Download or read book A Unified Approach to Volatility Estimation in the Presence of Both Rounding and Random Market Microstructure Noise written by Yingying Li and published by . This book was released on 2017 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: Widely used volatility estimation methods mainly consider one of the following two simple microstructure noise models: random additive noise on log prices, or pure rounding errors. Apparently in real data these two types of noise co-exist. In this paper, we discover a common feature of these two types of noise and propose a unified volatility estimation approach in the presence of both rounding and random noise. Our data-driven method enjoys superior properties in terms of bias and convergence rate. We establish feasible central limit theorems and show their superior performance via simulations. Empirical studies show clear advantages of our method when applied to both stocks data and currency exchange data.
Download or read book Volatility Estimation in the Presence of Rounding and Random Market Microstructure Noise written by Yichu Li and published by . This book was released on 2011 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book On the Estimation of Integrated Volatility in the Presence of Jumps and Microstructure Noise written by Christian T. Brownlees and published by . This book was released on 2019 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is concerned with the problem of the estimation of the integrated volatility of log-prices based on high frequency data when both price jumps and market microstructure noise are present. We begin by providing a survey of the leading estimators introduced in the literature to tackle volatility estimation in this setting. We then introduce novel integrated volatility estimators based on a truncation technique and establish their properties. Finally, we carry out a simulation study to compare the performance of the di erent estimation techniques.
Download or read book Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise written by Yacine Aït-Sahalia and published by . This book was released on 2005 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for that purpose will work even when the noise exhibits time series dependence, analyze in that context a refinement of this approach based on multiple time scales, and compare empirically our different estimators to the standard realized volatility.
Download or read book Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise written by Yacine Ait-Sahalia and published by . This book was released on 2010 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration. We show that combining two time scales for that purpose will work even when the noise exhibits time series dependence, analyze in that context a refinement of this approach based on multiple time scales, and compare empirically our different estimators to the standard realized volatility.
Download or read book Financial Mathematics Volatility and Covariance Modelling written by Julien Chevallier and published by Routledge. This book was released on 2019-06-28 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. Financial Mathematics, Volatility and Covariance Modelling: Volume 2 provides a key repository on the current state of knowledge, the latest debates and recent literature on financial mathematics, volatility and covariance modelling. The first section is devoted to mathematical finance, stochastic modelling and control optimization. Chapters explore the recent financial crisis, the increase of uncertainty and volatility, and propose an alternative approach to deal with these issues. The second section covers financial volatility and covariance modelling and explores proposals for dealing with recent developments in financial econometrics This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.
Download or read book Essays in Volatility Estimation Based on High Frequency Data written by Yucheng Sun and published by . This book was released on 2017 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on high-frequency price data, this thesis focuses on estimating the realized covariance and the integrated volatility of asset prices, and applying volatility estimation to price jump detection. The first chapter uses the LASSO procedure to regularize some estimators of high dimensional realized covariance matrices. We establish theoretical properties of the regularized estimators that show its estimation precision and the probability that they correctly reveal the network structure of the assets. The second chapter proposes a novel estimator of the integrated volatility which is the quadratic variation of the continuous part in the price process. This estimator is obtained by truncating the two-scales realized variance estimator. We show its consistency in the presence of market microstructure noise and finite or infinite activity jumps in the price process. The third chapter employs this estimator to design a test to explore the existence of price jumps with noisy price data.
Download or read book Estimation of Asset Volatility and Correlation Over Market Microstructure Noise in High Frequency Data written by Roman Yevstihnyeyev and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate measurement of asset return volatility and correlation is an important problem in financial econometrics. The presence of market microstructure noise in high-frequency data complicates such estimations. This study extends a prior application of a model-based volatility estimator with autocorrelated market microstructure noise to estimation of correlation. The model is applied to a high-frequency dataset including a stock and an index, and the results are compared to some existing models. This study supports previous findings that including an autocorrelation factor produces an estimator potentially less vulnerable to market microstructure noise, and finds that the same is true about the extended correlation estimator that is introduced here.
Download or read book High Frequency Volatility of Volatility Estimation Free from Spot Volatility Estimates written by Simona Sanfelici and published by . This book was released on 2015 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: We define a new consistent estimator of the integrated volatility of volatility based only on a pre-estimation of the Fourier coefficients of the volatility process. We investigate the finite sample properties of the estimator in the presence of noise contamination by computing the bias of the estimator due to noise and showing that it vanishes as the number of observations increases, under suitable assumptions. In both simulated and empirical studies, the performance of the Fourier estimator with high frequency data is investigated and it is shown that the proposed estimator of volatility of volatility is easily implementable, computationally stable and even robust to market microstructure noise.
Download or read book Microstructure Noise written by Aristides Romero and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As a basic principle in statistics, a larger sample size is preferred whenever possible. Nonetheless, in the financial world, especially equities and currencies trading, including all available data poses great challenges due to the noise present in the volatility estimation. In his paper I examine the Two Time Scales Realized Volatility estimator by Zhang, Mykland, and Ait-Sahalia (2005b) and I find that it not only provides a more efficient estimator than a basic estimator of the integrated volatility of returns, but it also consistently estimates the microstructure noise present in the latent efficient return process. I find that by using this approach, it is possible to compare the efficiency of the prices of securities with lower transaction costs traded against those with higher transactions costs.
