Download or read book Rejoinder to Comments on Realized Variance and Market Microstructure Noise written by Peter Reinhard Hansen and published by . This book was released on 2006 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: This rejoinder clarifies issues related to the features of market microstructure noise. Specifically, we show that pre-processing of high-frequency data is very useful for the estimation of quadratic variation. We also document a strong relationship between quadratic variation and the number of transactions.
Download or read book Comments on realized Variance and Market Microstructure Noise by Peter R Hansen and Asger Lund written by P. C. B. Phillips and published by . This book was released on 2005 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agrees with the thrust of Hansen and Lund's message concerning the complexity induced by microstructure noise. In particular, the authors agree that noise is time dependent and correlated with the efficient price and that microstructure noise cannot be accomodated by simple specifications.
Download or read book Realized Variance and Market Microstructure Noise written by Peter Reinhard Hansen and published by . This book was released on 2005 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of marketmicrostructure noise and that a simple kernel-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise is time-dependent and correlated with increments in the efficient price. This has important implications for volatility estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient price.
Download or read book Bias correcting the Realized Range based Variance in the Presence of Market Microstructure Noise written by Kim Christensen and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Missing Data Methods written by David M. Drukker and published by Emerald Group Publishing. This book was released on 2011-11-30 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part of the "Advances in Econometrics" series, this title contains chapters covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; and, Consistent Estimation and Orthogonality.
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 Decimalization Realized Volatility and Market Microstructure Noise written by Tommi A. Vuorenmaa and published by . This book was released on 2011 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper carefully examines the effect of decimalization on volatility and market microstructure noise. We apply several nonparametric estimators in order to accurately measure volatility and market microstructure noise variance before and after the final stage of decimalization which, on the NYSE, took place in January, 2001. We findn that decimalization decreased observed volatility by decreasing noise variance and, consequently, increased the significance of the true signal especially in trade price data for the highly active Dow Jones stocks. This study also reveals some differences between volatility and noise variance estimators' capability to handle changes in tick size and strategic order placing that are relevant in the evaluation of the decimalization effects. The ability of the realized kernel estimator to adapt to more complex data dependency than the traditional realized volatility estimator is useful. The two-scale and multi-scale realized volatility estimates turn out to be more variable especially with midquote data where a couple of outlying dates affect their volatility estimates and consequently the test results in a significant way.
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 Big Data written by Kuan-Ching Li and published by CRC Press. This book was released on 2015-02-23 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre
Download or read book Bootstrapping Pre averaged Realized Volatility Under Market Microstructure Noise written by Ulrich Hounyo and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 When is Noise Not Noise A Microstructure Estimate of Realized Volatility written by Zheng Sun and published by . This book was released on 2008 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies the joint distribution of tick by tick returns and durations between trades. Returns are decomposed into changes in full information prices and microstructure noise, but the noise is modeled in accordance with various models of market microstructure allowing rich correlation structures both with the efficient price and over time. The full information price has time varying volatility which depends upon the arrival time of trades. The paper aims at three contributions: First, the noise is modeled to allow asymmetric information, inventory and order processing costs, and delayed quote setting. Second, the response to the trade arrival times allows trade durations to be informative on future volatility. Third, the estimated state space models can act as a laboratory to examine various non-parametric approaches to realized volatility estimation. Both simulated and actual data can be compared across methods and the accuracy and efficiency assessed as long as the parameteric model is viewed as a sufficiently accurate representation. We apply the above model to 10 NYSE stock transactions data series with varying transaction rates. It appears that contemporaneous duration has little effect on the volatility per trade after conditioning on the past, which means average per second volatility is inversely related to the duration between trades. Microstructure noise is found to be informative about the unobserved efficient price, and the informational component explains 45% of the total variation of the microstructure noise.
Download or read book Volatility Information Feedback and Market Microstructure Noise a Tale of Two Regimes written by Torben G. Andersen and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We extend the classical "martingale-plus-noise" model for high-frequency prices by an error correction mechanism originating from prevailing mispricing. The speed of price reversal is a natural measure for informational efficiency. The strength of the price reversal relative to the signal-to-noise ratio determines the signs of the return serial correlation and the bias in standard realized variance estimates. We derive the model's properties and locally estimate it based on mid-quote returns of the NASDAQ 100 constituents. There is evidence of mildly persistent local regimes of positive and negative serial correlation, arising from lagged feedback effects and sluggish price adjustments. The model performance is decidedly superior to existing stylized microstructure models. Finally, we document intraday periodicities in the speed of price reversion and noise-to-signal ratios.
