Dr Emese Lazar

'Dr Emese Lazar

Dr Emese Lazar

  • Associate Professor of Quantitative Finance
  • Programme Director: MSc Financial Engineering

Contact details

Profile & Expertise

Emese received a PhD in Finance from the ICMA Centre, The University of Reading in 2006. Previously she obtained an MSc in Financial Engineering and Quantitative Analysis with a distinction from the ICMA Centre. She graduated from the Academy of Economic Studies in Bucharest, with a BSc in Finance and Banking.  Also, she holds a BSc in Computer Science obtained from the University of Bucharest, Faculty of Mathematics. Her research interests include: risk measurement and management, model risk, volatility and correlation models and their applications in pricing structured products. Emese presently teaches Market Risk and Derivatives Modelling.

Specialisms

  • Financial Econometrics
  • Market Risk
  • Volatility Modelling

Key publications, books, research & papers

Article

Information entropy and measures of market risk

Pele, D. T., Lazar, E. and Dufour, A. (2017) Information entropy and measures of market risk. Entropy, 19 (5). 226. ISSN 1099-4300 doi: 10.3390/e19050226

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In this paper we investigate the relationship between the information entropy of the distribution of intraday returns and intraday and daily measures of market risk. Using data on the EUR/JPY exchange rate, we find a negative relationship between entropy and intraday Value-at-Risk, and also between entropy and intraday Expected Shortfall. This relationship is then used to forecast daily Value-at-Risk, using the entropy of the distribution of intraday returns as a predictor.

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Dr Alfonso Dufour

Dr Alfonso Dufour

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Article

Time varying price discovery

Avino, D. , Lazar, E. and Varotto, S. (2015) Time varying price discovery. Economics Letters, 126. pp. 18-21. ISSN 0165-1765 doi: 10.1016/j.econlet.2014.09.030

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We show how multivariate GARCH models can be used to generate a time-varying “information share” (Hasbrouck, 1995) to represent the changing patterns of price discovery in closely related securities. We find that time-varying information shares can improve credit spread predictions.

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Dr Simone Varotto

Dr Simone Varotto

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Article

Price discovery of credit spreads in tranquil and crisis periods

Avino, D. , Lazar, E. and Varotto, S. (2013) Price discovery of credit spreads in tranquil and crisis periods. International Review of Financial Analysis, 30. pp. 242-253. ISSN 1057-5219 doi: 10.1016/j.irfa.2013.08.002

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In this paper we investigate the price discovery process in single-name credit spreads obtained from bond, credit default swap (CDS), equity and equity option prices. We analyse short term price discovery by modelling daily changes in credit spreads in the four markets with a vector autoregressive model (VAR). We also look at price discovery in the long run with a vector error correction model (VECM). We find that in the short term the option market clearly leads the other markets in the sub-prime crisis (2007-2009). During the less severe sovereign debt crisis (2009-2012) and the pre-crisis period, options are still important but CDSs become more prominent. In the long run, deviations from the equilibrium relationship with the option market still lead to adjustments in the credit spreads observed or implied from other markets. However, options no longer dominate price discovery in any of the periods considered. Our findings have implications for traders, credit risk managers and financial regulators.

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Dr Simone Varotto

Dr Simone Varotto

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Article

Forecasting VaR using analytic higher moments for GARCH processes

Alexander, C. , Lazar, E. and Stanescu, S. (2013) Forecasting VaR using analytic higher moments for GARCH processes. International Review of Financial Analysis, 30. pp. 36-45. ISSN 1057-5219 doi: 10.1016/j.irfa.2013.05.006

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It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency of the GARCH model, such predictions have typically required time-consuming simulations of the aggregated returns distributions. This paper shows that fast, quasi-analytic GARCH VaR calculations can be based on new formulae for the first four moments of aggregated GARCH returns. Our extensive empirical study compares the Cornish–Fisher expansion with the Johnson SU distribution for fitting distributions to analytic moments of normal and Student t, symmetric and asymmetric (GJR) GARCH processes to returns data on different financial assets, for the purpose of deriving accurate GARCH VaR forecasts over multiple horizons and significance levels.

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Article

Futures basis, inventory and commodity price volatility: an empirical analysis

Symeonidis, L., Prokopczuk, M. , Brooks, C. and Lazar, E. (2012) Futures basis, inventory and commodity price volatility: an empirical analysis. Economic Modelling, 29 (6). pp. 2651-2663. ISSN 0264-9993 doi: 10.1016/j.econmod.2012.07.016 (http://www.sciencedirect.com/science/journal/02649993)

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We employ a large dataset of physical inventory data on 21 different commodities for the period 1993–2011 to empirically analyze the behavior of commodity prices and their volatility as predicted by the theory of storage. We examine two main issues. First, we analyze the relationship between inventory and the shape of the forward curve. Low (high) inventory is associated with forward curves in backwardation (contango), as the theory of storage predicts. Second, we show that price volatility is a decreasing function of inventory for the majority of commodities in our sample. This effect is more pronounced in backwardated markets. Our findings are robust with respect to alternative inventory measures and over the recent commodity price boom.

Professor Marcel Prokopczuk, CFA

Professor Marcel Prokopczuk, CFA

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Professor Chris Brooks

Professor Chris Brooks

Deputy Head of Department

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Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Article

Modelling regime-specific stock price volatility

Alexander, C. and Lazar, E. (2009) Modelling regime-specific stock price volatility. Oxford Bulletin of Economics and Statistics, 71 (6). pp. 761-797. ISSN 1468-0084 doi: 10.1111/j.1468-0084.2009.00563.x

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Article

Option valuation with normal mixture GARCH models

Badescu, A., Kulperger, R. and Lazar, E. (2008) Option valuation with normal mixture GARCH models. Studies in nonlinear dynamics & econometrics, 12 (2). 5. ISSN 1558-3708 doi: 10.2202/1558-3708.1580

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Article

Normal mixture GARCH(1,1): applications to exchange rate modelling

Alexander, C. and Lazar, E. (2006) Normal mixture GARCH(1,1): applications to exchange rate modelling. Journal of Applied Econometrics, 21 (3). pp. 307-336. ISSN 1099-1255 doi: 10.1002/jae.849

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Conference or Workshop Item

Time aggregation of normal mixture GARCH models

Alexander, C. and Lazar, E. (2004) Time aggregation of normal mixture GARCH models. In: Second international IASTED conference on financial engineering and applications, 8-10 November, 2004, Massachusetts Institute of Technology, Cambridge, USA.

Dr Emese Lazar

Dr Emese Lazar

Programme Director: MSc Financial Engineering

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Taught modules

Market Risk

The purpose of the module is to provide an understanding of the latest developments in banking regulations that are the main driving force behind changes in our approaches to risk measurement. It focuses on the foundations of market risk analysis and the basic models for assessing market risk.…

The purpose of the module is to provide an understanding of the latest developments in banking regulations that are the main driving force behind changes in our approaches to risk measurement. It focuses on the foundations of market risk analysis and the basic models for assessing market risk.…

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Derivatives Modelling

The module is designed to provide an introduction to the models and pricing of interest rates and credit derivatives. It conveys the basic concepts and analytical methodology for the valuation of derivatives in the standard Black-Scholes framework. It also builds awareness of the mathematical…

The module is designed to provide an introduction to the models and pricing of interest rates and credit derivatives. It conveys the basic concepts and analytical methodology for the valuation of derivatives in the standard Black-Scholes framework. It also builds awareness of the mathematical…

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News & Media Appearances

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