Torben Andersen, Northwestern University, USA


Kim Christensen, Aarhus University, Denmark

Kim Christensen acquired his PhD from Aarhus School of Business, Aarhus University in 2007. His research interests include financial econometrics, particularly the modelling of financial markets volatility using high-frequency data (intraday transaction and quotation data). He has published his work in a number of leading field journals, including Journal of Econometrics and Journal of Financial Economics. He has previously held a position as an inflation-linked derivatives trader in Nordea, Copenhagen. He is the 2011 and 2019 winner of the Golden Pointer (Lecturer of the year prize awarded for teaching excellence) based on his lecture series in Statistics.

Dobrislav Dobrev, Federal Reserve Board, USA

I am a Research Economist at the Federal Reserve Board where my primary research focus has been on studying high-frequency volatility, jumps, and comovements, improving data-driven identification and attribution of abnormal market moving events and developing robust techniques for measurement, filtering and forecasting of latent activity variables in data-rich environments. I have a long-standing expertise in econometric analysis of high-frequency financial data and most recently I have been studying the impact of high-speed trading and algorithmic execution on cross-market linkages and liquidity provision. My work draws heavily on research computing and data science tools for analyzing vast amounts of tick-by-tick market data and running related large-scale simulations. In addition to applying my expertise in Federal Reserve Board and inter-agency policy analysis and research projects in these areas, I have also served as a contributor to a BIS Markets Committee study on algorithmic execution in FX markets and follow-up workshops on monitoring fast-paced electronic markets. My published research has been well cited and I have served regularly as a program committee member of conferences in the field.

I hold a PhD in Finance from Northwestern University’s Kellogg School of Management and an MSc in Applied Mathematics from Sofia University, Bulgaria. I am the recipient of the 2007 Chookaszian Prize in Risk Management and 2015 Special Achievement Award from the Board of Governors of the Federal Reserve System for my contributions to the high-frequency data analysis in the Joint Staff Report on the October 15, 2014 flash rally in U.S. Treasury markets.

Aleksey Kolokolov, University of Manchester, UK

Aleksey Kolokolov is a Lecturer (Assistant Professor) in Finance at Alliance Manchester Business School with a wide range of research interests. He focuses on econometrics and financial markets, with specific contributions to advanced statistical methods, high-frequency data analysis, forecasting, modelling jumps and flash-crashes.



Yifan Li, University of Manchester, UK

Yifan Li joined the Alliance Manchester Business School as a Lecturer in Finance in 2018. His research interest mainly lies in the field of econometric theory and its applications in finance. The themes of his works include volatility modelling using point processes, high-frequency option data, non-parametric moment estimators, market microstructure, the impact of news in the financial market, etc. Yifan holds an MRes in Finance and a PhD in Finance from Lancaster University and is an external researcher in the Centre for Financial Econometrics, Asset Market and Macroeconomic Policy.

Oliver Linton, University of Cambridge, UK

Oliver Linton is a fellow of Trinity College and is Professor of Political Economy at Cambridge University. Formerly, Professor of Econometrics at the London School of Economics and Professor of Economics at Yale University. He obtained his PhD in Economics from the University of California at Berkeley in 1991. He has published two books and more than a hundred articles on econometrics, statistics, and empirical finance. In 2015 he was a recipient of the Humboldt Research Award of the Alexander von Humboldt Foundation. He was Co-editor at the Journal of Econometrics between 2014 and 2019. He is a Fellow of: the Econometric Society, the Institute of Mathematical Statistics, and the British Academy. He is currently President of the Society for Financial Econometrics. He was a lead expert in the U.K. Government Office for Science Foresight project: “The future of Computer Trading in Financial Markets”, which published in 2012. He has appeared as an expert witness in several cases involving market manipulation.

Roberto Renò, University of Verona, Italy

Roberto Renò is Professor of Quantitative Finance at the Department of Economics of the University of Verona. He is Visiting Professor at the Carey Business School at the Johns Hopkins University of Baltimore and ESSEC Business School in Cergy. He has been Senior Fellow at Collegio Carlo Alberto, Turin; Fernand Braudel Fellow at the European University Institute in Florence; Visiting Professor at LUISS, Rome and IMT, Lucca; Associate and Assistant Professor of Quantitative Finance at the University of Siena. He holds a PhD in Financial Mathematics at Scuola Normale Superiore in Pisa, Italy, and a Degree in Physics at the University of Pisa. His research focuses on various aspects of finance, with specific contributions in asset pricing, volatility modeling and forecasting, nonparametric statistics. He published more than 40 research papers on leading finance, economics, econometrics, mathematics and physics journals.

Viktor Todorov, Northwestern University, USA

Viktor Todorov is Harold H. Hines Jr. Professor of Risk Management and Professor of Finance at the Kellogg School of Management, Northwestern University. Professor Todorov is a Fellow of the Society for Financial Econometrics and the Journal of Econometrics. His research interests are in the areas of theoretical and empirical asset pricing, econometrics and applied probability. He has published extensively in these fields. His recent work focuses on the robust estimation of asset pricing models using high-frequency financial data as well as the development and application of parametric and nonparametric methods of inference for studying risks and risk premia using derivatives markets data. He currently serves as a Co-Editor for Econometric Theory, and is on the editorial board of a number of leading academic journals, including Econometrica and the Journal of Econometrics. He received his PhD in Economics from Duke University in 2007.