MARIUS MATEI
Principal Economist at the National Bank of Romania (Financial Stability Department) and Senior Researcher at the National Institute for Economic Research, Romanian Academy.
Publications in Journal of Econometrics, Journal of International Financial Markets, Institutions & Money, Economic Record and Econometrics journals. PhD in Financial Econometrics (ESADE Business School) and in Economics (National Institute for Economic Research). Postdoc at the University of Tasmania. Master in Economics (Carleton University), Finance (ESADE Business School). Visiting researcher at Stanford University and CREATES (Århus University). Extensive teaching experience at undergraduate, honours, Master and MBA levels in Australia, Spain, Canada and Romania.
PROFILE SUMMARY
Current affiliation: National Bank of Romania (Financial Stability Department, Systemic Risk Monitoring Division) and National Institute for Economic Research (Romanian Academy)
I am a financial econometrician and active researcher in the econometrics of high frequency data and systemic risk fields. I have published in the Journal of Econometrics, Journal of International Financial Markets, Institutions & Money, Economic Record and Econometrics journals. Two PhD degrees, at ESADE Business School and at the National Institute for Economic Research | Romanian Academy. Master in Economics at Carleton University, Master in Finance at ESADE Business School.
Research interests: macroeconomics, banking and econometric modelling of high frequency data, with a focus on volatility, systemic risk, financial crises, contagion and financial flights. My main applications are in financial econometrics and macroeconomics.
Teaching interests: Econometrics, Economics, Statistics, Finance, Management, Matlab and EViews
RESEARCH
Relevant published papers:
2020 Examining stress in Asian currencies: A perspective offered by high frequency financial market data (authors: Dungey Mardi, Matei Marius & Treepongkaruna Sirimon) | Journal of International Financial Markets, Institutions & Money | 67 (101200), 1-18.
Link: https://authors.elsevier.com/a/1bPqW3j1YpubCk
2019 Bivariate Volatility Modelling with High Frequency Data (authors: Matei Marius, Rovira Xari & Agell Nuria) | Econometrics | 7(3), 41
2018 Testing for mutually exciting jumps and financial flights in high frequency data (authors: Dungey Mardi, Erdemlioglu Deniz, Matei Marius & Yang Xiye) | Journal of Econometrics | 202(2018), Vol 18-44
2017 Surfing through the GFC: systemic risk in Australia (authors: Dungey Mardi, Luciani Matteo, Matei Marius & Veredas David) | Economic Record | Vol 93(300)
Other published papers | Book chapters:
2012 Price volatility forecast for agricultural commodity futures: the role of high frequency data (authors: Matei Marius, Huang Wen, Huang Zhuo & Wang Tianyi) | Romanian Journal for Economic Forecasting | Vol 15(4)
2012 Perspectives on risk measurement-a critical assessment of PC-GARCH against the main volatility forecasting models (author: Matei Marius) | Romanian Journal for Economic Forecasting | Vol.15(1)
2011 Non-linear volatility modelling of economic and financial time series using high frequency data (author: Matei Marius) |Romanian Journal for Economic Forecasting | Vol. 14(2), 2011. Also book chapter in ‘Non-Linear Modelling in Economics - Beyond Standard Economics’, Expert: Bucharest, 2011
2009 Assessing volatility forecasting models: why GARCH models take the lead (author: Matei Marius) | Romanian Journal for Economic Forecasting | Vol.12(4)
2012 Techniques of forecasting volatility an returns of high frequency time series. Macro-micro binomial from the data aggregation and synthetising perspective (author: Matei Marius), Expert: Bucharest, ISBN 978-973-618-380-5
2015 Modelling and measuring jumps in high frequency data (author: Matei Marius); book chapter in ‘Selected issues in macroeconomic and regional modelling: Romania an emerging country in EU’, Nova Science Publishers: NY, ISBN 978-1-63484-936-4
2011 Non-linear Volatility Modelling of Economic and Financial Time Series Using High Frequency Data (author: Matei Marius); book chapter in ‘Non-Linear Modelling in Economics - Beyond Standard Economics’, Expert: Bucharest, ISBN 978-973-618-260-0
Submitted articles:
Volatility During the Financial Crisis Through the Lens of High Frequency Data: A Realized GARCH Approach | Banulescu G. D., Hansen P. R., Matei M. & Huang Z. | revise and resubmit at Journal of Banking & Finance
Working Papers:
Notes on FX Global Intensities | Dungey M., Matei M. & Novotný J.
