A Literature Review on the Model of EGARCH-MIDAS, LMM, GBM for Stock Market Prediction
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0523-8_110
Reference14 articles.
1. Harvey, A.C.: Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series, vol. 1. Cambridge University Press, Cambridge (2013)
2. Engle, R.F., Kroner, K.F.: Multivariate simultaneous generalized ARCH. Economet. Theor. 11(1), 122–150 (1995)
3. Islam, M.R., Nguyen, N.: Comparison of financial models for stock price prediction. J. Risk Financ. Manage. 13(8), 181 (2020). https://doi.org/10.3390/jrfm13080181
4. Engle, R.F., Rangel, J.G.: The spline GARCH model for low-frequency volatility and its global macroeconomic causes. Rev. Financ. Stud. 21(3), 1187–1222 (2008). https://doi.org/10.1093/rfs/hhn015
5. Liu, L., Ma, F., Zeng, Q., Zhang, Y.: Forecasting the aggregate stock market volatility in a data-rich world. Appl. Econ. 52(32), 3448–3463 (2020)
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