Forecasting UK stock market volatility

By D. McMillan, A. Speight, Owain Apgwilym. 2000

120 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/20dd91d80cbc999c59abf37e8f8a56fbf27eb83c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. G. Ali
2. Haim Shalit
3. Stefan Trück
4. Kevin Liang
5. Rami Yosef
6. Dima Alberg

In Finance

1. G. Ali
2. Haim Shalit
3. Stefan Trück
4. Kevin Liang
5. Rami Yosef
6. Dima Alberg
7. Rafal Weron

Citations in the corpus

• Modelling and forecasting volatility in the gold market (2012, background): “McMillan et al. (2000) tested a set of ten volatility estimation models including random walk, moving average and GARCH models in forecasting UK stock market returns at different frequencies.”
• Estimating stock market volatility using asymmetric GARCH models (2008, methodology): “To overcome this drawback Bollerslev (1987), Baillie and Bollerslev (1989), and Beine et al. (2002) have used the Student’s t-distribution.”
• EGARCH, GJR-GARCH, TGARCH, AVGARCH, NGARCH, IGARCH and APARCH Models for Pathogens at Marine Recreational Sites (2013, background): “McMillan, Speight and Ap Gwilyn [11] had symmetric and asymmetric densities for the United Kingdom stock market.”