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on Market Microstructure |
| By: | Shunya Chomei |
| Abstract: | In this paper, we build on the analysis of Muni Toke and Yoshida (2020) and conduct several empirical studies using high-frequency financial data. Muni Toke and Yoshida (2020) showed the consistency and asymptotic behavior of the Cox-type model estimators for relative intensities of orders in the limit order book, and then by using high-frequency trading data for $36$ stocks traded on the Paris Stock Exchange, they carry out model selection and trading sign prediction. In this study, we add new covariates and carry out model selection and trading sign prediction using high-frequency trading data for $222$ stocks traded on the Tokyo Stock Exchange. We not only show that the Cox-type model performs well in the Japanese market as well as in the Euronext Paris market, but also present the key factors for more accurate estimation. We also suggest how often the covariates should be calibrated. |
| Date: | 2023–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2302.01668&r=mst |
| By: | Giuliano Graziani; Barbara Rindi |
| Abstract: | We consider a model of a limit order book and determine the optimal tick size set by a social planner who maximizes the welfare of market participants. In a 2-period model where only two agents arrive sequentially, the tick size is a friction that constrains investors to use discrete price grids, and as a consequence the optimal tick size is equal to zero. However, in a model with sequential arrival of more than two investors who can endogenously either take liquidity or supply liquidity by undercutting or queuing behind existing orders, the tick size is positive: it is a strategic tool a social planner uses to optimally affect the choice made by investors between liquidity demand and supply. In addition, the optimal tick size is a function both of the value of the asset and of trading volume. The policy implication of such findings is that the European tick size regime and the “Intelligent Ticks” Nasdaq proposal dominate Reg. NMS Rule 612 that formalizes the tick size regime for the U.S. markets. Using data from the U.S. and the European markets we test our model’s empirical predictions. Keywords: Limit Order Book, Tick Size, Social Planner, Undercutting, Queuing. |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:igi:igierp:688&r=mst |
| By: | Mohammed Salek (CentraleSupélec); Damien Challet (CentraleSupélec); Ioane Muni Toke (CentraleSupélec) |
| Abstract: | Using high-quality data, we report several statistical regularities of equity auctions in the Paris stock exchange. First, the average order book density is linear around the auction price at the time of auction clearing and has a large peak at the auction price. The linear part comes from fast traders, while the peak is due to slow traders. The impact of a new market order or cancellation at the auction time can be decomposed into three parts as a function of the size of the additional order: (1) zero impact because of the discrete nature of prices; this holds for surprisingly large orders relative to the auction volume (2) linear impact for additional orders up to a large fraction of the auction volume (3) for even larger orders price impact is non-linear, frequently superlinear. |
| Keywords: | Equity Auctions, Market Microstructure, Price Impact, Statistical Analysis |
| Date: | 2023–01–13 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03938660&r=mst |
| By: | Yuki Sato; Kiyoshi Kanazawa |
| Abstract: | In financial markets, the market order sign exhibits strong persistence, widely known as the long-range correlation (LRC) of order flow; specifically, the sign correlation function displays long memory with power-law exponent $\gamma$, such that $C(\tau) \propto \tau^{-\gamma}$ for large time-lag $\tau$. One of the most promising microscopic hypotheses is the order-splitting behaviour at the level of individual traders. Indeed, Lillo, Mike, and Farmer (LMF) introduced in 2005 a simple microscopic model of order-splitting behaviour, which predicts that the macroscopic sign correlation is quantitatively associated with the microscopic distribution of metaorders. While this hypothesis has been a central issue of debate in econophysics, its direct quantitative validation has been missing because it requires large microscopic datasets with high resolution to observe the order-splitting behaviour of all individual traders. Here we present the first quantitative validation of this LFM prediction by analysing a large microscopic dataset in the Tokyo Stock Exchange market for more than nine years. On classifying all traders as either order-splitting traders or random traders as a statistical clustering, we directly measured the metaorder-length distributions $P(L)\propto L^{-\alpha-1}$ as the microscopic parameter of the LMF model and examined the theoretical prediction on the macroscopic order correlation: $\gamma \approx \alpha - 1$. We discover that the LMF prediction agrees with the actual data even at the quantitative level. Our work provides the first solid support of the microscopic model and solves directly a long-standing problem in the field of econophysics and market microstructure. |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2301.13505&r=mst |