Cryptocurrencies, with Bitcoin being the most notable example, have attracted considerable
attention in recent years, and they have experienced large fluctuations in their price. While a …

Time Series is an orderly sequence of values of a variable in a particular domain.
Forecasting is a challenging task in the area of Time Series Analysis. Forecasting has a …

The study shows that there are two main problems that affect the performance of fuzzy time
series (FTS) models, namely the selection of the universe of discourse and the …

The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI)
has become overwhelming, making it quite challenging for academics and relevant …

In recent years, the demand for developing low computational cost methods to deal with
uncertainties in forecasting has been increased. Probabilistic forecasting is a class of …

Abstract Seasonal Auto Regressive Fractionally Integrated Moving Average (SARFIMA) is a
well-known model for forecasting of seasonal time series that follow a long memory process …

Various models used in stock market forecasting presented have been classified according
to the data preparation, forecasting methodology, performance evaluation, and performance …

Time series forecasting is a powerful tool in planning and decision making, from traditional
statistical models to soft computing and artificial intelligence approaches several methods …

An interpretable regression model is proposed in this paper for stock price prediction.
Conventional offline neuro-fuzzy systems are only able to generate implications based on …

Financial bubbles represent a severe problem for investors. In particular, the cryptocurrency
market has witnessed the bursting of different bubbles in the last decade, which in turn have …