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A hybrid fuzzy GJR-GARCH modeling approach for stock market volatility forecasting

Maciel, Leandro - In: Advances in financial risk management : corporates, …, (pp. 253-283). 2013

Persistent link: https://www.econbiz.de/10010213079

Evaluating volatility using an ANFIS model for financial time series prediction

Orozco-Castañeda, Johanna M.; Alzate-Vargas, Sebastián; … - In: Risks : open access journal 12 (2024) 10, pp. 1-15

patterns from past data and achieve an understanding of the future behavior of the price and its volatility. The proposed ARIMA … the diebold and Mariano test to compare the accuracy of the two volatility forecasts. The results revealed that each … volatility model focuses on different aspects of the data dynamics. The ANFIS model, while effective in certain scenarios, may …

Persistent link: https://www.econbiz.de/10015130356

Evolving fuzzy-GARCH approach for financial volatility modeling and forecasting

Maciel, Leandro; Gomide, Fernando; Ballini, Rosangela - In: Computational economics 48 (2016) 3, pp. 379-398

Persistent link: https://www.econbiz.de/10011712504

Modelling long memory dependence structure using FIGARCH-copula approach : evidence from major Asian stock markets

Gupta, Pankaj Kumar; Mittal, Prabhat - In: Global business & economics review 30 (2024) 1, pp. 56-71

Persistent link: https://www.econbiz.de/10014490993

Predicting exchange rate volatility in Brazil : an approach using quantile autoregression

Viola, Alessandra Pasqualina; Klotzle, Marcelo Cabus; … - 2017

Persistent link: https://www.econbiz.de/10011944952

Comparison of GARCH and ANN model for forecasting volatility : Evidence based on Indian stock markets

Shaik, Muneer; Sejpal, Aditya - In: The journal of prediction markets 14 (2020) 2, pp. 103-121

Persistent link: https://www.econbiz.de/10012667736

Volatility forecasting using hybrid GARCH Neural Network models : the case of the Italian stock market

Kartsonakis Mademlis, Dimitrios; Dritsakis, Nikolaos - In: International journal of economics and financial issues … 11 (2021) 1, pp. 49-60

Persistent link: https://www.econbiz.de/10012436893

Which model performs better while forecasting stock market volatility? : answer for Dhaka Stock Exchange (DSE)

Abdullah, S. M.; Kabir, Mohammod Akbar; Jahan, Kawsar; … - In: Theoretical economics letters 8 (2018) 14, pp. 3203-3222

Persistent link: https://www.econbiz.de/10011955144

Predicting stock market volatility using MODWT with HyFIS and FS.HGD models

Alenezy, Abdullah H.; Mohd Tahir Ismail; Sadam Al-Wadi; … - In: Risks : open access journal 11 (2023) 7, pp. 1-16

We enhance the precision of predicting daily stock market price volatility using the maximum overlapping discrete …

Persistent link: https://www.econbiz.de/10014335933

Cross-sectional return dispersion and stock market volatility : evidence from high-frequency data

Niu, Zibo; Demirer, Rıza; Suleman, Muhammad Tahir; … - In: Journal of forecasting 42 (2023) 6, pp. 1309-1328

Persistent link: https://www.econbiz.de/10014338888