[[abstract]]This paper presents a new method for forecasting the TAIEX based on fuzzy time series and technical indices analysis of the stock market. Because the proposed method uses both fuzzy time series and technical indices analysis of the stock market to analyze the historical training data in details for forecasting the TAIEX, it can get higher forecasting accuracy rate than the existing methods. The contribution of this paper is that we present a new fuzzy time series forecasting method based on the MACD index, combined with the stochastic line indices (KD indices) to forecast the TAIEX. It gets a higher average forecasting accuracy rate than the existing method for forecasting the TAIEX.[[notice]]補正完
The point-valued time series (PTS) is simply about one value in each time or period of the data, but...
The point-valued time series (PTS) is simply about one value in each time or period of the data, but...
There are many approaches to improve the forecasted accuracy of model based on fuzzy time series suc...
After reviewing the vast body of literature on using FTS in stock market forecasting, certain defici...
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, p...
AbstractIn recent years, there have been many time series methods proposed for forecasting enrollmen...
After reviewing the vast body of literature on using FTS in stock market forecasting, certain defici...
WOS: 000430162100002All fuzzy time series approaches proposed in the literature consider three steps...
A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, an...
In stock markets, many types of time series models such as statistical time series model, fuzzy time...
Most existing fuzzy forecasting models partition historical training time series into fuzzy time ser...
This paper proposes a new dual factor time-invariant fuzzy time series method that is capable of for...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JK...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JK...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JK...
The point-valued time series (PTS) is simply about one value in each time or period of the data, but...
The point-valued time series (PTS) is simply about one value in each time or period of the data, but...
There are many approaches to improve the forecasted accuracy of model based on fuzzy time series suc...
After reviewing the vast body of literature on using FTS in stock market forecasting, certain defici...
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, p...
AbstractIn recent years, there have been many time series methods proposed for forecasting enrollmen...
After reviewing the vast body of literature on using FTS in stock market forecasting, certain defici...
WOS: 000430162100002All fuzzy time series approaches proposed in the literature consider three steps...
A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, an...
In stock markets, many types of time series models such as statistical time series model, fuzzy time...
Most existing fuzzy forecasting models partition historical training time series into fuzzy time ser...
This paper proposes a new dual factor time-invariant fuzzy time series method that is capable of for...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JK...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JK...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JK...
The point-valued time series (PTS) is simply about one value in each time or period of the data, but...
The point-valued time series (PTS) is simply about one value in each time or period of the data, but...
There are many approaches to improve the forecasted accuracy of model based on fuzzy time series suc...