China Marine Pink Sheet Forecast - Polynomial Regression

CMFODelisted Stock  USD 0.0001  0.00  0.00%   
The Polynomial Regression forecasted value of China Marine Food on the next trading day is expected to be 0.0001 with a mean absolute deviation of 0.000076 and the sum of the absolute errors of 0. China Pink Sheet Forecast is based on your current time horizon.
  
China Marine polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for China Marine Food as well as the accuracy indicators are determined from the period prices.

China Marine Polynomial Regression Price Forecast For the 8th of January

Given 90 days horizon, the Polynomial Regression forecasted value of China Marine Food on the next trading day is expected to be 0.0001 with a mean absolute deviation of 0.000076, mean absolute percentage error of 0.00000002, and the sum of the absolute errors of 0.
Please note that although there have been many attempts to predict China 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 China Marine's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

China Marine 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 China Marine pink sheet data series using in forecasting. Note that when a statistical model is used to represent China Marine 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 Criteria100.1321
BiasArithmetic mean of the errors None
MADMean absolute deviation1.0E-4
MAPEMean absolute percentage error0.2426
SAESum of the absolute errors0.0046
A single variable polynomial regression model attempts to put a curve through the China Marine 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 China Marine

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as China Marine Food. 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.
Hype
Prediction
LowEstimatedHigh
0.000.00010.00
Details
Intrinsic
Valuation
LowRealHigh
0.000.0000950.00
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as China Marine. Your research has to be compared to or analyzed against China Marine's peers to derive any actionable benefits. When done correctly, China Marine's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in China Marine Food.

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

China Marine Market Strength Events

Market strength indicators help investors to evaluate how China Marine 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 China Marine shares will generate the highest return on investment. By undertsting and applying China Marine pink sheet market strength indicators, traders can identify China Marine Food entry and exit signals to maximize returns.

Pair Trading with China Marine

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 China Marine 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 China Marine will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to China Marine could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace China Marine 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 China Marine - 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 China Marine Food to buy it.
The correlation of China Marine is a statistical measure of how it moves in relation to other instruments. 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 China Marine moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if China Marine Food 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 China Marine 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
Check out Trending Equities 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 census.
You can also try the Volatility Analysis module to get historical volatility and risk analysis based on latest market data.

Other Consideration for investing in China Pink Sheet

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