Forecasting Financial Market Volatility: A Review

By Clive W. J. Granger, Ser-Huang Poon. 2001

129 citations recorded by the source corpus.

Subfields: Demography, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/f2fe9feff66ec66db3211adbc737a8de0a284a12

How researchers see this paper

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

In Demography

1. Haim Shalit
2. Eric Zivot
3. Robert F. Engle
4. Stavros Degiannakis *
5. Evdokia Xekalaki
6. Rami Yosef
7. Dima Alberg

In Economics and Econometrics

1. Stavros Degiannakis *
2. Evdokia Xekalaki
3. George Filis
4. Eric Zivot
5. Haim Shalit
6. Robert F. Engle
7. Rami Yosef
8. Dima Alberg

In Finance

1. Stavros Degiannakis *
2. Evdokia Xekalaki
3. Eric Zivot
4. Haim Shalit
5. Robert F. Engle
6. Rami Yosef
7. Dima Alberg
8. George Filis

Citations in the corpus

• Estimating stock market volatility using asymmetric GARCH models (2008, methodology): “The forecasting ability of GARCH models has been comprehensively discussed by Poon and Granger (2003). We use the G@RCH 2.”
• Autoregressive Conditional Heteroscedasticity (ARCH) Models: A Review (2004, background): “Recently, Poon and Granger (2001) conducted a comparative review based on the forecasting performance of ARCH, implied volatility, and historical volatility models.”
• Practical Issues in the Analysis of Univariate GARCH Models (2009, background): “There are also several comprehensive surveys that focus on the forecasting performance of GARCH models including [78], [77], and [3].”
• New frontiers for arch models (2002, background): “See for example Granger and Poon(2001) for a survey.”