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Department of Statistics


Department of Statistics
Columbia House
London School of Economics
Houghton Street


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BSc Queries

+44 (0)20 7955 7650


MSc Queries

+44 (0)20 7955 6879 

MSc Frequently Asked Questions


MPhil/PhD Queries

+44 (0)20 7955 7511
i.marshall@lse.ac.uk (PhD enquiries)









Welcome to the Department of Statistics at the London School of Economics & Political Science. The department enjoys a vibrant research environment and offers a comprehensive programme of undergraduate and postgraduate degrees in Statistics.

The Department of Statistics offers a comprehensive programme of seminars throughout the year, including the statistics seminars series, joint statistics and econometrics seminars and the London Mathematical Finance seminars. You can find further details here, along with an archive of our past seminars and details of workshops, conferences and other special events.
Our forthcoming conferences and workshops include:
Current challenges in financial mathematics and economics (August 2015)
Complex systems in time series  (December 2015)

See below for more details.
Workshop on current challenges in financial mathematics and economics
Monday 24 August 2015 to Friday 28 August 2015 (London)
A week-long series of workshops

When you register a place to attend this conference we recommend that you also email Ian Marshall (i.marshall@lse.ac.uk) to confirm that you have done this

The recent and on-going financial crisis motivates a scrutinised study in the field of Financial Mathematics. In order to obtain better models, imperfections and complexity of real financial markets must be taken into account. Rather than assuming that arbitrary quantities of assets can be traded without impacting the market, liquidity risk needs to be carefully analysed.

Facing imperfections, good models must be robust, placing less emphasis on particular model assumptions which tend to be unrealistic in practical applications. A better understanding of such issues is of strategic importance to maintain a healthy financial system, and is currently attracting considerable interest from researchers, industry practitioners, as well as regulators.

Any model of liquidity risk will be incomplete without a detailed analysis of the dynamics of supply and demand and the causes of their imbalance. In particular it is important to understand how this imbalance evolve in time in an equilibrium framework where strategic agents trade to maximise their utility.  In order to analyse  interacting, possibly heterogeneous, agents, one often needs a diverse set of tools from filtering theory, multi-dimensional backward stochastic differential equations and mean-field games.

Recent years have also witnessed substantial developments in path-wise stochastic analysis and martingale transport theory. These results have found applications in obtaining robust financial models for derivative pricing.  The aim of this workshop is to bring together researchers to discuss the latest developments in three aforementioned themes: liquidity, mean field games, and robust finance.

Speakers include Pierre Collin-Dufresne  (EPFL); Alexander Cox (University of Bath); François Delarue (Université Nice-Sophia Antipolis); Markus Fischer (University of Padua); Ying Hu (Université de Rennes 1); Dmitry Kramkov (Carnegie Mellon University); Martin Larsson (ETH Zürich): Mathieu Rosenbaum (Université Pierre et Marie Curie - Paris VI)

Please send any questions to Ian Marshall.
Complex systems in time series
Friday 4 and Saturday 5 December 2015 (London)

When you register a place to attend this conference we recommend that you also email Ian Marshall (i.marshall@lse.ac.uk) to confirm that you have done this.  

Complex systems can be observed from complex social networks and its evolution to transportation and electric power generation; from physical flow of fluids to neurological circuits in our brains; from spatio-temporal dependence of macroeconomic and financial; time series to the spread of disease. Understanding any patterns and providing good forecasts in these systems is of paramount importance in decision or policy making. Since data involved is usually high dimensional in nature and dependence among variables can be strong, techniques in handling such data are all evolving to adapt to the new challenges. New research in this direction includes temporal network analysis, statistical and machine learning, parametric and nonparametric inferences and dimension reduction in stationary and non-stationary time series.

The aim of this two-day conference is to bring together expertise in these areas to create possible new research opportunities. Researchers from relevant scientific fields can also gain valuable information on new data analytics.

