HNX 30 Index Forecast - Simple Exponential Smoothing

HNX30 Index   481.21  13.82  2.96%   
The Simple Exponential Smoothing forecasted value of HNX 30 on the next trading day is expected to be 481.21 with a mean absolute deviation of  5.32  and the sum of the absolute errors of 318.93. Investors can use prediction functions to forecast HNX 30's index prices and determine the direction of HNX 30's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading.
Most investors in HNX 30 cannot accurately predict what will happen the next trading day because, historically, index 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 simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for HNX 30 are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as HNX 30 prices get older.

HNX 30 Simple Exponential Smoothing Price Forecast For the 23rd of April

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of HNX 30 on the next trading day is expected to be 481.21 with a mean absolute deviation of 5.32, mean absolute percentage error of 68.30, and the sum of the absolute errors of 318.93.
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 479.59 and 482.83, 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.
Market Value
481.21
479.59
Downside
481.21
Expected Value
482.83
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing 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.
AICAkaike Information Criteria120.4966
BiasArithmetic mean of the errors 0.0648
MADMean absolute deviation5.3155
MAPEMean absolute percentage error0.0105
SAESum of the absolute errors318.93
This simple exponential smoothing model begins by setting HNX 30 forecast for the second period equal to the observation of the first period. In other words, recent HNX 30 observations are given relatively more weight in forecasting than the older observations.

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 index market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the index 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 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 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 index 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.

HNX 30 Market Strength Events

Market strength indicators help investors to evaluate how HNX 30 index reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading HNX 30 shares will generate the highest return on investment. By undertsting and applying HNX 30 index market strength indicators, traders can identify HNX 30 entry and exit signals to maximize returns.

HNX 30 Risk Indicators

The analysis of HNX 30'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 HNX 30's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting hnx index 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.

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