Impact of Illiquidity in Identification of Financial Stress Periods: A Simulation Approach | Dungey M., Matei M. & Treepongkaruna S.
Financial Modelling with Cryptocurrencies High Frequency Data | Matei M. & George M.
PUBLICATIONS
EXAMINING STRESS IN ASIAN CURRENCIES: A PERSPECTIVE OFFERED BY HIGH FREQUENCY FINANCIAL MARKET DATA
Authors: Dungey Mardi, Matei Marius and Treepongkaruna Sirimon
Journal of International Financial Markets, Institutions & Money (2020) | Volume 67 (101200), pp. 1-18. Link: https://authors.elsevier.com/a/1bPqW3j1YpubCk
Abstract: By harnessing the changes in jump behavior of high frequency currency market data we construct a means of detecting stress dates in exchange rates. Using 5-min data for Asian currencies covering more than 20 years from 1996 to 2018 we align the identified stress dates to domestic and international economic and political events or exchange rate management actions. Each currency has distinctive characteristics, particularly evident with political turmoil and exchange rate management. While we find some evidence that liquidity is related to financial stress, cross-country results show that increased liquidity does not dramatically contribute to the identification of a stressful episode.
BIVARIATE VOLATILITY MODELLING WITH HIGH-FREQUENCY DATA
Authors: Matei Marius, Rovira Xari and Agell Núria
Econometrics (2019) | 7(3), 41
Abstract: We propose a methodology to include night volatility estimates in the day volatility modeling problem with high-frequency data in a realized generalized autoregressive conditional heteroskedasticity (GARCH) framework, which takes advantage of the natural relationship between the realized measure and the conditional variance. This improves volatility modeling by adding, in a two-factor structure, information on latent processes that occur while markets are closed but captures the leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that includes intraday, day, and night volatility estimates is proposed and was empirically tested to confirm whether using night volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate models over those that do not include night volatility estimates.
TESTING FOR MUTUALLY EXCITING JUMPS AND FINANCIAL FLIGHTS IN HIGH FREQUENCY DATA
Authors: Dungey Mardi, Erdemlioglu Deniz, Matei Marius & Yang Xiye
Journal of Econometrics (2018) | Vol . 202(2018), 18-44
Abstract: We propose a new nonparametric test to identify mutually exciting jumps in high frequency data. We derive the asymptotic properties of the test statistics and show that the tests have good size and reasonable power in finite sample cases. Using our mutual excitation tests, we empirically characterize the dynamics of financial flights in forms of flight-to-safety and flight-to-quality. The results indicate that mutually exciting jumps and risk-off trades mostly occur in periods of high market stress. Flight-to- safety episodes (from stocks to gold) arrive more frequently than do flight-to-quality spells (from stocks to bonds). We further find evidence that reverse cross-excitations or seeking-return-strategies exhibit significant asymmetry over the business cycle, reflecting the fact that investors appear to be selling gold – rather than bonds – to invest in stocks during good market conditions.
SURFING THROUGH THE GFC: SYSTEMIC RISK IN AUSTRALIA
Authors: Dungey Mardi, Luciani Matteo, Marius Matei, Veredas David
Economic Record (2017) | Vol 93(300)
Abstract: We provide empirical evidence on the degree of systemic risk in Australia before, during and after the global financial crisis. We calculate a daily index of systemic risk from 2004 to 2013 in order to understand how real economy firms influence the outcomes for the rest of the economy. This is done via a mapping of the intercon- nectedness of the financial and non-financial sectors. The financial sector is in general home to the most consistently systemically risky firms in the economy. The materials sector occasionally becomes as systemically risky as the financial sector, reflecting the importance of understanding these linkages.
PRICE VOLATILITY FORECAST FOR AGRICULTURAL COMMODITY FUTURES: THE ROLE OF HIGH FREQUENCY DATA
Authors: Huang Wen, Huang Zhuo, Matei Marius, Wang Tianyi
Romanian Journal of Economic Forecasting (2012) | Vol 15(4)
Abstract: Realized measures of volatility based on high frequency data contain valuable information about the unobserved conditional volatility. In this paper, we use the Realized GARCH model developed by Hansen, Huang and Shek (2012) to estimate and forecast price volatility for four agricultural commodity futures. Empirical evidences, both in-sample and out-of-sample, show that the Realized GARCH model and its variants outperform the conventional volatility models that only use daily price data, such as GARCH and EGARCH. We also consider skewed student’s t-distribution to account for the skewness and fat-tail in the agricultural futures prices. The empirical performances are relatively close for models using three different realized measures, as the measurement equation in the Realized GARCH model can adjust to the different realized measures to some extent.
