Central Hydropower Stock Forecast - Simple Regression

CHP Stock   33,500  500.00  1.52%   
The Simple Regression forecasted value of Central Hydropower JSC on the next trading day is expected to be 33,123 with a mean absolute deviation of 238.43 and the sum of the absolute errors of 14,545. Investors can use prediction functions to forecast Central Hydropower's stock prices and determine the direction of Central Hydropower JSC'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 Central Hydropower's historical fundamentals, such as revenue growth or operating cash flow patterns. 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 board of governors.
  
Simple Regression model is a single variable regression model that attempts to put a straight line through Central Hydropower price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Central Hydropower Simple Regression Price Forecast For the 29th of November

Given 90 days horizon, the Simple Regression forecasted value of Central Hydropower JSC on the next trading day is expected to be 33,123 with a mean absolute deviation of 238.43, mean absolute percentage error of 91,997, and the sum of the absolute errors of 14,545.
Please note that although there have been many attempts to predict Central 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 Central Hydropower's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Central Hydropower Stock Forecast Pattern

Central Hydropower Forecasted Value

In the context of forecasting Central Hydropower'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. Central Hydropower's downside and upside margins for the forecasting period are 33,122 and 33,123, respectively. We have considered Central Hydropower'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
33,500
33,122
Downside
33,123
Expected Value
33,123
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of Central Hydropower stock data series using in forecasting. Note that when a statistical model is used to represent Central Hydropower 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 Criteria129.54
BiasArithmetic mean of the errors None
MADMean absolute deviation238.4345
MAPEMean absolute percentage error0.0072
SAESum of the absolute errors14544.5056
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Central Hydropower JSC historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Predictive Modules for Central Hydropower

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

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

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

Central Hydropower JSC 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 Central Hydropower'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 Central Hydropower's current price.

Central Hydropower Market Strength Events

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

Central Hydropower Risk Indicators

The analysis of Central Hydropower'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 Central Hydropower's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting central 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 Central Hydropower

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