Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book

Bibinger, Markus; Neely, Christopher J.; Winkelmann, Lars

doi:10.1016/j.jeconom.2019.01.001

Cited by 14 publications

(9 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(W t , B t ) is a twodimensional Brownian motion with leverage d[W, B] t = 0.2 dt. The stochastic volatility component has several realistic features and the simulated model is in line with recent literature, see [6] and references therein. Observations with lower-bounded, one-sided microstructure noise are generated by with exponentially distributed noise, i iid ∼ Exp(η), with η = 10,000.…”

Section: Simulation Study Of Estimatorssupporting

confidence: 77%

“…Observations with lower-bounded, one-sided microstructure noise are generated by with exponentially distributed noise, i iid ∼ Exp(η), with η = 10,000. The noise variance is then rather small, but this is in line with stylized facts of real NASDAQ data as, for instance, those analysed in [6]. 1 The black line in Figure 2 shows a fixed path of the squared volatility.…”

Section: Simulation Study Of Estimatorssupporting

confidence: 70%

“…Inequality (2) is less restrictive than α-Hölder continuity, since it does not rule out volatility jumps. This is important as empirical evidence for volatility jumps, in particular simultaneous price and volatility jumps, has been reported for intraday high-frequency financial data, see, for instance, [22] and [6]. The presented theory is moreover for general stochastic volatilities, allowing as well for rough volatility.…”

Section: Model With Lower-bounded One-sided Noise and Assumptionsmentioning

confidence: 62%

See 2 more Smart Citations

Inference on the intraday spot volatility from high-frequency order prices with irregular microstructure noise

Bibinger¹

2023

Preprint

View full text Add to dashboard Cite

We consider estimation of the spot volatility in a stochastic boundary model with one-sided microstructure noise for high-frequency limit order prices. Based on discrete, noisy observations of an Itô semimartingale with jumps and general stochastic volatility, we present a simple and explicit estimator using local order statistics. We establish consistency and stable central limit theorems as asymptotic properties. The asymptotic analysis builds upon an expansion of tail probabilities for the order statistics based on a generalized arcsine law. In order to use the involved distribution of local order statistics for a bias correction, an efficient numerical algorithm is developed. We demonstrate the finite-sample performance of the estimation in a Monte Carlo simulation.

show abstract

Section: Simulation Study Of Estimatorssupporting

confidence: 77%

Section: Simulation Study Of Estimatorssupporting

confidence: 70%

Section: Model With Lower-bounded One-sided Noise and Assumptionsmentioning

confidence: 62%

See 1 more Smart Citation

Inference on the intraday spot volatility from high-frequency order prices with irregular microstructure noise

Bibinger¹

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Curato (2019) presented the non‐parameter estimator of leverage effect via Fourier transformation. Bibinger et al (2019) explored the non‐continuous leverage effect in 320 NASDAQ corporations.…”

Section: Introductionmentioning

confidence: 99%

A new volatility model: GQARCH‐ItÔ model

Yuan

Sun

Lu³

et al. 2021

Journal Time Series Analysis

View full text Add to dashboard Cite

Volatility asymmetry is a hot topic in high-frequency financial market. This article proposes a new econometric model, which could describe volatility asymmetry based on high-frequency data and low-frequency data. After providing the quasi-maximum likelihood estimators for the parameters, we establish their asymptotic properties. We also conduct a series of simulation studies to check the finite sample performance and volatility forecasting performance of the proposed model and method. And a real data example is demonstrated that the new model has more substantial volatility prediction power than GARCH-Itô model in the literature.

show abstract

“…Curato (2019) presented the non-parameter estimator of leverage effect via Fourier transformation. Bibinger et al (2019) explored the non-continuous leverage effect in 320 NASDAQ corporations.…”

Section: Introductionmentioning

confidence: 99%

A New Volatility Model: GQARCH-Ito Model

Yuan¹,

Zhou²,

Lu³

et al. 2020

Preprint

View full text Add to dashboard Cite

Volatility asymmetry is a hot topic in high-frequency financial market. In this paper, we propose a new econometric model, which could describe volatility asymmetry based on high-frequency historical data and low-frequency historical data. After providing the quasi-maximum likelihood estimators for the parameters, we establish their asymptotic properties. We also conduct a series of simulation studies to check the finite sample performance and volatility forecasting performance of the proposed methodologies. And an empirical application is demonstrated that the new model has stronger volatility prediction power than GARCH-It\^{o} model in the literature.

show abstract

Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book

Cited by 14 publications

References 40 publications

Inference on the intraday spot volatility from high-frequency order prices with irregular microstructure noise

Inference on the intraday spot volatility from high-frequency order prices with irregular microstructure noise

A new volatility model: GQARCH‐ItÔ model

A New Volatility Model: GQARCH-Ito Model

Contact Info

Product

Resources

About