PERSPECTIVES ON RISK MEASUREMENT - A CRITICAL ASSESSMENT OF PC-GARCH AGAINST THE MAIN VOLATILITY FORECASTING MODELS
Author: Marius Matei
Romanian Journal of Economic Forecasting (2012) | Vol.15(1)
Abstract: The paper makes a critical assessment of the Principal Components-GARCH (PCGARCH) model and argues why, when dealing with hundreds or thousands of variables, this model comes up as the most appropriate to be used. The suitability originates from the perspective of quality/cost ratio of volatility forecasts, allowing for a trade-off between quality and costs when computational efforts are significant. PCGARCH not only provides a method that allows for simpler volatility modeling, reducing significantly the computational time and getting rid of any problem that may arise from complex data manipulations, but also improves the modeling process quality by ensuring a stricter control of noise due to more stable correlation estimates.
NON-LINEAR VOLATILITY MODELLING OF ECONOMIC AND FINANCIAL TIME SERIES USING HIGH FREQUENCY DATA
Author: Matei Marius
Romanian Journal of Economic Forecasting (2011) | Vol. 14(2), also book chapter in ‘Non-Linear Modelling in Economics - Beyond Standard Economics’, Expert: Bucharest, 2011
Abstract: The current work undertakes an overview of the forecasting volatility with high frequency data topic, attempting to answer to the fundamental latency problem of return volatility. It surveys the most relevant aspects of the volatility topic, suggesting advantages and disadvantages of each alternative in modeling. It reviews the concept of realized volatility and explains why forecasting of volatility is more effective when the model contains a measure of intraday data. A discrete and a continuous time model are defined. Sampling methods at different frequencies are reviewed, and the impact of microstructure noise is considered. Details on procedures employed in the literature with respect to modeling and forecasting using realized models are discussed, while an empirical exercise will prove the advantages of using measures of high frequency data.
ASSESSING VOLATILITY FORECASTING MODELS: WHY GARCH MODELS TAKE THE LEAD
Authors: Matei Marius
Romanian Journal of Economic Forecasting (2009) | Vol.12(4)
Abstract: The paper provides a critical assessment of the main forecasting techniques and an evaluation of the superiority of the more advanced and complex models. Ultimately, its scope is to offer support for the rationale behind of an idea: GARCH is the most appropriate model to use when one has to evaluate the volatility of the returns of groups of stocks with large amounts (thousands) of observations. The appropriateness of the model is seen through a unidirectional perspective of the quality of volatility forecast provided by GARCH when compared to any other alternative model, without considering any cost component.
BOOKS AND BOOK CHAPTERS
TECHNIQUES OF FORECASTING VOLATILITY AND RETURNS OF HIGH FREQUENCY TIME SERIES. MACRO-MICRO BINOMIAL FROM THE DATA AGGREGATION AND SYNTHETISING PERSPECTIVE
2012
Authors: Matei Marius,
Expert Publishing Company: Bucharest, ISBN 978-973-618-380-5
MODELLING AND MEASURING JUMPS IN HIGH FREQUENCY DATA
2015
Authors: Matei Marius
Published in ‘Selected issues in macroeconomic and regional modelling: Romania an emerging country in EU’, Nova Science Publishers: NY, ISBN 978-1-63484-936-4
NON-LINEAR VOLATILITY MODELLING OF ECONOMIC AND FINANCIAL TIME SERIES USING HIGH FREQUENCY DATA
2011
Authors: Marius Matei
Published in ‘Non-Linear Modelling in Economics - Beyond Standard Economics’, Expert: Bucharest, ISBN 978-973-618-260-0
WORKING PAPERS
VOLATILITY DURING THE FINANCIAL CRISIS THROUGH THE LENS OF HIGH FREQUENCY DATA: A REALIZED GARCH APPROACH
Authors: Banulescu Georgiana, Hansen Peter Reinhard, Matei Marius & Huang Zhuo
Submitted to Journal of Banking & Finance
Abstract: We formally test that a process containing Brownian motion and jumps characterises the high frequency observations for eight Asian currencies against the US dollar. By harnessing the changes in behaviour of the data during periods of stress we explore evidence for detecting stress dates in the data. We align the identified stress dates to economic and political conditions using central bank and IMF reports on developments in currency markets. While there is some evidence that liquidity is related to financial stress, increased liquidity does not often dramatically increase the probability of a stressful episode.
