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on Market Microstructure |
| By: | Gloria Gonzalez-Rivera (Department of Economics, University of California Riverside); Wei Lin (Capital University of Economics and Business, China) |
| Abstract: | Asymmetric information models of market microstructure claim that variables like trading intensity are proxies for latent information on the value of financial assets. We consider the interval-valued time series (ITS) of low/high returns and explore the relationship between these extreme returns and the intensity of trading. We assume that the returns (or prices) are generated by a latent process with some unknown conditional density. At each period of time, from this density, we have some random draws (trades) and the lowest and highest returns are the realized extreme observations of the latent process over the sample of draws. In this context, we propose a semiparametric model of extreme returns that exploits the results provided by extreme value theory. If properly centered and standardized extremes have well defined limiting distributions, the conditional mean of extreme returns is a highly nonlinear function of conditional moments of the latent process and of the conditional intensity of the process that governs the number of draws. We implement a two-step estimation procedure. First, we estimate parametrically the regressors that will enter into the nonlinear function, and in a second step, we estimate nonparametrically the conditional mean of extreme returns as a function of the generated regressors. Unlike current models for ITS, the proposed semiparametric model is robust to misspecification of the conditional density of the latent process. We fit several nonlinear and linear models to the 5-min and 1-min low/high returns to seven major banks and technology stocks, and find that the nonlinear specification is superior to the current linear models and that the conditional volatility of the latent process and the conditional intensity of the trading process are major drivers of the dynamics of extreme returns. |
| Keywords: | Trading intensity, Interval-valued Time Series, Generalized Extreme Value Distribution, Nonparametric regression, Generated Regressor |
| JEL: | C01 C14 C32 C51 |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:ucr:wpaper:201801&r=mst |
| By: | Linton, O.; Mahmoodzadeh, S. |
| Abstract: | High frequency trading (HFT) has grown substantially in recent years, due to fast-paced technological developments and their rapid uptake, particularly in equity markets. This paper investigates how HFT could evolve and, by developing a robust understanding of its effects, to identify potential risks and opportunities that it could present in terms of financial stability and other market outcomes such as volatility, liquidity, price efficiency and price discovery. Despite commonly held negative perceptions, the available evidence indicates that HFT and algorithmic trading (AT) may have several beneficial effects on markets. However, they may cause instabilities in financial markets in specific circumstances. Carefully chosen regulatory measures are needed to address concerns in the shorter term. However, further work is needed to inform policies in the longer term, particularly in view of likely uncertainties and lack of data. This will be vital to support evidence-based regulation in this controversial and rapidly evolving field. |
| Date: | 2018–01–12 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:1802&r=mst |
| By: | Lisa Anderson; Emad Andrews; Baiju Devani; Michael Mueller; Adrian Walton |
| Abstract: | In 2015, TSX Alpha, a Canadian stock exchange, implemented a speed bump for marketable orders and an inverted fee structure as part of a redesign. We find no evidence that this redesign impacted market-wide measures of trading costs or contributed appreciably to segmenting retail order flow away from other Canadian venues with a maker-taker fee structure. This suggests that Alpha attracts already-segmented flow from venues with fee structures other than maker-taker. Some heavy users of Alpha trade off improvements in fill rates and execution size against mildly larger effective spreads and price impacts. These heavy users also utilize larger market orders and fewer spray orders. |
| Keywords: | Financial markets, Market structure and pricing |
| JEL: | G14 G24 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:18-3&r=mst |
| By: | Kinda Hachem (University of Chicago); Ana Babus (Chicago FED) |
| Abstract: | Standardized financial securities are frequently traded in over-the-counter markets. This is difficult to reconcile with the view that these markets exist to facilitate the trade of customized contracts. We build a model of financial innovation to explain why standardized securities can be traded in decentralized markets. In our set-up, each dealer designs a security which specifies a payoff for every state of the world. The dealer chooses the states in which the payoff is flat and the states in which the payoff is contingent on the realized state of the world. Investors choose which securities to trade, taking into account how their trades may impact the price of each security. The market structure in which a given security is traded is determined endogenously. We characterize which securities are traded in decentralized rather than centralized markets. We also study the effects of regulations that force all trade to take place in centralized markets. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed017:1212&r=mst |