Download or read book A Tale of Two Time Scales written by Lan Zhang and published by . This book was released on 2010 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is a common practice in finance to estimate volatility from the sum of frequently-sampled squared returns. However market microstructure poses challenges to this estimation approach, as evidenced by recent empirical studies in finance. This work attempts to lay out theoretical grounds that reconcile continuous-time modeling and discrete-time samples. We propose an estimation approach that takes advantage of the rich sources in tick-by-tick data while preserving the continuous-time assumption on the underlying returns. Under our framework, it becomes clear why and where the usual' volatility estimator fails when the returns are sampled at the highest frequency.
Download or read book Quasi Maximum Likelihood Estimation of Volatility with High Frequency Data written by Dacheng Xiu and published by . This book was released on 2010 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates the properties of the well-known maximum likelihood estimator in the presence of stochastic volatility and market microstructure noise, by extending the classic asymptotic results of quasi-maximum likelihood estimation. When trying to estimate the integrated volatility and the variance of noise, this parametric approach remains consistent, efficient and robust as a quasi-estimator under misspecified assumptions. Moreover, it shares the model-free feature with nonparametric alternatives, for instance realized kernels, while being advantageous over them in terms of finite sample performance. In light of quadratic representation, this estimator behaves like an iterative exponential realized kernel asymptotically. Comparisons with a variety of implementations of the Tukey-Hanning 2 kernel are provided using Monte Carlo simulations, and an empirical study with the Euro/US Dollar future illustrates its application in practice.
Download or read book Fourier Malliavin Volatility Estimation written by Maria Elvira Mancino and published by Springer. This book was released on 2017-03-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a user-friendly presentation of the main theoretical properties of the Fourier-Malliavin volatility estimation, allowing the readers to experience the potential of the approach and its application in various financial settings. Readers are given examples and instruments to implement this methodology in various financial settings and applications of real-life data. A detailed bibliographic reference is included to permit an in-depth study.
Download or read book Volatility Estimation and Jump Testing Via Realized Information Variation written by Weiyi Liu and published by . This book was released on 2016 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: We put forward two jump-robust estimators of integrated volatility, namely realized information variation (RIV) and realized information power variation (RIPV). The "information" here refers to the difference between two-grid of ranges in high-frequency intervals, which preserves continuous variation and eliminates jump variation asymptotically. We give several probabilistic laws to show that RIV is much more efficient than most of the other estimators, e.g. 8.87 times more efficient than bi-power variation, and RIPV has a fast jump convergence rate at Op(1/n), while the others are usually Op(1/sqrt(n)) in the literature. We also extend our results to integrated quarticity and higher-order variation estimation, and then propose a new jump testing method. Simulation studies provide extensive evidence on the finite sample properties of our estimators and tests, comparing with alternative methods. The simulations support our theoretical results on volatility estimation and demonstrate that our jump testing method has much lower type I error for smaller sample frequencies, or in the presence of microstructure noise.
Download or read book Efficient Estimation of Integrated Volatility Incorporating Trading Information written by Yingying Li and published by . This book was released on 2016 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider a setting where market microstructure noise is a parametric function of trading information, possibly with a remaining noise component. Assuming that the remaining noise is $O_p(1/ sqrt{n})$, allowing irregular times and jumps, we show that we can estimate the parameters at rate $n$, and propose a volatility estimator which enjoys $ sqrt{n}$ convergence rate. Simulation studies show that our method performs well even with model misspecification and rounding. Empirical studies demonstrate the practical relevance and advantages of our method. Furthermore, we find that a simple model can account for a high percentage of the total variation of the microstructure noise.
Download or read book A Combined Filtering Approach to High Frequency Volatility Estimation with Mixed Type Microstructure Noises written by Yinfen Tang and published by . This book was released on 2018 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper introduces a solution that combines the Kalman and particle fi lters to the challenging problem of estimating integrated volatility using high-frequency data where the underlying prices are perturbed by a mixture of random noise and price discreteness. An explanation is presented of how the proposed combined filtering approach is able to correct for bias due to this mixed-type microstructure effect. Simulation and empirical studies on the tick-by-tick trade price data for four US stocks in the year 2009 show that our method has clear advantages over existing high-frequency volatility estimation methods.
Download or read book High Frequency Volatility Estimation and the Relative Importance of Market Microstructure Variables written by Yifan Li and published by . This book was released on 2018 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we examine the relative importance of trading volume, bid-ask spread, order flow, order imbalance, total quote depth, quote depth difference and trading intensity for high-frequency volatility estimation. By using a best subset regression approach, we fi nd that contemporaneous trading intensity and order flow contains the most important information about volatility estimation in general, but the rankings of the importance of the market microstructure (MMS) variables vary between securities. Using a Lognormal Log-Autoregressive Conditional Duration (LL-ACD) model, we show that the inclusion of MMS covariates signi ffcantly improves the goodness-of- fit of the model. Furthermore, we show that the inclusion of MMS covariates in the LL-ACD model leads to substantial improvements in the quality of volatility estimates, both on a daily and an intraday level.
