Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation

Barndorff–Nielsen, Ole E.; Shephard, Neil

doi:10.1093/jjfinec/nbi022

Cited by 1,026 publications

(634 citation statements)

References 53 publications

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“…We prove the existence of the bipower variation process for a wide class of continuous semimartingales (extending the results of [4] and [5]). We establish the CLT in a slightly more restricted setting.…”

Section: Introductionmentioning

confidence: 61%

“…This result is essentially taken from [4]. The assumption (H) could be weakened, of course, but probably not in any essential way.…”

Section: Hypothesis (H)mentioning

confidence: 98%

“…The bipower variation process of order (r, s) for Y , denoted by V (Y ; r, s) t , is the limit in probability, if it exists for all t ≥ 0, of V (Y ; r, s) n t . It has been introduced in [4] and [5], where it is shown that the bipower variation processes exist for all nonnegative indices r, s as soon as Y is a continuous semimartingale of "Itô type" with smooth enough coefficients. These papers also contain a version of the associated CLT under somewhat restrictive assumptions and when r = s = 1.…”

Section: Introductionmentioning

confidence: 99%

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A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales

Barndorff–Nielsen¹,

Graversen²,

Jacod³

et al. 2006

From Stochastic Calculus to Mathematical Finance

221

326

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Summary. Consider a semimartingale of the form Yt = Y0 + t 0 asds + t 0 σs− dWs, where a is a locally bounded predictable process and σ (the "volatility") is an adapted right-continuous process with left limits and W is a Brownian motion. We consider the realised bipower variation processwhere r and s are nonnegative reals with r + s > 0. We prove that V (Y ; r, s) n t converges locally uniformly in time, in probability, to a limiting process V (Y ; r, s)t (the "bipower variation process"). If further σ is a possibly discontinuous semimartingale driven by a Brownian motion which may be correlated with W and by a Poisson random measure, we prove that √ n (V (Y ; r, s) n − V (Y ; r, s)) converges in law to a process which is the stochastic integral with respect to some other Brownian motion W , which is independent of the driving terms of Y and σ. We also provide a multivariate version of these results, and a version in which the absolute powers are replaced by smooth enough functions.

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Section: Introductionmentioning

confidence: 61%

“…This result is essentially taken from [4]. The assumption (H) could be weakened, of course, but probably not in any essential way.…”

Section: Hypothesis (H)mentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales

Barndorff–Nielsen¹,

Graversen²,

Jacod³

et al. 2006

From Stochastic Calculus to Mathematical Finance

221

326

View full text Add to dashboard Cite

show abstract

“…Since there is only one spread of each maturity available per day, we perform the bipower variation test on buckets of 21 daily spreads (approx. one month), which is a low observation frequency compared to Barndorff-Nielsen and Shephard (2006). In a simulation study (cf.…”

mentioning

confidence: 99%

The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk

Schneider¹,

Sögner²,

Veža³

2010

J. Financ. Quant. Anal.

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A previous version of this paper was circulated as "Jumps and Recovery Rates Inferred from Corporate CDS Premia". We are thankful to FIRM@WU for access to their high-performance computing resources as well as friendly support, and to Dow Jones for providing us with complete ICB sector information. AbstractUsing an extensive cross-section of US corporate CDS this paper offers an economic understanding of implied loss given default (LGD) and jumps in default risk. We formulate and underpin empirical stylized facts about CDS spreads, which are then reproduced in our affine intensity-based jump-diffusion model. Implied LGD is well identified, with obligors possessing substantial tangible assets expected to recover more. Sudden increases in the default risk of investment-grade obligors are higher relative to speculative grade. The probability of structural migration to default is low for investment-grade and heavily regulated obligors because investors fear distress rather through rare but devastating events.

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“…Under the assumption of no jump and some other regularity conditions, Barndorff-Nielsen and Shephard (2006) provide the joint asymptotic distribution of the jump variation. 6 Using this theory, the contribution of the jump variation to the quadratic variation of 5 The Parzen kernel function is given by K(x) = 8 < :…”

mentioning

confidence: 99%

Coupling High-Frequency Data with Nonlinear Models in Multiple-Step-Ahead Forecasting of Energy Markets' Volatility

Baruník

Křehlík

2014

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: Terms of use: Documents inIn the past decade, the popularity of realized measures and various linear models for volatility forecasting has attracted attention in the literature on the price variability of energy markets. However, results that would guide practitioners to a specifc estimator and model when aiming for the best forecasting accuracy are missing. This paper contributes to the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using several popular high-frequency measures and forecasting models. To capture the complex patterns hidden to linear models commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with artificial neural networks as a forecasting tool. Forecasting performance is compared across models as well as realized measures of crude oil, heating oil, and natural gas volatility during three qualitatively distinct periods covering the precrisis period, recent global turmoil of markets in 2008, and the most recent post-crisis period. We conclude that coupling realized measures with arti_cial neural networks results in both statistical and economic gains, reducing the tendency to over-predict volatility uniformly during all tested periods. Our analysis favors the median realized volatility, as it delivers the best performance and is a computationally simple alternative for practitioners.

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Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation

Cited by 1,026 publications

References 53 publications

A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales

A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales

The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk

Coupling High-Frequency Data with Nonlinear Models in Multiple-Step-Ahead Forecasting of Energy Markets' Volatility

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