Download or read book An Unbiased Measure of Realized Variance written by Peter Reinhard Hansen and published by . This book was released on 2004 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: The realized variance (RV) is known to be biased because intraday returns are contaminated with market microstructure noise, in particular if intraday returns are sampled at high frequencies. In this paper, we characterize the bias under a general specification for the market microstructure noise, where the noise may be autocorrelated and need not be independent of the latent price process. Within this framework, we propose a simple Newey-West type correction of the RV that yields an unbiased measure of volatility, and we characterize the optimal unbiased RV in terms of the mean squared error criterion. Our empirical analysis of the 30 stocks of the Dow Jones Industrial Average index shows the necessity of our general assumptions about the noise process. Further, the empirical results show that the modified RV is unbiased even if intraday returns are sampled every second.
Download or read book Realized Variance in the Presence of Non Iid Microstructure Noise written by Bart Frijns and published by . This book was released on 2004 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is a well known fact that at high sampling frequencies, the contamination of microstructure noise causes the Realized Variance to be a biased measure of the Integrated Variance. Recent developments in this field propose sampling on lower frequencies, sub-sampling techniques, or bias corrections using the autocorrelation patterns in the data. In this paper we propose a structural decomposition of the efficient price process and the microstructure noise. At the highest sampling frequency, we allow for potential correlation between the efficient price and the microstructure noise. For 20 actively traded stocks at Nasdaq, we find that the method provides a lower bound on Realized Variance. Applying a recently introduced bias correction reveals a very long persistence in transaction by transaction returns corrects the Realized Variance upwards to a level equal to low frequency Realized Variance. It remains questionable, however, whether this long persistence should be seen as microstructure noise, or is an inherent feature of the price process.
Download or read book Volatility Forecasting and Microstructure Noise written by Arthur Sinko and published by . This book was released on 2012 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is common practice to use the sum of frequently sampled squared returns to estimate volatility, yielding so called realized volatility. Unfortunately, returns are contaminated by market microstructure noise. Several noise-corrected realized volatility measures have been proposed. We assess to what extend correction for microstructure noise improves forecasting future volatility using the MIxed DAta Sampling (MIDAS) framework. We start by studying the population properties of predictions using various realized volatility measures. We do this in a general regression setting and with both i.i.d. as well as depend microstructure noise. Next we study optimal sampling issues theoretically, when the objective is forecasting and microstructure noise contaminates realized volatility. For the volatility measures constructed using five-minute returns, microstructure corrections tend to reduce predictability. The subsampling and averaging class of estimators (Zhang, Mykland, and Aamp;ıt-Sahalia 2005) predicts volatility the best at this frequency. In particular, a new power variation estimator constructed by averaging over subsamples has the best performance. This result reinforces earlier findings of (Ghysels, Santa-Clara, and Valkanov 2006) and Forsberg and Ghysels (2004). Finally, the volatility dynamics are more complicated for one-minute returns and the results are not that clear-cut. Moreover, when we study optimal sampling empirically, we find its implementation hampered by the requirement to estimate fourth order moments.
Download or read book Frequency of Observation and the Estimation of Integrated Volatility in Deep and Liquid Financial Markets written by Alain P. Chaboud and published by . This book was released on 2007 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. Using volatility signature plots and a recently-proposed formal decision rule to select the sampling frequency, we find that one can sample FX returns as frequently as once every 15 to 20 seconds without contaminating volatility estimates; bond returns may be sampled as frequently as once every 2 to 3 minutes on days without U.S. macroeconomic announcements, and as frequently as once every 40 seconds on announcement days. With a simple realized kernel estimator, the sampling frequencies can be increased to once every 2 to 5 seconds for FX returns and to about once every 30 to 40 seconds for bond returns. These sampling frequencies, especially in the case of FX returns, are much higher than those often recommended in the empirical literature on realized volatility in equity markets. We suggest that the generally superior depth and liquidity of trading in FX and government bond markets contributes importantly to this difference.