IDENTIFYING PERIODS OF FINANCIAL STRESS IN ASIAN CURRENCIES: THE ROLE OF HIGH FREQUENCY FINANCIAL MARKET DATA
Authors: Dungey Mardi, Matei Marius & Treepongkaruna Sirimon
Submitted to the Journal of International Financial Markets, Institutions & Money
Abstract: We study financial volatility during the Global Financial Crisis and use the largest volatility shocks to identify major events during the crisis. Our analysis makes extensive use of high-frequency financial data to model volatility and to determine the timing within the day when the largest volatility shocks occurred. The latter helps us identify the events that may be associated with each of these shocks, and serves to illustrate the benefits of using high-frequency data. Some of the largest volatility shocks coincide, not surprisingly, with the bankruptcy of Lehman Brothers on September 15, 2008 and Congress’s failure to pass the Emergency Economic Stabilization Act on September 29, 2008. Yet, the largest volatility shock was on February 27, 2007, the date when Freddie Mac announced a stricter policy for underwriting subprime loans and a date that was marked by a crash on the Chinese stock market. However, the intraday high-frequency data shows that the main culprit was a computer glitch in the trading system. The days with the largest drops in volatility can in most cases be related to interventions by governments and central banks.
NOTES ON FX GLOBAL INTENSITIES
Authors: Dungey Mardi, Matei Marius & Novotný Jan
Abstract: In this paper we aim to understand the dynamics of the multivariate intensity processes in the global foreign exchange markets. In particular, we are interested in the causal flows across the FX markets and in the patterns of the contagion on the global markets. The paper documents which are the country specific/common factors which trigger jumps in exchange rates as expressed by the jump intensities, which are the channels of propagation of jumps/jump intensities and if there is a time dynamic map of jumps’ transmission between currencies when a shock occurs. Other research questions are: does a currency crisis (as endogenously identified using standard methods) overlap with an economic crisis, do jumps spread faster during crisis vs. non crisis and do their patterns differ between the two periods?
IMPACT OF ILLIQUIDITY IN IDENTIFICATION OF FINANCIAL STRESS PERIODS: A SIMULATION APPROACH
Authors: Dungey Mardi, Matei Marius and Treepongkaruna Sirimon
Abstract: What happens to identification of financial stress periods techniques when asset returns violate the assumption of Brownian motion? This paper represents an application of Erdemlioglu, Laurent and Neely (2013) methodology to illiquid markets (most of them emerging markets). Based on data simulations we prove that illiquidity and discreteness often met in emerging markets violate the standard detection techniques used for identifying Brownian motion and jumps. As well, by simulating data we obtain better critical values in identifying stress dates.
FINANCIAL MODELLING WITH CRYPTOCURRENCIES HIGH FREQUENCY DATA
Authors: Matei Marius and George Milunovich
ACADEMIC WORK EXPERIENCE
My Career
LECTURER IN FINANCIAL ECONOMETRICS
2019 - 2020
Bucharest University of Economic Studies | School of Finance and Banking | Department of Money and Banking | Romania
I am currently the lecturer and unit convenor of the ‘Financial Econometrics’ master level course, teaching both the course and the tutorials, and am scheduled to teach the ‘Advanced Financial Econometrics’ course in the second semester of the 2019-2020 academic year. The courses are part of the Master of Advanced Research in Finance CEFIN at the Faculty of Finance and Banking, Bucharest University of Economic Studies.
