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on Market Microstructure |
| By: | Peng Wu; Marcello Rambaldi; Jean-Fran\c{c}ois Muzy; Emmanuel Bacry |
| Abstract: | In this work we introduce two variants of multivariate Hawkes models with an explicit dependency on various queue sizes aimed at modeling the stochastic time evolution of a limit order book. The models we propose thus integrate the influence of both the current book state and the past order flow. The first variant considers the flow of order arrivals at a specific price level as independent from the other one and describes this flow by adding a Hawkes component to the arrival rates provided by the continuous time Markov "Queue Reactive" model of Huang et al. Empirical calibration using Level-I order book data from Eurex future assets (Bund and DAX) show that the Hawkes term dramatically improves the pure "Queue-Reactive" model not only for the description of the order flow properties (as e.g. the statistics of inter-event times) but also with respect to the shape of the queue distributions. The second variant we introduce describes the joint dynamics of all events occurring at best bid and ask sides of some order book during a trading day. This model can be considered as a queue dependent extension of the multivariate Hawkes order-book model of Bacry et al. We provide an explicit way to calibrate this model either with a Maximum-Likelihood method or with a Least-Square approach. Empirical estimation from Bund and DAX level-I order book data allow us to recover the main features of Hawkes interactions uncovered in Bacry et al. but also to unveil their joint dependence on bid and ask queue sizes. We notably find that while the market order or mid-price changes rates can mainly be functions on the volume imbalance this is not the case for the arrival rate of limit or cancel orders. Our findings also allows us to clearly bring to light various features that distinguish small and large tick assets. |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1901.08938&r=all |
| By: | Merrick Li, Z.; Linton, O. |
| Abstract: | We introduce a new nonparametric method to measure microstructure noise, the deviation of the observed asset prices from the fundamental values caused by market imperfections. Using high-frequency data, we provide joint estimators of arbitrary finite moments of microstructure noise, which could be serially dependent and nonstationary. We characterize the limit distributions of the proposed estimators and construct robust confidence intervals under infill asymptotics. We further demonstrate a consistency property of our new estimators without any specification on the data frequencies. As an economic application, we propose two liquidity measures that gauge the instantaneous and average bid-ask spread with potentially autocorrelated order flows, and such measures can be interpreted as an intermediary’s inventory risks to meet liquidity demand. Statistical applications include several model-free tests for the intraday patterns and the zero autocorrelations hypotheses of microstructure noise. |
| Date: | 2019–01–13 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:1908&r=all |
| By: | Entrop, Oliver; Fischer, Georg |
| Abstract: | This paper is the first to analyze the joint determinants of premiums and spreads in structured financial products, while also focusing on issuers' hedging costs. We evaluate more than 396,000 single stock discount certificates on an intraday basis in the German secondary market. We find that premiums and spreads are endogenous and negatively related to each other, and depend on different key determinants. The economically significant determinants of the premiums are mainly profit-related, i.e. dividends of the underlying, issuers' credit risk, lifecycle effect and competition, whereas hedging costs and risks are economically less important. However, initial hedging costs are also priced into the premium in the case of large inventory changes. The spread is mostly determined by hedging costs and risk components, such as initial hedging costs, rebalancing costs, volatility, scalper risk, and overnight gap risk, but also depends on dividends. Initial hedging costs appear to be more relevant than rebalancing costs. |
| Keywords: | Discount certificates,Derivatives,Pricing,Market microstructure,Trading costs,Hedging |
| JEL: | D40 G12 G21 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:upadbr:b3419&r=all |
| By: | Linton, O.; Wu, J. |
| Abstract: | We propose a semi-parametric coupled component GARCH model for intraday and overnight volatility that allows the two return series to have different properties. We adopt a dynamic conditional score model with t-distributed innovations that captures the very heavy tails of overnight returns. We propose a several-step estimation procedure that captures the nonparametric slowly moving components by kernel estimation and the dynamic parameters by estimated maximum likelihood. We establish the consistency, asymptotic normality, and semiparametric efficiency of our semiparametric estimation procedures. We extend the modelling to the multivariate case where we allow time varying correlation between stocks. We apply our model to the study of Dow Jones industrial average component stocks, CRSP size-based portfolios, and size-based portfolios in four large international markets over the period 1993-2017. We show that the ratio of overnight to intraday volatility has actually increased in importance for Dow Jones stocks during the last two decades. This ratio has also increased for large stocks in the CRSP database, but decreased for small stocks in CRSP. Notably, the slope increases monotonically from the smallest-cap decile to the largest-cap decile. This pattern also exists in other international markets. The multivariate model shows that overnight and intraday correlations have both increased, but overnight correlations have increased more substantially during recent crises than intraday correlations. |
| Keywords: | DCS, GAS, GARCH, size-based portfolios, Testing |
| JEL: | C12 C13 |
| Date: | 2018–09–14 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:1879&r=all |