|
on Market Microstructure |
| By: | Gomber, Peter; Sagade, Satchit; Theissen, Erik; Weber, Moritz Christian; Westheide, Christian |
| Abstract: | The equity trading landscape all over the world has changed dramatically in recent years. We have witnessed the advent of new trading venues and significant changes in the market shares of existing ones. We use an extensive panel dataset from the European equity markets to analyze the market shares of five categories of lit and dark trading mechanisms. Market design features, such as minimum tick size, immediacy and anonymity; market conditions, such as liquidity and volatility; and the informational environment have distinct implications for order routing decisions and trading venues' resulting market shares. Furthermore, these implications differ distinctly for small and large trades, probably because traders jointly optimize their trade size and venue choice. Our results both confirm and go beyond current theoretical predictions on trading in fragmented markets. |
| Keywords: | dark trading,fragmentation,anonymity,immediacy |
| JEL: | G10 G12 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:safewp:143&r=mst |
| By: | El Euch Omar; Fukasawa Masaaki; Rosenbaum Mathieu |
| Abstract: | We show that typical behaviors of market participants at the high frequency scale generate leverage effect and rough volatility. To do so, we build a simple microscopic model for the price of an asset based on Hawkes processes. We encode in this model some of the main features of market microstructure in the context of high frequency trading: high degree of endogeneity of market, no-arbitrage property, buying/selling asymmetry and presence of metaorders. We prove that when the first three of these stylized facts are considered within the framework of our microscopic model, it behaves in the long run as a Heston stochastic volatility model, where leverage effect is generated. Adding the last property enables us to obtain a rough Heston model in the limit, exhibiting both leverage effect and rough volatility. Hence we show that at least part of the foundations of leverage effect and rough volatility can be found in the microstructure of the asset. |
| Date: | 2016–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1609.05177&r=mst |
| By: | Zhuo Zhong (University of Melbourne); Kei Kawakami (University of Melbourne) |
| Abstract: | The decentralized over-the-counter (OTC) market generates a trading network among dealers. We model the driver behind the formation of this inter-dealer network as the need for dealers to share risk. The trade-o¤ between the benefit of risk-sharing and the funding cost of collateral determines the shape of the inter-dealer network. In equilibrium, dealers’ markups and trading volumes increase with the number of links they have to other dealers, whereas dealers’inventory risks decrease as they form links. In addition, when capacity of providing liquidity differentiates dealers, the network formed exhibits the empirically observed core-periphery structure: dealers with large capacity comprise the core of the network, connecting them to all other dealers, while dealers who have small capacity operate at the periphery. The model matches recent empirical findings on the negative relationship between order sizes and markups. More importantly, we show that there may be structural breaks in this negative relationship as variations in order sizes may alter the inter-dealer network. These results suggest that empirical studies on OTC markets should control for the stability of an inter-dealer network to avoid model misspeci…cation. |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed016:822&r=mst |
| By: | Robert Shimer (University of Chicago); Gregor Jarosch (Stanford University); Maryam Farboodi (Princeton University) |
| Abstract: | We study decentralized trading networks where agents differ in both their time-varying taste for an asset and the constant frequency at which they meet others. We show that fast agents can endogenously arise as intermediators whose net valuation of an asset gets moderated through their exposure to others. We show that allocating meetings in an ex-ante asymmetric fashion across agents generates higher welfare then a homogeneous distribution of meeting frequencies, only if some agents intermediate. We also characterize properties of the market equilibrium in which ex-ante identical agents choose their meeting rates, and compare the allocation with the planner allocation. |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed016:844&r=mst |
| By: | Shanshan Wang; Thomas Guhr |
| Abstract: | We construct a price impact model between stocks in a correlated market. For the price change of a given stock induced by the short-run liquidity of this stock itself and of the information about other stocks, we introduce an internal and a cross-impact function of the time lag. We model the average cross-response functions for individual stocks employing the impact functions of the time lag, the impact functions of traded volumes and the trade-sign correlators. To reduce the complexity of the model and the number of fit parameters, we focus on three scenarios and carry out numerical simulations. We also introduce a diffusion function that measures the correlated motion of prices from different stocks to test our simulated results. It turns out that both the sign cross-and self-correlators are connected with the cross-responses. The internal and cross-impact functions are indispensable to compensate amplification effects which are due to the sign correlators integrated over time. We further quantify and interpret the price impacts of time lag in terms of temporary and permanent components. To support our model, we also analyze empirical data, in particular the memory properties of the sign self- and average cross-correlators. The relation between the average cross-responses and the traded volumes which are smaller than their average is of exponential form. |
| Date: | 2016–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1609.04890&r=mst |