SESSIONAL ACADEMIC
2017 - 2019
Macquarie University | Macquarie Business School | Australia
Teaching: Financial Econometrics; Economic and Business Forecasting, Quantitative Methods in Economics, Business and Finance | Research in Econometrics field
SENIOR RESEARCHER, GRADE 1
2018 - present
Romanian Academy | National Institute for Economic Research | Romania
SESSIONAL ACADEMIC
2017
University of New South Wales · UNSW Business School · Australia
I taught tutorials and marked exams for the Financial Econometrics course ECON 3206 (undergrad level)/ECON 5206 (Master level). Topics: linear regression model, univariate time series analysis (ARMA), non stationary time series (stationarity and unit-root), long-run relationships (cointegration, VEC), multivariate time series analysis (VAR), risk and volatility analysis (ARCH, GARCH), simulation methods
POSTDOCTORAL RESEARCH FELLOW IN FINANCIAL ECONOMETRICS | LECTURER
2012 - 2015
Tasmanian School of Business and Economics | University of Tasmania · Australia
Research on modelling, detecting and forecasting financial volatility, systemic risk, financial crises and financial contagion with high frequency data, with relevance on financial markets’ risk assessment. Mentor: Prof. Mardi Dungey. Employed in two projects:
▫ ‘Detecting Financial Contagion Using High Frequency Data’, granted by the Australian Research Council. Achievements: 2 papers submitted to A journals and one to an A* journal
▫ ‘Detecting Systemically Important Risk’, granted by the Australian Centre for International Finance and Regulation. Achievements: 2 papers submitted to A journals, one published in an A journal
Courses taught: Honours ‘Finance’ (486/475);‘Principles of Economics 2’ (121)
LECTURER/ADJUNCT FACULTY MEMBER
2009, 2011
UIBS United International Business Schools (Barcelona and Valencia campuses) · Spain
Courses taught: ▫ ‘Cost, Volume, Profit Analysis’ (one MBA level course); ▫ ‘Production Management’ (four MBA level courses); ▫ ‘Total Quality Management’ (one undergraduate level course)
RESEARCH FELLOW IN FINANCE
2008 - 2012
ESADE Business School | Ramon Llull University · Spain
Research in two projects:
▫‘Updates in volatility forecasting using high frequency data. A new benchmark analysis of models’
▫‘Financial reporting, ownership structure and quotes on the Spanish stock exchange’
POSTDOCTORAL RESEARCH FELLOW IN ECONOMICS
2010 - 2012
National Institute for Economic Research | Romanian Academy · Romania
Research on the topic of volatility modelling with high frequency data
TEACHING ASSISTANT
2006 - 2007
Carleton University, Department of Economics · Canada
Tutorials taught: Microeconomics, Public Finance, Statistics, Statistical Methods in Economics and Business, Intermediate Macroeconomics, Economic Perspectives on Climate Change
NON-ACADEMIC WORK EXPERIENCE
PRINCIPAL ECONOMIST
2019 - present
National Bank of Romania | Financial Stability Department | Systemic Risk Monitoring Division
SENIOR ECONOMIST
2019
Markets and Regulation | Office of Environment and Heritage | New South Wales Government | Australia
SENIOR TECHNOLOGY CONSULTANT / DATA SCIENTIST
2018
BearingPoint
SENIOR QUANTITATIVE ANALYST (ASSET ALLOCATION)
2016
Mine Super | Australia
SENIOR ECONOMIST - HEAD OF MACROECONOMIC RESEARCH DEPARTMENT
2004 - 2005
UniCredit Bank | Member of UniCredit Group · Romania
▫ Managed macroeconomic research activity of the bank; ▫ Coordinated forecasting and analysis activity for strategic planning purposes; ▫ Assisted senior management in decision making process involving macroeconomic issues; ▫ Assisted trading department with economic research and forecasts; ▫ Delivered 3-year plan to the strategic planning and control department; ▫ Coordinated the White Book project; ▫ Provided sectorial analysis; ▫ Co-author of: Household wealth in New Europe: towards EU, Impact of an oil shock in the New Europe, Economic cycle in the New Europe: converging towards the EMU, Exchange rates dynamics towards the Euro, Household wealth monitor, New Europe biweekly monitor, New Europe Quarterly–Macroeconomic Update, Pension fund reform
FINANCIAL ANALYST - RISK MANAGEMENT DEPARTMENT
2002 - 2003
UniCredit Bank | Member of UniCredit Group · Romania