Confirmed speakers: John Aston (Cambridge); Marc Hallin (ECARES); Eric D Kolaczyk (Boston University); Wolfgang K Härdle (Humboldt University); Olivier Ledoit (University of Zurich); Alexei Onatski (University of Cambridge); Richard Samworth (University of Cambridge); Rainer von Sachs  (Université catholique de Louvain); Patrick Wolfe (UCL); Jeff Yao (Hong Kong University).

Please send any questions to Ian Marshall.
The department offers degree courses at undergraduate, taught postgraduate and research level.

Undergraduate programmes offer an opportunity to build on your mathematical skills and apply them to areas such as insurance, banking, finance and statistics.

The MSc programmes provide students with intensive training in statistics applicable to the social sciences, econometrics, finance and insurance.

The department welcomes applications for the MPhil/PhD in Statistics from suitably qualified candidates. Full details of departmental research interests are available on our Research pages.
The department has three undergraduate degrees that involve the applications of statistics to the social sciences and include a range of statistical and mathematical subjects.

BSc in Actuarial Science
BSc in Business Mathematics and Statistics
BSc Statistics with Finance
Our taught postgraduate courses are based around lectures, with problem classes and computer workshops. Most courses are assessed by a two-hour exam in the summer term, although some contain an element of course work.

MSc in Statistics
MSc in Statistics (Financial Statistics)
MSc in Risk and Stochastics
Research programmes are designed to produce professional social scientists, well versed in a range of advanced statistical techniques and methods, in addition to having an in-depth knowledge of a particular area.

MPhil/PhD Statistics




Research in Risk and Stochastics

Our research in risk and stochastics covers diverse aspects in quantitative modelling in finance, insurance, and risk management. Current areas include robust models on option pricing; model-uncertainty in decision making; valuation financial derivatives with exotic features; equilibrium with market constraints and informational asymmetry; optimal trading with micro-structure noise; insurance securitisation; contagion in financial and insurance markets; modelling energy and commodity markets.

The current members of the Risk and Stochastics group are Beatrice Acciaio, Pauline Barrieu, Erik Baurdoux, Luciano Campi, Umut Cetin, Angelos Dassios, Kostas Kardaras and Hao Xing.

Research in Social Statistics

Research in social statistics is concerned with the development of statistical methods that can be used across the social sciences. Statisticians play an essential role in all aspects of social inquiry, including: study design; measurement; data linkage; development of statistical models that account for the complex structure of social data; model selection and assessment.

Members of the Social Statistics group have interest in statistical methods in each of these areas and regularly collaborate with social scientists whose questions motivate new lines of methodological research. We have experience in a range of social science disciplines, including demography, education, epidemiology, psychology and sociology, and psychology.

The current members of the Social Statistics group are Wicher Bergsma, Sara Geneletti, Kostas Kalogeropoulos, Jouni Kuha, Irini Moustaki, Chris Skinner and Fiona Steele.

Research in Time Series

The Department's research in time series encompasses many aspects of the discipline. We are keenly involved in both theoretical developments and practical applications. Current areas of interest include non-parametric inference for financial time series, model error in forecasting non-linear systems, structural modelling of weather series and decision support using weather and climate models.

The current members of the Time Series group are Matteo Barigozzi, Piotr Fryzlewicz, Kostas Kalogeropoulos, Clifford Lam, Leonard Smith and Qiwei Yao. The group will soon be joined by Yining Chen and Xinghao Qiao.

The Centre for the Analysis of Time Series (CATS)

The centre aims to ddress the question of data analysis using both physical insight and the latest statistical methods; focus on non-linear analysis in situations of economic and physical interest, such as weather forecasting; promote awareness of limitations of non-linear analysis and the danger of blindly transferring well-known physics to simulation modelling; focus on end-to-end forecasting, taking account of current uncertainty about the state of the system, model inadequacy and finite computational power.

CATS is led by Director Leonard Smith, with Chair Henry Wynn and Co-Directors Pauline Barrieu, Roman Frigg and David Stainforth.