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In this paper, we consider the one-term Edgeworth expansion for finite population L-statistics. We provide an explicit formula for the Edgeworth correction term and give sufficient conditions for the validity of the expansion which are…

Statistics Theory · Mathematics 2012-04-04 Andrius Čiginas

In this paper, we consider the sphericity test for a one-sample problem under high-dimensional two-step monotone incomplete data. Existing asymptotic expansions for the null distributions of the likelihood ratio test (LRT) statistic and…

Statistics Theory · Mathematics 2026-04-01 Tetsuya Sato , Tomoyuki Nakagawa

Edgeworth expansion provides higher-order corrections to the normal approximation for a probability distribution. The classical proof of Edgeworth expansion is via characteristic functions. As a powerful method for distributional…

Probability · Mathematics 2022-11-09 Xiao Fang , Song-Hao Liu

We study the distribution of a general class of asymptoticallylinear statistics which are symmetric functions of $N$ independent observations. The distribution functions of these statistics are approximated by an Edgeworth expansion with a…

Statistics Theory · Mathematics 2021-02-09 Friedrich Götze , Mindaugas Bloznelis

This paper provides a finite sample bound for the error term in the Edgeworth expansion for a sum of independent, potentially discrete, nonlattice random vectors, using a uniform-in-$P$ version of the weaker Cram\'{e}r condition in Angst…

Statistics Theory · Mathematics 2019-08-14 Kyungchul Song

We study a Edgeworth-type refinement of the central limit theorem for the discretizacion error of It\^o integrals. Towards this end, we introduce a new approach, based on the anticipating It\^o formula. This alternative technique allows us…

Probability · Mathematics 2018-02-22 Elisa Alòs , Masaaki Fukasawa

The usage of a spot volatility estimate based on a volatility decomposition in a time-changed price-model according to the trading times is investigated. In this model clock-time volatility splits up into the product of tick-time volatility…

Probability · Mathematics 2016-05-10 Rainer Dahlhaus , Sophon Tunyavetchakit

We study the asymptotic normality of two feasible estimators of the integrated volatility of volatility based on the Fourier methodology, which does not require the pre-estimation of the spot volatility. We show that the bias-corrected…

Statistics Theory · Mathematics 2022-09-07 Giacomo Toscano , Giulia Livieri , Maria Elvira Mancino , Stefano Marmi

The implied volatility skew has received relatively little attention in the literature on short-term asymptotics for financial models with jumps, despite its importance in model selection and calibration. We rectify this by providing…

Mathematical Finance · Quantitative Finance 2015-12-15 José E. Figueroa-López , Sveinn Ólafsson

This paper is concerned with the estimation of the volatility process in a stochastic volatility model of the following form: $dX_t=a_tdt+\sigma_tdW_t$, where $X$ denotes the log-price and $\sigma$ is a c\`adl\`ag semi-martingale. In the…

Statistical Finance · Quantitative Finance 2015-03-13 A. Alvarez , F. Panloup , M. Pontier , N. Savy

We develop a higher-order asymptotic analysis for the semi-hard triplet loss using the Edgeworth expansion. It is known that this loss function enforces that embeddings of similar samples are close while those of dissimilar samples are…

Machine Learning · Statistics 2025-03-18 Masanari Kimura

We examine whether model-based spot volatility estimators extracted from traded options data enhance the predictive power of the Heterogeneous Autoregressive (HAR) model for realized volatility. Specifically, we infer spot volatility under…

Risk Management · Quantitative Finance 2026-04-13 Zheqi Fan , Meng Melody Wang , Yifan Ye

This paper studies higher-order inference properties of nonparametric local polynomial regression methods under random sampling. We prove Edgeworth expansions for $t$ statistics and coverage error expansions for interval estimators that (i)…

Econometrics · Economics 2021-07-26 Sebastian Calonico , Matias D. Cattaneo , Max H. Farrell

Volatility estimation is a central problem in financial econometrics, but becomes particularly challenging when jump activity is high, a phenomenon observed empirically in highly traded financial securities. In this paper, we revisit the…

Econometrics · Economics 2026-05-13 B. Cooper Boniece , José E. Figueroa-López , Tianwei Zhou

Consider a homogeneous Poisson process in $\mathbb{R}^d$, $d \ge 1$. Let $R_1 < R_2 < \dots$ be the distances of the points from the origin, and let $S = R_1^{-\gamma} + R_2^{-\gamma} + \dots$, where $\gamma > d$ is a parameter. Let…

Probability · Mathematics 2019-12-17 Antal A. Járai

In this article we generalize the classical Edgeworth expansion for the probability density function (PDF) of sums of a finite number of symmetric independent identically distributed random variables with a finite variance to sums of…

Statistical Mechanics · Physics 2015-05-20 Netanel Hazut , Shlomi Medalion , David A. Kessler , Eli Barkai

We propose new nonparametric estimators of the integrated volatility of an It\^{o} semimartingale observed at discrete times on a fixed time interval with mesh of the observation grid shrinking to zero. The proposed estimators achieve the…

Statistics Theory · Mathematics 2014-05-30 Jean Jacod , Viktor Todorov

In this paper we study the Fourier estimator of Malliavin and Mancino for the spot volatility. We establish the convergence of the trigonometric polynomial to the volatility's path in a setting that includes the following aspects. First,…

Computational Finance · Quantitative Finance 2026-01-15 L. J. Espinosa González , Erick Treviño Aguilar

There are several approaches to modeling and forecasting time series as applied to prices of commodities and financial assets. One of the approaches is to model the price as a non-stationary time series process with heteroscedastic…

Statistical Finance · Quantitative Finance 2024-07-01 Andrei Renatovich Batyrov

In this paper, we derive a valid Edgeworth expansions for the Bessel corrected empirical variance when data are generated by a strongly mixing process whose distribution can be arbitrarily. The constraint of strongly mixing process makes…

Statistics Theory · Mathematics 2018-09-19 Eric Benhamou