Robust estimation of integrated variance and quarticity under flat price and no trading bias

This is the accepted version of the paper.This version of the publication may differ from the final published version. are not only consistent, but also scarcely plagued by small-sample bias. To this purpose, we introduce the concept of threshold bipower variation, which is based on the joint use of bipower variation and threshold estimation. We show that its generalization (threshold multipower variation) admits a feasible central limit theorem in the presence of jumps and provides less biased estimates, with respect to the standard multipower variation, of the continuous quadratic variation in finite samples. We further provide a new test for jump detection which has substantially more power than tests based on multipower variation. Empirical analysis (on the S&P500 index, individual stocks and US bond yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods following the occurrence of a jump. Permanent repository link

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“…Further analysis and different possible corrections for this problem are discussed in Schulz (2010).…”

Section: Bond Data and The No-trade Biasmentioning

confidence: 99%

Threshold bipower variation and the impact of jumps on volatility forecasting

Corsi

Pirino

Renò

2010

Journal of Econometrics

499

285

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“…[33,34]. Schulz [35] proposes a robust approach in the case of flat prices and zero-returns in the univariate framework. Ideas considering how to deal with zero-returns in a multivariate setting are welcome.…”

Section: Implications and Conclusionmentioning

confidence: 99%

Covariance estimation using high-frequency data: Analysis of Nord Pool electricity forward data

Lien¹,

Haugom²,

Westgaard³

et al. 2010

2010 7th International Conference on the European Energy Market

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Abstract:The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM (Capital Asset Pricing Model betas), derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution (both distributional properties and temporal dependencies) of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.

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Estimation of quarticity with high-frequency data

Mancino

Sanfelici

2012

Quantitative Finance

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We propose a new methodology based on Fourier analysis to estimate the fourth power of volatility function (spot quarticity) and, as a byproduct, the integrated function. We prove consistency of the proposed estimator of integrated quarticity. Further we analyze its efficiency in the presence of microstructure noise, both from a theoretical and empirical viewpoint. Extensions to higher powers of volatility and to the multivariate case are also discussed.

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Robust estimation of integrated variance and quarticity under flat price and no trading bias

Cited by 4 publications

References 26 publications

Threshold bipower variation and the impact of jumps on volatility forecasting

Threshold bipower variation and the impact of jumps on volatility forecasting

Covariance estimation using high-frequency data: Analysis of Nord Pool electricity forward data

Estimation of quarticity with high-frequency data

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