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on Market Microstructure |
| By: | Alasdair Brown (University of East Anglia); Fuyu Yang (University of East Anglia) |
| Abstract: | Recent evidence suggests that the fastest algorithmic traders in financial markets profit at the expense of slower traders. One solution gaining traction is a `speed-bump', which introduces a delay between the time in which an order is submitted, and when it is processed. We conduct an impact evaluation of the speed bump's effectiveness on Betfair, a betting exchange, where this design has been in force for more than a decade. We find that increases in the duration of the delay led to improvements in liquidity (measured by bid-ask spreads and depth) and market quality (measured by order frequency and volume). |
| Date: | 2015–04 |
| URL: | http://d.repec.org/n?u=RePEc:uea:aepppr:2012_70&r=mst |
| By: | Simon Hagemann; Christoph Weber (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen) |
| Abstract: | This paper presents an analytical benchmark model for national intraday adjustment needs under consideration of fundamental drivers, market concentration and portfolio internal netting. The benchmark model is used to calculate the intraday market outcomes if (i) large and small players as well as transmissions operators trade and (ii) only large players and transmission system operators trade. Transaction costs may prevent the competitive fringe from intraday market participation. The theoretical national intraday trading volumes are calculated with market data from three European countries with auction-based intraday markets (Italy, Portugal, Spain) and four countries with continuous intraday markets (Denmark, France, Germany, United Kingdom). The model results allow two main conclusions: The competitive fringe is not trading on exchanges in Denmark and France but in Germany. The second conclusion is that the high observed volumes in auction-based intraday markets cannot be explained by fundamentals or the auction-based design but are mainly caused by market peculiarities. The same result applies to the UK. |
| Keywords: | Renewables market integration, Liquidity modeling, continuous and auction-based intraday markets |
| JEL: | L94 Q41 |
| Date: | 2015–04 |
| URL: | http://d.repec.org/n?u=RePEc:dui:wpaper:1503&r=mst |
| By: | Bell, Peter N |
| Abstract: | I had the pleasure to hear Dr. Soheil Mahmoodzadeh discuss his job market paper (Mahmoodzadeh & Gençay, 2015) recently at the University of Victoria Department of Economics seminar. The paper studies the effect of changes to tick size from pip to decimal pip for major currency pairs by the Electronic Broking Services (EBS) in 2011. EBS implemented the change in a way that provides a natural or quasi-experiment with observations on both treatment and control groups, before and after the change. The change to decimal pip added an extra decimal point to all orders, which created new opportunities for high frequency traders (HFT) that may benefit or hurt the market. Mahmoodzadeh and Gençay establish stylized facts about the market and address how the change in tick size effects measures of market quality. |
| Keywords: | Foreign exchange, tick size, decimal pip, high frequency traders. |
| JEL: | G10 |
| Date: | 2015–02–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:62157&r=mst |
| By: | Lucio Maria Calcagnile; Giacomo Bormetti; Michele Treccani; Stefano Marmi; Fabrizio Lillo |
| Abstract: | Recent years have seen an unprecedented rise of the role that technology plays in all aspects of human activities. Unavoidably, technology has heavily entered the Capital Markets trading space, to the extent that all major exchanges are now trading exclusively using electronic platforms. The ultra fast speed of information processing, order placement, and cancelling generates new dynamics which is still not completely deciphered. Analyzing a large dataset of stocks traded on the US markets, our study evidences that since 2001 the level of synchronization of large price movements across assets has significantly increased. Even though the total number of over-threshold events has diminished in recent years, when an event occurs, the average number of assets swinging together has increased. Quite unexpectedly, only a minor fraction of these events -- regularly less than 40% along all years -- can be connected with the release of pre-announced macroeconomic news. We also document that the larger is the level of sistemicity of an event, the larger is the probability -- and degree of sistemicity -- that a new event will occur in the near future. This opens the way to the intriguing idea that systemic events emerge as an effect of a purely endogenous mechanism. Consistently, we present a high-dimensional, yet parsimonious, model based on a class of self- and cross-exciting processes, termed Hawkes processes, which reconciles the modeling effort with the empirical evidence. |
| Date: | 2015–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1505.00704&r=mst |
| By: | Peter Reinhard Hansen (European University Institute and CREATES); Guillaume Horel (Serenitas Credit L.p.); Asger Lunde (Aarhus University and CREATES); Ilya Archakov (European University Institute) |
| Abstract: | We introduce a multivariate estimator of financial volatility that is based on the theory of Markov chains. The Markov chain framework takes advantage of the discreteness of high-frequency returns. We study the finite sample properties of the estimation in a simulation study and apply it to highfrequency commodity prices. |
| Keywords: | Markov chain, Multivariate Volatility, Quadratic Variation, Integrated Variance, Realized Variance, High Frequency Data |
| JEL: | C10 C22 C80 |
| Date: | 2015–03–30 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2015-19&r=mst |
| By: | António Alberto Santos (Faculty of Economics, University of Coimbra and GEMF, Portugal) |
| Abstract: | In this paper, we calculate the realized volatility measures using intraday data not equally spaced in time. The aim is to compare these measures with the ones from the stochastic volatility model. With this model, the data used are obtained in equal time intervals. Known facts are that the volatility is not directly observable and time-varying. If we consider the set of the most flexible models to capture the volatility evolution of returns, the stochastic volatility model belongs to the aforementioned set. High-frequency observations are used, which means daily observations obtained in equal time intervals. Can this be compatible with ultra-high-frequency data and realized volatility measures? Can we obtain compatible measures of volatility with both approaches? This is the object of this paper. |
| Keywords: | Bayesian estimation, Financial returns, Integrated volatility, Intraday data, Markov chain Monte Carlo, Realized volatility, Stochastic volatility. |
| JEL: | C11 C15 C53 G17 |
| Date: | 2015–04 |
| URL: | http://d.repec.org/n?u=RePEc:gmf:wpaper:2015-10.&r=mst |