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on Market Microstructure |
| By: | Rindi, Barbara; Panayides, Marios; Werner, Ingrid |
| Abstract: | We study the 2013 changes in maker-taker pricing fees implemented by BATS on its two European venues, CXE and BXE. The CXE rebate reduction deteriorates market quality and market share, whereas the BXE rebate removal and take-fee reduction improve them. We derive a model of two competing limit order books, in which large (small) stocks are characterized by investors with higher (lower) propensity to supply liquidity and by greater (lower) trading activity. Consistent with our model, we show that traders in large stocks are more reactive to rebate reductions while traders in small stocks are more reactive to take-fee reductions. |
| JEL: | G10 G12 G14 G18 G20 D40 D47 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19363 |
| By: | Chabakauri, Georgy; Fos, Vyacheslav; Jiang, Wei |
| Abstract: | Privately informed about firm fundamentals, corporate insiders detect activism-motivated trades better than other traders. This paper solves the model of this novel form of insider trading motivated by non-insider information and presents empirical evidence. Corporate insiders preserve their ownership (restraining from selling or buying more) before activist interventions go public to benefit from price appreciation and to defend their private benefits of control. Response to real-time (pre-disclosure) activist trading is stronger precisely when positive information about firm fundamentals is absent, supporting the mechanism that insiders attribute order flows to activist interest when speculation on fundamentals can be ruled out. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19461 |
| By: | Dominik Feil; Max Nendel |
| Abstract: | Prediction markets are attracting growing attention as trading volumes rise and their practical relevance increases. To ensure efficient price discovery, liquidity provision becomes ever more important. Due to the binary settlement structure in prediction markets, optimal market making leads to an optimization problem that is fundamentally different from the ones studied in classical settings. In this paper, we develop a stochastic control framework for prediction markets in which the market price is modeled as a conditional probability of the outcome that is generated by a transformed latent belief diffusion. A market maker selects bid and ask quotes to maximize expected terminal wealth while controlling both mark-to-market inventory risk and the settlement risk of remaining positions at resolution. We derive the associated Hamilton--Jacobi--Bellman equation and characterize the unique optimal bid and ask quotes. By transforming the equation to the latent belief space and using a fixed-point argument, we prove existence and uniqueness of a classical solution and verify the resulting optimal quoting strategy. In addition, we provide a numerical analysis, which reveals how optimal liquidity provision in prediction markets depends on inventory, market beliefs, time to resolution, and risk aversion. Further, we demonstrate that the optimal quoting strategy substantially improves downside protection while preserving most of its expected profit relative to a myopic benchmark that maximizes the instantaneous expected mark-to-market profit. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.17991 |
| By: | Alexander Barzykin; Robert Boyce; Eyal Neuman; Sturmius Tuschmann |
| Abstract: | We derive a mesoscopic model for optimal execution with limit orders that incorporates microstructural features of passive price impact. Our framework is based on two empirical observables: the approximately exponential decay of limit-order fill probabilities with distance from the midprice, and the short-term linear response of price changes to order flow imbalance. Combining these ingredients, we obtain a reduced-form passive impact rate that decays exponentially with quote distance. The model describes passive execution at a tactical level, where fills arise from a sequence of quote adjustments that balance execution probability, adverse selection, and opportunity cost. We formulate and solve an optimal liquidation problem in which the trader controls the aggressiveness of passive sell quotes. This generates a trade-off between higher fill intensity and larger accumulated impact on the one hand, and lower impact but greater non-execution risk on the other. Empirical calibration using NASDAQ equities and public FX supports the empirical foundations of the model. We also analyse extensions with heterogeneous decay rates, transient impact, and target execution schedules. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.28323 |