Threshold bipower variation and the impact of jumps on volatility forecasting

From MaRDI portal
Publication:737246

DOI10.1016/j.jeconom.2010.07.008zbMath1441.62656OpenAlexW3124336248MaRDI QIDQ737246

Roberto Renò, Fulvio Corsi, Davide Pirino

Publication date: 10 August 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://openaccess.city.ac.uk/id/eprint/4435/1/CorsiPirinoReno_TBV_sub2010.pdf




Related Items (80)

Forecasting stock market in high and low volatility periods: a modified multifractal volatility approachJumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movementsTesting long memory based on a discretely observed processOptimal portfolio allocation with volatility and co-jump risk that Markowitz would likeBias-optimal vol-of-vol estimation: the role of window overlappingIs the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessmentFinancial modelling, risk management of energy instruments and the role of cryptocurrenciesCollective synchronization and high frequency systemic instabilities in financial marketsNONPARAMETRIC STOCHASTIC VOLATILITYVolatility of volatility: estimation and tests based on noisy high frequency data with jumpsTests for structural breaks in memory parameters of long-memory heterogeneous autoregressive modelsManaging risk with a realized copula parameterDo we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities?Information content of liquidity and volatility measuresJump-robust volatility estimation using dynamic dual-domain integration methodDetection of jumps in financial time seriesVector error correction heterogeneous autoregressive forecast model of realized volatility and implied volatilityEstimation of the Hurst parameter in the simultaneous presence of jumps and noiseA generalized heterogeneous autoregressive model using market informationThe contribution of intraday jumps to forecasting the density of returnsAsymptotic properties for multipower variation of semimartingales and Gaussian integral processes with jumpsUncertainty and realized jumps in the pound-dollar exchange rate: evidence from over one century of dataForecasting volatility with time-varying coefficient regressionsJump‐robust testing of volatility functions in continuous time modelsAdaptive robust large volatility matrix estimation based on high-frequency financial dataVolatility measurement with pockets of extreme return persistenceUniform predictive inference for factor models with instrumental and idiosyncratic betasVolatility models for stylized facts of high‐frequency financial dataAsymptotic normality of Nadaraya–Waton kernel regression estimation for mixing high-frequency dataOvernight GARCH-Itô Volatility ModelsHow precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?Forecasting jump arrivals in stock prices: new attention-based network architecture using limit order book dataBias reduction in spot volatility estimation from optionsA factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errorsHigh-frequency volatility of volatility estimation free from spot volatility estimatesOptimally thresholded realized power variations for Lévy jump diffusion modelsThe VIX, the variance premium and stock market volatilityHigh-frequency jump tests: which test should we use?Central limit theorems for power variation of Gaussian integral processes with jumpsIDENTIFYING THE BROWNIAN COVARIATION FROM THE CO-JUMPS GIVEN DISCRETE OBSERVATIONSCojumps and asset allocation in international equity marketsDoes anything beat 5-minute RV? A comparison of realized measures across multiple asset classesOptimum thresholding using mean and conditional mean squared errorInference from high-frequency data: a subsampling approachTail Granger causalities and where to find them: extreme risk spillovers vs spurious linkagesTesting for jumps and jump intensity path dependenceJump-robust volatility estimation using nearest neighbor truncationTime-varying leverage effectsAn integrated heteroscedastic autoregressive model for forecasting realized volatilitiesForecasting the volatility of crude oil futures using intraday dataFluctuations of stock price model by statistical physics systemsOptimal iterative threshold-kernel estimation of jump diffusion processesNonparametric estimation of jump diffusion modelsJump robust two time scale covariance estimation and realized volatility budgetsModelling systemic price cojumps with Hawkes factor modelsAssessing the quality of volatility estimators via option pricingVolatility analysis with realized GARCH-Itô modelsForecasting the realized variance of the log-return of Korean won US dollar exchange rate addressing jumps both in stock-trading time and in overnightA realized volatility approach to option pricing with continuous and jump variance componentsEstimation for high-frequency data under parametric market microstructure noiseChasing volatility. A persistent multiplicative error model with jumpsTransaction activity and bitcoin realized volatilityA ROBUST NEIGHBORHOOD TRUNCATION APPROACH TO ESTIMATION OF INTEGRATED QUARTICITYDetecting price jumps in the presence of market microstructure noiseForecasting realised volatility using ARFIMA and HAR modelsVolatility Estimation and Jump Testing via Realized Information VariationAssessing the impact of jumps in an option pricing model: a gradient estimation approachIs the Variance Swap Rate Affine in the Spot Variance? Evidence from S&P500 DataSecond-order properties of thresholded realized power variations of FJA additive processesSpot volatility estimation using delta sequencesESTIMATION OF VOLATILITY FUNCTIONS IN JUMP DIFFUSIONS USING TRUNCATED BIPOWER INCREMENTSOn the estimation of integrated volatility in the presence of jumps and microstructure noiseJumps and oil futures volatility forecasting: a new insightEconometrics of co-jumps in high-frequency data with noiseThe Relationship between the Volatility of Returns and the Number of Jumps in Financial MarketsThe impact of jumps and leverage in forecasting covolatilitySmile from the past: a general option pricing framework with multiple volatility and leverage componentsEmpirical evidence on the importance of aggregation, asymmetry, and jumps for volatility predictionStochastic multifactor modeling of spot electricity pricesEstimation of quarticity with high-frequency data



Cites Work


This page was built for publication: Threshold bipower variation and the impact of jumps on volatility forecasting