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Marius Matei

Personal Details

First Name:Marius
Middle Name:
Last Name:Matei
Suffix:
RePEc Short-ID:pma1184
[This author has chosen not to make the email address public]
https://mateimar.wixsite.com/website
National Bank of Romania, Financial Stability Department, Systemic Risk Monitoring Division, Strada Lipscani nr. 25, sector 3, Bucharest, 030031, Romania
+40799248222

Affiliation

(47%) Centrul de Modelare Macroeconomica
Institutul National de Cercetari Economice (INCE)
Academia Romana

Bucureşti, Romania
http://www.ipe.ro/CentrulModelareMacroeconomica/
RePEc:edi:cmrarro (more details at EDIRC)

(47%) Banca Nationala a Romaniei

Bucureşti, Romania
http://www.bnro.ro/
RePEc:edi:bnrgvro (more details at EDIRC)

(6%) Department of Economics
Business School
Macquarie University

Sydney, Australia
https://www.mq.edu.au/macquarie-business-school/our-departments/department-of-economics
RePEc:edi:edmqqau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Dungey, Mardi & Luciani, Matteo & Matei, Marius & Veredas, David, 2015. "Surfing through the GFC: systemic risk in Australia," Working Papers 2015-01, University of Tasmania, Tasmanian School of Business and Economics.
  2. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
  3. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
  4. Matei, Marius, 2009. "Analiza riscului în evaluarea oportunitatilor internationale de investitii. Perspective în modelarea si previzionarea volatilitatii utilizate în estimarea riscului," Working Papers of Macroeconomic Modelling Seminar 092101, Institute for Economic Forecasting.

Articles

  1. Marius Matei & Xari Rovira & Núria Agell, 2019. "Bivariate Volatility Modeling with High-Frequency Data," Econometrics, MDPI, vol. 7(3), pages 1-15, September.
  2. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
  3. Matei, Marius, 2012. "Perspectives on risk measurement: a critical assessment of PC-GARCH against the main volatility forecasting models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 95-115, March.
  4. Huang, Wen & Huang, Zhuo & Matei, Marius & Wang, Tianyi, 2012. "Price Volatility Forecast for Agricultural Commodity Futures: The Role of High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 83-103, December.
  5. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
  6. Matei, Marius, 2009. "Assessing Volatility Forecasting Models: Why GARCH Models Take the Lead," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 42-65, December.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Dungey, Mardi & Luciani, Matteo & Matei, Marius & Veredas, David, 2015. "Surfing through the GFC: systemic risk in Australia," Working Papers 2015-01, University of Tasmania, Tasmanian School of Business and Economics.

    Cited by:

    1. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost, Tomáš, 2020. "Increasing systemic risk during the Covid-19 pandemic: A cross-quantilogram analysis of the banking sector," EconStor Preprints 222580, ZBW - Leibniz Information Centre for Economics.
    2. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," Economic Modelling, Elsevier, vol. 109(C).
    3. Christina Bui, 2018. "Bank Regulation and Financial Stability," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2018.
    4. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    5. Rahman, Md Lutfur & Troster, Victor & Uddin, Gazi Salah & Yahya, Muhammad, 2022. "Systemic risk contribution of banks and non-bank financial institutions across frequencies: The Australian experience," International Review of Financial Analysis, Elsevier, vol. 79(C).
    6. Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
    7. Rösch, Daniel & Scheule, Harald, 2016. "The role of loan portfolio losses and bank capital for Asian financial system resilience," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 289-305.
    8. Raisul Islam & Vladimir Volkov, 2022. "Contagion or interdependence? Comparing spillover indices," Empirical Economics, Springer, vol. 63(3), pages 1403-1455, September.
    9. Xin Yan & Min Chen & Mu-Yen Chen, 2019. "Coupling and Coordination Development of Australian Energy, Economy, and Ecological Environment Systems from 2007 to 2016," Sustainability, MDPI, vol. 11(23), pages 1-13, November.
    10. Bui, Christina & Scheule, Harald & Wu, Eliza, 2017. "The value of bank capital buffers in maintaining financial system resilience," Journal of Financial Stability, Elsevier, vol. 33(C), pages 23-40.
    11. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    12. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2018. "Systemic risk in the US: Interconnectedness as a circuit breaker," Economic Modelling, Elsevier, vol. 71(C), pages 305-315.
    13. Van Cauwenberge, Annelies & Vancauteren, Mark & Braekers, Roel & Vandemaele, Sigrid, 2019. "International trade, foreign direct investments, and firms’ systemic risk : Evidence from the Netherlands," Economic Modelling, Elsevier, vol. 81(C), pages 361-386.

  2. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.

    Cited by:

    1. Mardi Dungey & Marius Matei & Matteo Luciani & David Veredas, 2017. "Surfing through the GFC: Systemic Risk in Australia," The Economic Record, The Economic Society of Australia, vol. 93(300), pages 1-19, March.
    2. Pattanaporn Chatjuthamard & Pavitra Jindahra & Pattarake Sarajoti & Sirimon Treepongkaruna, 2021. "The effect of COVID‐19 on the global stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4923-4953, September.