▫ Coordinated the risk management activities of the bank; ▫ Assessed the market risk, liquidity risk, FX risk, interest rate risk, VaR indicator, FX position, solvency; ▫ Calculated other risk indicators by employing the appropriate risk models ▫ Performed stress testing; ▫ Elaborated the bank’s principles and policies as regards risk management and control; ▫ Developed measurement systems and standards and monitored processes; ▫ Verified the compliance with approved principles and policies in the Group, by monitoring the established processes and by verifying the fairness of applied formulae
EDUCATION
PHD, ESADE BUSINESS SCHOOL | RAMON LLULL UNIVERSITY · SPAIN
2008 - 2012
PHD, NATIONAL INSTITUTE FOR ECONOMIC RESEARCH | ROMANIAN ACADEMY · ROMANIA
2002 - 2010
MRES, ESADE BUSINESS SCHOOL | RAMON LLULL UNIVERSITY · SPAIN
2007 - 2008
MA, CARLETON UNIVERSITY · CANADA
2006 - 2007
MASTER, NATIONAL UNIVERSITY FOR POLITICAL AND ADMINISTRATIVE STUDIES · ROMANIA
1999 - 2001
CERTIFICATE, ESSCA (ÉCOLE SUPÉRIEURE DES SCIENCES COMMERCIALES D’ANGERS) · FRANCE
1997
BACHELOR, UNIVERSITY OF ECONOMIC STUDIES · ROMANIA
1995 - 1999
CERTIFICATE IV IN PROGRAMMING | TAFE NSW · AUSTRALIA
2017 - 2019
ADDITIONAL ACADEMIC ACTIVITIES
AFFILIATIONS TO RESEARCH PROJECTS
2019 ‘Automating the Calculation of Dispersion and Skewness Measures of Across-Sectional Distributions in Matlab’ (with Dr. Ben Wang) | Macquarie University | Australia
2017 - 2019 ‘Financial Modelling with Cryptocurrencies High Frequency Data’(with Prof. George Milunovich) | Macquarie University | Australia
2018 - 2019 'Modelling Potential Output and Output Gap'| National Institute of Economic Research | Romanian Academy
2014 -2015 ‘Detecting Systemically Important Risk’ project granted by CIFR (together with Prof. Mardi Dungey, Prof. David Veredas and Dr. Matteo Luciani) | Australia
2012 - 2014 ‘Detecting Financial Contagion Using High Frequency Data’ project granted by the Australian Research Council (together with Prof. Mardi Dungey and Prof. Sirimon Treepongkaruna) | Australia
2012 ‘HEROM Structural Model Update’–CEROPE and National Institute for Economic Research | Romanian Academy | Poland
2012 ‘Studies on Theory and Applications of Volatility and Correlation Models Based on Realized GARCH Framework’ – with Prof. Zhuo Huang, National School of Development | Beijing University | China
2011 ‘Updates in Volatility Forecasting Using High Frequency Data. A New Benchmark Analysis of Models’ | ESADE Business School | Ramon Llull University | Spain
2009 - 2012 ‘Financial Reporting, Ownership Structure and Quotes on the Spanish Stock Exchange’, Research Project ECO2008 - 05218 | ESADE Business School | Ramon Llull University | Spain
2010 - 2012 ‘Revision of the Dobrescu Macro-model of the Romanian Economy’ - National Institute for Economic Research | Romanian Academy | Bucharest
2009 - 2010 ‘Methodologies on risk and uncertainty analysis, decision rules, statistical and mathematical methods and models, risk and uncertainty quantitative measurements’ | National Institute for Economic Research | Romanian Academy | Bucharest
CONFERENCE | SEMINAR PARTICIPATION
Dungey M., Matei M., Treepongkaruna S., ‘Identifying Periods of Financial Stress in Asian Currencies: The Role of High Frequency Financial Market Data’
▫ 25th New Zealand Econometrics Study Group Meeting, National Centre for Econometric Research | Queensland University of Technology | Brisbane | 2015
▫ Frontiers in Financial Econometrics Conference | Queensland University of Technology | Brisbane
▫ ESAM/ACE Conference (Econometric Society Australasian Meeting and Australian Conference of Economists) | Hobart | 2014
▫ 4th Emerging Markets Group Conference on Emerging Markets Finance | Cass Business School | City University | London | 2014
▫ Skewness, Heavy Tails, Market Crashes, and Dynamics Conference | Cambridge University and SoFiE | Cambridge | 2014
▫ Departmental Seminar | European University Institute | Department of Economics | Florence | 2014
▫ Macro-modelling Seminar | Institute for Economic Prognosis | Romanian Academy | Bucharest |2014
Matei M., Rovira X. & Agell N. ‘Bivariate Volatility Modelling with High Frequency Data’
▫ Econometric Society Australasian Meeting | Sydney | 2014
▫ FIRN (Financial Integrity Research Network) Annual Conference | Hobart | 2012
