Measuring volatility with the realized range

By M. Martens, Dick Van Dijk. 2006

339 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b5ca584fe9e2047eea7d7719e1483370f27c760c

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Citations in the corpus

Optimal combinations of realised volatility estimators (2009, background): “Our fifth type of realised measure is the “realised range-based variance” (R RV ) of Christensen and Podolskij (2007) and Martens and van Dijk (2007) .”
Realized range-based estimation of integrated variance (2007, neutral): “9 In an independent, concurrent paper, Martens & van Dijk (2007) have studied RRV for homoscedastic diﬀusions, but they do not derive a general asymptotic theory.”
Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes (2015, positive): “The approach of Patton (2011a) allows for a variety of metrics, including the MSE and QLIKE loss functions.”
Volatility Forecast Comparison Using Imperfect Volatility Proxies (2006, neutral): “2 The high/low range and realised volatility, see Parkinson (1980) and Andersen et al.”
Forecasting the realized range-based volatility using dynamic model averaging approach (2017, methodology): “Using the extreme value method of intra-day return by the high-low range, Martin and Dick (2007) provide a more efficient measure called the realized range-based volatility (RRV), which uses the high-low range instead of the squared return.”
Nonparametric regression for locally stationary time series (2012, neutral): “[1], and Martens & van Dijk [21].”
Variation, jumps, market frictions and high frequency data in financial econometrics (2005, positive): “In independent work, Christensen and Podolskij (2005) and Martens and van Dijk (2005) have studied the realised range process.”
Forecasting time-varying covariance with a range-based dynamic conditional correlation model (2009, background): “Many insightful studies have provided powerful evidence including Parkinson (1980), Garman and Klass (1980), Wiggins (1991), Rogers and Satchell (1991), Kunitomo (1992) and, more recently, Gallant et al. (1999), Yang and Zhang (2000), Alizadeh et al. (2002), Brandt and Jones (2006), Chou (2005, 2006”
Comparison of Volatility Measures: A Risk Management Perspective (2010, positive): “Early theoretical and empirical justification of such an approach can be found, for example, inMüller et al. (1997), who suggest the presence of a short- and a long-term component as a results of the interactions of different agentswith different time-horizons in the financialmarkets: the long-term ”