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on Market Microstructure |
| By: | Hafner, Christian (Université catholique de Louvain, LIDAM/ISBA, Belgium); Linton, Oliver (obl20@cam.ac.uk); Wang, Linqi (Université catholique de Louvain, LIDAM/LFIN, Belgium) |
| Abstract: | We introduce a new class of semiparametric dynamic autoregressive models forthe Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a GMM estimator based on conditional moment restrictions and an efficient semiparametric ML estimator based on an iid assumption. We derive large sample properties for both estimators. We further develop a methodology to detect the occurrence of permanent and transitory breaks in the illiquidity process. Finally, we demonstrate the model performance and its empirical relevance on two applications. First, we study the impact of stock splits on the illiquidity dynamics of the five largest US technology company stocks. Second, we investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index. |
| Keywords: | Nonparametric ; Semiparametric ; Splits ; Structural Change |
| JEL: | C12 C14 |
| Date: | 2022–02–23 |
| URL: | http://d.repec.org/n?u=RePEc:aiz:louvad:2022009&r= |
| By: | Bu, R.; Li, D.; Linton, O.; Wang, H. |
| Abstract: | In this paper, we consider estimating spot/instantaneous volatility matrices of high-frequency data collected for a large number of assets. We first combine classic nonparametric kernel-based smoothing with a generalised shrinkage technique in the matrix estimation for noise-free data under a uniform sparsity assumption, a natural extension of the approximate sparsity commonly used in the literature. The uniform consistency property is derived for the proposed spot volatility matrix estimator with convergence rates comparable to the optimal minimax one. For the highfrequency data contaminated by the microstructure noise, we introduce a localised pre-averaging estimation method in the high-dimensional setting which first pre-whitens data via a kernel filter and then uses the estimation tool developed in the noise-free scenario, and further derive the uniform convergence rates for the developed spot volatility matrix estimator. In addition, we also combine the kernel smoothing with the shrinkage technique to estimate the time-varying volatility matrix of the high-dimensional noise vector, and establish the relevant uniform consistency result. Numerical studies are provided to examine performance of the proposed estimation methods in finite samples. |
| Keywords: | Brownian semi-martingale, Kernel smoothing, Microstructure noise, Sparsity, Spot volatility matrix, Uniform consistency |
| JEL: | C10 C14 C22 |
| Date: | 2022–03–16 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2218&r= |
| By: | Eichfelder, Sebastian; Noack, Mona; Noth, Felix |
| Abstract: | We investigate the impact of the French 2012 financial transaction tax on trading activity, volatility, and price efficiency measured by first-order autocorrelation. We extend empirical research by analysing anticipation and reallocation effects. In addition, we consider measures for long-run volatility and first-order autocorrelation that have not been explored yet. We find robust evidence for anticipation effects before the effective date of the French FTT. Controlling for short-run effects, we only find weak evidence for a long-run reduction of trading activity due to the French FTT. Thus, the main impact of the French FTT on trading activity is short-run. We find stronger reactions of low-liquidity treated stocks and a reallocation of trading activity to high-liquidity stocks participating in the Supplemental Liquidity Provider Programme, which is both in line with liquidity clientele effects. Finally, we find weak evidence for a persistent volatility reduction but no indication for a significant FTT impact on price efficiency measured by first-order autocorrelation. |
| Keywords: | anticipation effect,financial transaction tax,long-run treatment effect,market quality,short-run treatment effect |
| JEL: | G02 G12 H24 M4 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwhdps:122022&r= |
| By: | Ben-Rephael, Azi; Cookson, J. Anthony; izhakian, yehuda |
| Abstract: | This paper shows that public information arrival affects investor beliefs and disagreement through a new channel: the uncertainty of beliefs (UOB). Based on novel daily measurement of belief uncertainty and disagreement, disagreement and trading are lower when UOB is higher. Higher UOB also dampens the relationship between disagreement and trading volume. The paper also highlights novel patterns of disagreement and trading around public news. For clarifying news like earnings announcements, information arrival reduces UOB, which naturally amplifies disagreement and trading. Consistent with learning, UOB decreases more for events with more attentive investors and for firms with a better information environment. By contrast, unscheduled events with opaque information information increase UOB while decreasing disagreement and trading. |
| Date: | 2022–02–22 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:ud7yw&r= |