▫ The Econometric Society European Meeting | Malaga | 2012
Matei M., ‘Multivariate Volatility Modelling with High Frequency Data’
▫ Departmental Seminar | Center for Research in Econometric Analysis of Time Series (CREATES) | School of Economics and Management | Århus University | Denmark
Dungey M., Luciani M., Matei M., Veredas D., ‘Surfing through the GFC: Systemic Risk in Australia’
▫ Asset Allocation 2016 Conference | International Business Review Conference | Sydney | Australia
GRANTS
2014 Two Conference Travel Grants, Tasmanian School of Business and Economics, University of Tasmania (totalling $5228)
2013 CFA Institute Professor Scholarship
2009 - 2012 FI Grant, Generalitat de Catalunya, Spain
2009 Mobility Grant, Ministry of Education of Spain
2007 - 2008 ESADE scholarship, ESADE Business School, Spain
2006 - 2007 Domestic Student Tuition Scholarship, Carleton University, Canada
2006 - 2007 Departmental Scholarship, Carleton University, Canada
2002 Teaching Assistantship, École Supérieure des Sciences Commerciales d’Angers, France
1998 Scholarship, University of Economics and Business Administration, Austria
1995 - 1997 Study Scholarship, Academy of Economic Studies, Faculty of International Business, Romania
CONFERENCE | SEMINAR ORGANISATION
I have actively participated at the organisation of the ESAM / ACE Conference (Econometric Society Australasian Meeting and Australian Conference of Economists) which took place at the University of Tasmania, in Hobart, on 1-4.07.2014. I have reviewed and selected some of the submitted papers and I have participated to the program designing, to the organisation of the visiting programs for professors and researchers, as well to other related assignments. I have also chaired some of the sessions of the conference.
Organisation of the Young Research Workshop, Tasmanian School of Business and Economics, University of Tasmania, on 30.6.2014.
SUPERVISION OF PHD STUDENTS
Sayeed Mohammad & Biplob Chowdhury | Tasmanian School of Business and Economics, University of Tasmania
VISITING RESEARCH STAGES | SUMMER SCHOOLS
Center for Research in Econometric Analysis of Time Series (CREATES) | Århus University · Denmark
2011
CREATES Visiting Postdoc (3 months)
Research topic: Volatility modelling with high frequency data. Invited by Prof. Niels Haldrup
Stanford University | Department of Economics · USA
2010
Stanford University Visiting Scholar (3 months)
Research topic: Volatility modelling with high frequency data. Invited by Prof. Peter Reinhard Hansen
Oxford University · United Kingdom
2012
OMI (Oxford-Man Institute) - SoFiE (Society for Financial Econometrics) Financial Econometrics Summer School
NOVA University · Portugal
2009
Certificate, ‘New Advances in Modelling and Forecasting Volatility’ Summer School
University of Economics and Business Administration Vienna · Austria
1998
Certificate, International Summer Study Program. Specialisation: Management
University of Aix-en-Provence · France
1998
Summer University - L’Université D’Été de la Nouvelle Économie
MISCELLANEOUS
Check out my professional portfolio to find out what I’ve worked on. Here, you can find out how I approached my projects from concept to execution, and what skills I brought to the proverbial table that made these a real success. If any of these projects appeal to you, or you have a specific project in mind you’d like me to get involved in, give me a call today.
Certification
Certificate in Tutoring | Tutor Training Program
University of New South Wales · Australia
Certificate IV in Programming |
TAFE NSW · Australia
Referee Activity
Journal of Empirical Finance | European Journal of Operational Research | Computational Management Science | Australian Journal of the Agricultural and Resource Economics | Journal of Contemporary Accounting and Economics | Romanian Journal of Economic Forecasting
Computer Skills
Matlab | R | E-Views | SPSS | Visual Basic (VBA) | Excel | SQL | LyX | LaTex | Scientific WorkPlace | Power Point
Languages
English - fluent; Spanish, French, German – intermediate
CONFERENCES
‘IDENTIFYING PERIODS OF FINANCIAL STRESS IN ASIAN CURRENCIES: THE ROLE OF HIGH FREQUENCY FINANCIAL MARKET DATA’ (AUTHORS: DUNGEY M., MATEI M., TREEPONGKARUNA S.)
