Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements

By M. Martens, Dick Van Dijk, M. D. Pooter. 2009

157 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/675a1790fff146cde8542ddab5d95d53abd2d1ce

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. M. Nieto
2. Esther Ruiz

In Finance

1. M. Nieto
2. Esther Ruiz

Citations in the corpus

• Optimally Harnessing Inter-Day and Intra-Day Information for Daily Value-at-Risk Prediction (2013, unknown): “In this vein, our paper builds upon the studies by Giot and Laurent (2004), Angelidis and Degiannakis (2008) and Martens et al. (2009) on stock indices, Clements et al. (2008) on exchange rates and Brownlees and Gallo (2010) on specific NYSE stocks.”
• Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics (2016, unknown): “These are not solely related to the realized volatility series as such (as for instance in Martens et al., 2009, Table 2) but also to how realized volatility is modeled.”
• Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling (2012, unknown): “…well known that volatility tends to increase more after a negative shock than after a positive shock of the same magnitude see e.g. Christie (1982); Campbell and Hentschel (1992); Glosten et al. (1989) and more recently Bollerslev et al. (2006), Bollerslev et al. (2009) and Martens et al. (2009).”
• Forecasting Volatility in Financial Markets (2010, background): “Various methods from linear to nonlinear have been developed and extensively applied in practice to describe the stock return volatility [1-4].”
• Frontiers in VaR forecasting and backtesting (2016, background): “…also important as it is routinely implemented as an empirical check for alternative models to forecast conditional means and variances; see, for example, Asai and McAleer (2008), Martens et al. (2009), Wilhelmsson (2009), Grigoletto and Lisi (2009) and Brownlees and Gallo (2010) among many others.”