SZSE Component Index Forecast - Triple Exponential Smoothing

SZI Index   10,433  179.18  1.69%   
The Triple Exponential Smoothing forecasted value of SZSE Component on the next trading day is expected to be 10,444 with a mean absolute deviation of 216.22 and the sum of the absolute errors of 12,757. Investors can use prediction functions to forecast SZSE Component's index prices and determine the direction of SZSE Component's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading.
Triple exponential smoothing for SZSE Component - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When SZSE Component prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in SZSE Component price movement. However, neither of these exponential smoothing models address any seasonality of SZSE Component.

SZSE Component Triple Exponential Smoothing Price Forecast For the 2nd of December

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of SZSE Component on the next trading day is expected to be 10,444 with a mean absolute deviation of 216.22, mean absolute percentage error of 91,737, and the sum of the absolute errors of 12,757.
Please note that although there have been many attempts to predict SZSE 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 SZSE Component's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

SZSE Component Index Forecast Pattern

SZSE Component Forecasted Value

In the context of forecasting SZSE Component'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. SZSE Component's downside and upside margins for the forecasting period are 10,441 and 10,447, respectively. We have considered SZSE Component'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
10,433
10,441
Downside
10,444
Expected Value
10,447
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of SZSE Component index data series using in forecasting. Note that when a statistical model is used to represent SZSE Component 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 CriteriaHuge
BiasArithmetic mean of the errors 52.8103
MADMean absolute deviation216.2207
MAPEMean absolute percentage error0.0216
SAESum of the absolute errors12757.0206
As with simple exponential smoothing, in triple exponential smoothing models past SZSE Component observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older SZSE Component observations.

Predictive Modules for SZSE Component

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

Other Forecasting Options for SZSE Component

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

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

SZSE Component 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 SZSE Component'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 SZSE Component's current price.

SZSE Component Market Strength Events

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

SZSE Component Risk Indicators

The analysis of SZSE Component'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 SZSE Component's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting szse 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.