… A hybrid approach to the Japanese candlestick method for financial forecasting is developed
in [84]. This paper discusses an experimental study of the Japanese candlestick method …

… to diverse markets to forecast either indexes or … soft computing techniques to stock market
problems; in particular, over 100 related scientific articles applied to stock market forecasting …

… logic computing and in the financial world in ex plaining the use of fuzzy logic to forecast the
… (FL) to tackle the financial time series forecasting problems. Experimental results on set of …

… , soft computing models for solving the dilemma. As the main component of soft computing
… The machine learning approach for financial modeling is an attempt to find financial models …

… techniques for enhancing financial forecasting capabilities. … financial forecasting, exploring
the role of soft computing techniques in harnessing the power of AI for data-driven financial …

… As we are working in the area of financial forecasting by using soft computing techniques..
So we have to select best one soft computing technique to find the forecasted result one. So …

… data, and focused on financial applications. Numerous studies applying GARCH and its
expansion methods to various contexts aside from financial data have been conducted. Several …

… covering financial time series forecasting and trading systems using traditional soft computing
… , focusing on DL implementations of financial time series forecasting. Our motivation is two-…

… and forecast of short time series encountered in financial analysis of a small enterprize.
We described how a time series can be decomposed into a sequence of trend values and a …

… of soft computing techniques (especially fuzzy sets, artificial neural network, and evolutionary
computing) in time series forecasting. … problems of time series forecasting in depth, starting …