Vinacomin Power Stock Forecast - Naive Prediction

DTK Stock   11,900  500.00  4.39%   
The Naive Prediction forecasted value of Vinacomin Power Holding on the next trading day is expected to be 11,430 with a mean absolute deviation of 243.09 and the sum of the absolute errors of 14,828. Investors can use prediction functions to forecast Vinacomin Power's stock prices and determine the direction of Vinacomin Power Holding's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading. We recommend always using this module together with an analysis of Vinacomin Power's historical fundamentals, such as revenue growth or operating cash flow patterns. Check out Investing Opportunities 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 board of governors.
  
A naive forecasting model for Vinacomin Power is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Vinacomin Power Holding value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Vinacomin Power Naive Prediction Price Forecast For the 2nd of December

Given 90 days horizon, the Naive Prediction forecasted value of Vinacomin Power Holding on the next trading day is expected to be 11,430 with a mean absolute deviation of 243.09, mean absolute percentage error of 94,344, and the sum of the absolute errors of 14,828.
Please note that although there have been many attempts to predict Vinacomin 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 Vinacomin Power's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Vinacomin Power Stock Forecast Pattern

Vinacomin Power Forecasted Value

In the context of forecasting Vinacomin Power's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Vinacomin Power's downside and upside margins for the forecasting period are 11,427 and 11,433, respectively. We have considered Vinacomin Power's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
11,900
11,427
Downside
11,430
Expected Value
11,433
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Vinacomin Power stock data series using in forecasting. Note that when a statistical model is used to represent Vinacomin Power 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 Criteria129.5652
BiasArithmetic mean of the errors None
MADMean absolute deviation243.0865
MAPEMean absolute percentage error0.0196
SAESum of the absolute errors14828.2746
This model is not at all useful as a medium-long range forecasting tool of Vinacomin Power Holding. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Vinacomin Power. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Vinacomin Power

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

Other Forecasting Options for Vinacomin Power

For every potential investor in Vinacomin, whether a beginner or expert, Vinacomin Power's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Vinacomin Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Vinacomin. Basic forecasting techniques help filter out the noise by identifying Vinacomin Power's price trends.

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

Vinacomin Power Holding Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Vinacomin Power's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Vinacomin Power's current price.

Vinacomin Power Market Strength Events

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

Vinacomin Power Risk Indicators

The analysis of Vinacomin Power'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 Vinacomin Power's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting vinacomin 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.

Pair Trading with Vinacomin Power

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 Vinacomin Power 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 Vinacomin Power will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Vinacomin Power could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Vinacomin Power 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 Vinacomin Power - 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 Vinacomin Power Holding to buy it.
The correlation of Vinacomin Power 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 Vinacomin Power moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Vinacomin Power Holding 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 Vinacomin Power 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