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Analysis and prediction of China stock market return based on BP neural network

Zhang, Yize - In: Internet finance and digital economy : advances in …, (pp. 739-753). 2024

Persistent link: https://www.econbiz.de/10014534672

Applying hybrid ARIMA-SGARCH in algorithmic investment strategies on S&P 500 Index

Nguyen Vo; Ślepaczuk, Robert - 2021

Persistent link: https://www.econbiz.de/10012816706

Predictive power of ARIMA models in forecasting equity returns : a sliding window method

Dong, Huijian; Guo, Xiaomin; Reichgelt, Han; Hu, Ruizhi - In: The journal of asset management 21 (2020) 6, pp. 549-566

Persistent link: https://www.econbiz.de/10012298733

A comparative study of static and iterative models of ARIMA and SVR to predict stock indices prices in developed and emerging economies

Beniwal, Mohit; Archana Singh; Kumar, Nand - In: International journal of applied management science : IJAMS 15 (2023) 4, pp. 352-371

Persistent link: https://www.econbiz.de/10014391724

Forecasting Indian financial markets using neural networks

Panda, Chakradhara - 2008

Persistent link: https://www.econbiz.de/10003752543

How Fama-MacBeth Can Go Wrong – And an Informative Solution

Khalaf, Lynda - 2011

We find that weak identification can lead to econometric problems with Fama-MacBeth regressions, including serious size distortions and biased point estimates. Two sources of weak identification are particularly important and have been little studied in the finance literature – small betas and...

Persistent link: https://www.econbiz.de/10013128509

Momentum, Reversals, and other Puzzles in Fama-MacBeth Cross-Sectional Regressions

Kamstra, Mark J. - 2017

The existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth...

Persistent link: https://www.econbiz.de/10012959272

Forecasting volatility in the Indian equity market using return and range-based models

Raju, Karthik; Rangaswamy, Saravanan - In: Applied economics 49 (2017) 49, pp. 5027-5039

Persistent link: https://www.econbiz.de/10011844848

Time-varying industry beta in Indian stock market and forecasting errors

Das, Sudipta; Barai, Parama - In: International journal of emerging markets 10 (2015) 3, pp. 521-534

Persistent link: https://www.econbiz.de/10011489295

Modeling and forecasting the volatility of NIFTY 50 using GARCH and RNN models

Mahajan, Vanshu; Thakan, Sunil; Malik, Aashish - In: Economies : open access journal 10 (2022) 5, pp. 1-20

, several scholars have lately been interested in forecasting stock market volatility. This study analyzed India VIX (NIFTY 50 …The stock market is constantly shifting and full of unknowns. In India in 2000, technological advancements led to … volatility index) to identify the behavior of the Indian stock market in terms of volatility and then evaluated the forecasting …

Persistent link: https://www.econbiz.de/10013199403

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