25th New Zealand Econometrics Study Group Meeting, National Centre for Econometric Research, Queensland University of Technology, Brisbane, 19-20.02.2015
Frontiers in Financial Econometrics Conference- Queensland University of Technology, Brisbane, 7-8.08.14
ESAM/ACE Conference (Econometric Society Australasian Meeting and Australian Conference of Economists), Hobart, 1-4.07.2014
4th Emerging Markets Group Conference on Emerging Markets Finance, Cass Business School, City University, London, 8-9.05.2014 (Here I also served as a discussant to one of the papers)
Skewness, Heavy Tails, Market Crashes, and Dynamics Conference, Cambridge University and SoFiE, Cambridge, 28-29.04.2014
Departmental Seminar at the European University Institute, Department of Economics, Florence, 6.5.2014
Macro-modelling Seminar, Institute for Economic Prognosis, Romanian Academy, Bucharest,13.05.2014
‘BIVARIATE VOLATILITY MODELLING WITH HIGH FREQUENCY DATA’ (AUTHORS: MATEI M., ROVIRA X. & AGELL N.)
Econometric Society Australasian Meeting, Sydney, 9-12.07.2014
FIRN (Financial Integrity Research Network) Annual Conference, Hobart, 9-11.11.2012
The Econometric Society European Meeting, Malaga, 27-31.8.2012
‘MULTIVARIATE VOLATILITY MODELLING WITH HIGH FREQUENCY DATA’ (AUTHOR: MATEI M.)
Departmental Seminar, Center for Research in Econometric Analysis of Time Series (CREATES), School of Economics and Management, Århus University, Denmark
‘SURFING THROUGH THE GFC: SYSTEMIC RISK IN AUSTRALIA’ (AUTHORS: DUNGEY M., LUCIANI M., MATEI M., VEREDAS D.)
Asset Allocation 2016 Conference, International Business Review Conference, Sydney, Australia
PROJECTS
‘AUTOMATING THE CALCULATION OF DISPERSION AND SKEWNESS MEASURES OF ACROSS-SECTIONAL DISTRIBUTIONS IN MATLAB’
2019
Affiliation with Dr. Ben Wang | Macquarie University | Australia
‘FINANCIAL MODELLING WITH CRYPTOCURRENCIES HIGH FREQUENCY DATA’
2017 - 2019
Associated with Prof. George Milunovich | Macquarie University | Australia
'MODELLING POTENTIAL OUTPUT AND OUTPUT GAP'
2018 - 2019
National Institute for Economic Research | Romanian Academy | Romania
‘DETECTING SYSTEMICALLY IMPORTANT RISK’
2014 - 2015
The project was granted by CIFR (Australian Centre for International Finance and Regulation) and was owned by Prof. Mardi Dungey, Prof. David Veredas and Dr. Matteo Luciani), Australia
‘DETECTING FINANCIAL CONTAGION USING HIGH FREQUENCY DATA’
2012 - 2014
The project granted by the Australian Research Council and was owned by Prof. Mardi Dungey and Prof. Sirimon Treepongkaruna
‘HEROM STRUCTURAL MODEL UPDATE’
2012
CEROPE and National Institute for Economic Research, Romanian Academy, Poland
‘STUDIES ON THEORY AND APPLICATIONS OF VOLATILITY AND CORRELATION MODELS BASED ON REALIZED GARCH FRAMEWORK’
2012
With Zhuo Huang, National School of Development, Beijing University, China
‘FINANCIAL REPORTING, OWNERSHIP STRUCTURE AND QUOTES ON THE SPANISH STOCK EXCHANGE’
2009 - 2012
Research Project ECO2008 - 05218, ESADE Business School, Ramon Llull University, Spain
‘REVISION OF THE DOBRESCU MACRO-MODEL OF THE ROMANIAN ECONOMY’
2010 - 2012
National Institute for Economic Research, Romanian Academy, Bucharest
‘METHODOLOGIES ON RISK AND UNCERTAINTY ANALYSIS, DECISION RULES, STATISTICAL AND MATHEMATICAL METHODS AND MODELS, RISK AND UNCERTAINTY QUANTITATIVE MEASUREMENTS’
2009 - 2010
National Institute for Economic Research, Romanian Academy
To discuss the projects I have worked on, contact me today.
"Do not go where the path may lead. Instead, go where there is no path and leave a trail"
