Time series forecasting is a widely applied approach in sequential data series including the
stock market. Time series forecasting can be examined through single step ahead as well as …

Stock market trading is an unending investment exercise globally. It has potentials to
generate high returns on investors' investment. However, it is characterized by high risk of …

The aim of anomaly detection is to find patterns or data points that are not confirming the
expected behavior inside the dataset. Techniques from a variety of disciplines like machine …

This paper describes a framework that utilizes an adaptive‐network‐based fuzzy inference
system to perform user‐constrained pattern recognition on time‐series data. Using a …

The stock market index future price forecasting is one of the imperative financial time series
problems. Accurately estimated future closing prices can play important role in making …

Stock Markets represent a complex, nonlinear, ever-changing, trading systems where
traders (investors) are competing for profit. Stock market forecasting have attracted some …

Stock marketplace tradeoff is an endless investment implementation worldwide. It has
capabilities to produce maximum profits on stockholders' venture. In the globe, the stock …

Abstract In 2010, Hadavandi, Shavandi & Ghanbari noted that fuzzy inference systemused
for forecasting stock price requires an effective Rule Base and Knowledge Base to be built in …

There are a variety of theories, procedures, and approaches that make time series prediction
more accurate, demanding, and exciting for researchers. Dynamic and volatile nature of …

We generalize the double smoothing local linear regression method to nonparametric
regression of time series. Under a strong mixing condition for the dependence of the time …