Markus Bibinger from the University of Marburg, Christopher Neely from the Federal Reserve Bank of St. Louis and Lars Winkelmann from Free University Berlin published a paper using LOBSTER data. It is titled Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book and is forthcoming in the Journal of Econometrics.
Abstract: An extensive empirical literature documents a generally negative relation, named the “leverage effect,” between asset returns and changes of volatility. It is more challenging to establish such a return–volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and test for a discontinuous leverage effect — i.e. a covariation between contemporaneous jumps in prices and volatility. The methods are robust to market microstructure noise and build on a newly developed price-jump localization and estimation procedure. Our empirical investigation of six years of transaction data from 320 NASDAQ firms displays no unconditional negative covariation between price and volatility cojumps. We show, however, that there is a strong and significant discontinuous leverage effect if one conditions on the sign of price jumps and whether the price jumps are market-wide or idiosyncratic.
You can find the article here.
and Ulrich Horst of Universität Wien and Humboldt-Universität zu Berlin published and Article in April 2015) with the titel Optimal order display in limit order markets with liquidity competition using LOBSTER data. Abstract:
Order display is associated with benefits and costs. Benefits arise from increased execution-priority, while costs are due to adverse market impact. We analyze a structural model of optimal order placement that captures trade-off between the costs and benefits of order display. For a benchmark model of pure liquidity competition, we give a closed-form solution for optimal display sizes. We show that competition in liquidity supply incentivizes the use of hidden orders to prevent losses due to over-bidding. Thus, because aggressive liquidity competition is more prevalent in liquid stocks, our model predicts that the proportion of hidden liquidity is higher in liquid markets. Our theoretical considerations ares supported by an empirical analysis using high-frequency order-message data from NASDAQ. We find that there are no benefits in hiding orders in il-liquid stocks, whereas the performance gains can be significant in liquid stocks.
Julius Bonart and Martin Gould of Imperial College London published an Article in (April 2017) using LOBSTER data titled Latency and Liquidity Provision in a Limit Order Book. Abstract:
We use a recent, high-quality data set from Nasdaq to perform an empirical analysis of order flow in a limit order book (LOB) before and after the arrival of a market order. For each of the stocks that we study, we identify a sequence of distinct phases across which the net flow of orders differs considerably. We note some of our results are consist with the widely reported phenomenon of stimulated refill, but that others are not. We therefore propose alternative mechanical and strategic motivations for the behaviour that we observe. Based on our findings, we argue that strategic liquidity providers consider both adverse selection and expected waiting costs when deciding how to act.
Read the working paper version here.
VieCo 2017 aims to bring together leading experts and practitioners in financial econometrics, financial statistics, quantitative financial economics as well as applied mathematical finance. It is jointly organized by the Department of Statistics and Operations Research of the University of Vienna, in cooperation with the Wolfgang Pauli Institute Vienna and the Department of Economics of the University of Copenhagen. The “Vienna–Copenhagen Conference on Financial Econometrics” will take place on March 9-11 2017 in Vienna.
LOBSTER will be present at the conference, if you like to get in touch please come to our desk during the poster session on friday or send an email to get in touch.
HFT2016 aims at bringing together some of the world’s leading experts on high-frequency trading. The focus will be on a critical analysis as well as the perspectives of this recent development in global financial markets.
LOBSTER is presented at the conference with our academic adviser and co-founder Prof. Nikolaus Hautsch (who also happens to organize the event).
After two years of testing LOBSTER supported by Humboldt-Innovation GmbH, the incubator of Humboldt-Universität zu Berlin, we, the developers and creators of LOBSTER, founded our own company to develop & distribute LOBSTER further.
Our company’s name frischedaten UG (haftungsbeschränkt) roughly translates to fresh and recent data, and verbalizes what we strive for.
If you are already a customer, you received an email legally informing you of the transition of your current contract from Humboldt-Innovation to frischedaten UG. Your terms remain unchanged, but you will need to shortly confirm to that transition so that you can access LOBSTER after the 14th of November.
Our new customers will be able to conclude a contract directly with frischedaten UG from now on. We will update the relevant pages for the onboarding process shortly, in the meantime just contact us for all questions regarding enrolment.
As our customer base increases, so are the usage patterns of our users. We saw an increase in very big data queries the last weeks, which our queuing system handled efficiently but not very fair-minded with respect to users that wanted to see their small queries fulfilled in a reasonable time frame. To accommodate all of our users, we had to tweak the queuing system of LOBSTER.
From now on we have a fixed amount of threads (currently three) that run in parallel associated with each user. Of course you can still enter all your queries at once, and three of them will always start immediately while all others get queued until the first one finishes.
We updated our research section with some of the recent papers that used LOBSTER as data source. Are you missing your work? We will gladly add them to the section in case you let us know.
We updated the LOBSTER database to include data up to the 27th of June 2007.