# HNX 30 Index Forecast - Polynomial Regression

HNX30 Index | 418.28 1.40 0.33% |

Most investors in HNX 30 cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the HNX 30's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets HNX 30's price structures and extracts relationships that further increase the generated results' accuracy.

HNX 30 polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for HNX 30 as well as the accuracy indicators are determined from the period prices. ## HNX 30 Polynomial Regression Price Forecast For the 7th of June

Given 90 days horizon, the Polynomial Regression forecasted value of HNX 30 on the next trading day is expected to be 430.64 with a mean absolute deviation of 6.12, mean absolute percentage error of 52.22, and the sum of the absolute errors of 379.68.Please note that although there have been many attempts to predict HNX Index 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 HNX 30's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

## HNX 30 Index Forecast Pattern

## HNX 30 Forecasted Value

In the context of forecasting HNX 30's Index 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. HNX 30's downside and upside margins for the forecasting period are 429.37 and 431.90, respectively. We have considered HNX 30'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.

## 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 HNX 30 index data series using in forecasting. Note that when a statistical model is used to represent HNX 30 index, 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.AIC | Akaike Information Criteria | 123.9038 |

Bias | Arithmetic mean of the errors | None |

MAD | Mean absolute deviation | 6.1239 |

MAPE | Mean absolute percentage error | 0.0162 |

SAE | Sum of the absolute errors | 379.6814 |

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## Predictive Modules for HNX 30

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as HNX 30. Regardless of method or technology, however, to accurately forecast the stock or bond 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.Sophisticated investors, who have witnessed many market ups and downs, frequently view the market will even out over time. This tendency of HNX 30'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. Please use the tools below to analyze the current value of HNX 30 in the context of predictive analytics.

Please note, it is not enough to conduct a financial or market analysis of a single entity such as HNX 30. Your research has to be compared to or analyzed against HNX 30's peers to derive any actionable benefits. When done correctly, HNX 30'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 HNX 30.

## Other Forecasting Options for HNX 30

For every potential investor in HNX, whether a beginner or expert, HNX 30's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. HNX Index price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in HNX. Basic forecasting techniques help filter out the noise by identifying HNX 30's price trends.## HNX 30 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 HNX 30 index to make a market-neutral strategy. Peer analysis of HNX 30 could also be used in its relative valuation, which is a method of valuing HNX 30 by comparing valuation metrics with similar companies.

Risk & Return | Correlation |

## HNX 30 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 HNX 30'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 HNX 30's current price.Cycle Indicators | ||

Math Operators | ||

Math Transform | ||

Momentum Indicators | ||

Overlap Studies | ||

Pattern Recognition | ||

Price Transform | ||

Statistic Functions | ||

Volatility Indicators | ||

Volume Indicators |

## HNX 30 Risk Indicators

The analysis of HNX 30's basic risk indicators is one of the essential steps in helping accuretelly forecast its future price. The process involves identifying the amount of risk involved in HNX 30's investment and either accepting that risk or mitigating it. Along with some funamental techniques of forecasting HNX 30 stock price, 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.

Mean Deviation | 0.9419 | |||

Semi Deviation | 1.05 | |||

Standard Deviation | 1.26 | |||

Variance | 1.58 | |||

Downside Variance | 1.77 | |||

Semi Variance | 1.09 | |||

Expected Short fall | (0.96) |

Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential stock investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards HNX 30 in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, HNX 30's short interest history, or implied volatility extrapolated from HNX 30 options trading.

## Becoming a Better Investor with Macroaxis

Macroaxis puts the power of mathematics on your side. We analyze your portfolios and positions such as HNX 30 using complex mathematical models and algorithms, but make them easy to understand. There is no real person involved in your portfolio analysis. We perform a number of calculations to compute absolute and relative portfolio volatility, correlation between your assets, value at risk, expected return as well as over 100 different fundamental and technical indicators.## Build Optimal Portfolios

### Align your risk with return expectations

Check out Risk vs Return Analysis to better understand how to build diversified portfolios. Also, note that the market value of any index could be tightly coupled with the direction of predictive economic indicators such as signals in producer price index. You can also try the Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.

## Complementary Tools for HNX Index analysis

When running HNX 30's price analysis, check to measure HNX 30's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy HNX 30 is operating at the current time. Most of HNX 30's value examination focuses on studying past and present price action to predict the probability of HNX 30's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move HNX 30's price. Additionally, you may evaluate how the addition of HNX 30 to your portfolios can decrease your overall portfolio volatility.

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