment Opportunities

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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Check out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in main economic indicators.
You can also try the Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.

Other Consideration for investing in Lict Pink Sheet

If you are still planning to invest in Lict 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 Lict's history and understand the potential risks before investing.
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