Articles

  1. Marius Matei & Xari Rovira & Núria Agell, 2019. "Bivariate Volatility Modeling with High-Frequency Data," Econometrics, MDPI, vol. 7(3), pages 1-15, September.

    Cited by:

    1. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021. "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 489-502.
    2. Kumar SANTOSH & Meher Kumar BHARAT & Ramona BIRAU & Mircea Laurentiu SIMION & Anand ABHISHEK & Singh MANOHAR, 2023. "Quantifying Long-Term Volatility for Developed Stock Markets: An Empirical Case Study Using PGARCH Model on Toronto Stock Exchange (TSX)," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-68.

  2. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.

    Cited by:

    1. Deniz Erdemlioglu & Nikola Gradojevic, 2020. "Heterogeneous investment horizons, risk regimes, and realized jumps," Post-Print hal-02995997, HAL.
    2. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2020. "Volatility Forecasting in European Government Bond Markets," Essex Finance Centre Working Papers 27362, University of Essex, Essex Business School.
    3. McMahon, Michael & Ahrens, Maximilian & Erdemlioglu, Deniz & Neely, Christopher J & Yang, Xiye, 2023. "Mind Your Language: Market Responses to Central Bank Speeches," CEPR Discussion Papers 18191, C.E.P.R. Discussion Papers.
    4. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    5. Bryan Lim & Stefan Zohren & Stephen Roberts, 2020. "Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio," Papers 2002.02008, arXiv.org, revised Sep 2020.
    6. Leong, Minhao & Kwok, Simon, 2023. "The pricing of jump and diffusive risks in the cross-section of cryptocurrency returns," Journal of Empirical Finance, Elsevier, vol. 74(C).
    7. A E Clements & A S Hurn & K A Lindsay & V Volkov, 2023. "Estimating a Non-parametric Memory Kernel for Mutually Exciting Point Processes," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1759-1790.
    8. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    9. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis.
    10. Boswijk, H. Peter & Laeven, Roger J.A. & Yang, Xiye, 2018. "Testing for self-excitation in jumps," Journal of Econometrics, Elsevier, vol. 203(2), pages 256-266.
    11. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).
    12. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    13. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    14. Zhang, Chuanhai & Liu, Zhi & Liu, Qiang, 2021. "Jumps at ultra-high frequency: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    15. Mardi Dungey & Jet Holloway & Abdullah Yalaman & Wenying Yao, 2022. "Characterizing financial crises using high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 22(4), pages 743-760, April.
    16. Guangying Liu & Meiyao Liu & Jinguan Lin, 2022. "Testing the volatility jumps based on the high frequency data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 669-694, September.

  3. Matei, Marius, 2012. "Perspectives on risk measurement: a critical assessment of PC-GARCH against the main volatility forecasting models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 95-115, March.

    Cited by:

    1. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.

  4. Huang, Wen & Huang, Zhuo & Matei, Marius & Wang, Tianyi, 2012. "Price Volatility Forecast for Agricultural Commodity Futures: The Role of High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 83-103, December.

    Cited by:

    1. Dejan Živkov & Marijana Joksimović & Suzana Balaban, 2021. "Measuring parametric and semiparametric downside risks of selected agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(8), pages 305-315.
    2. Dejan Živkov & Boris Kuzman & Jonel Subić, 2020. "What Bayesian quantiles can tell about volatility transmission between the major agricultural futures?," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(5), pages 215-225.
    3. Sanusi, Olajide I. & Safi, Samir K. & Adeeko, Omotara & Tabash, Mosab I., 2022. "Forecasting agricultural commodity price using different models: a case study of widely consumed grains in Nigeria," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 8(2), June.
    4. Dejan Živkov & Suzana Balaban & Marijana Joksimović, 2022. "Making a Markowitz portfolio with agricultural commodity futures," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(6), pages 219-229.

  5. Matei, Marius, 2009. "Assessing Volatility Forecasting Models: Why GARCH Models Take the Lead," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 42-65, December.

    Cited by:

    1. Dhanya Jothimani & Ravi Shankar & Surendra S. Yadav, 2016. "Discrete Wavelet Transform-Based Prediction of Stock Index: A Study on National Stock Exchange Fifty Index," Papers 1605.07278, arXiv.org.
    2. Lin, Xiaoqiang & Fei, Fangyu, 2013. "Long memory revisit in Chinese stock markets: Based on GARCH-class models and multiscale analysis," Economic Modelling, Elsevier, vol. 31(C), pages 265-275.
    3. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
    4. Ahmad Muslim, 2014. "Analyzing volatility of rice price in Indonesia using ARCH/GARCH model," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 6(1), pages 1-12, April.
    5. Subashini Maniam & Chin Lee, 2018. "Stock Market Liberalization Impact on Sectoral Stock Market Return in Malaysia," Capital Markets Review, Malaysian Finance Association, vol. 26(2), pages 21-31.
    6. Tristan Nguyen & Thi Thanh Mai Bui, 2018. "Modeling the Volatility and Forecasting the Stock Price of the German Stock Index (DAX30)," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 4(4), pages 72-92, 04-2018.
    7. Nieto, María Rosa & Carmona-Benítez, Rafael Bernardo, 2018. "ARIMA + GARCH + Bootstrap forecasting method applied to the airline industry," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 1-8.
    8. Abokyi, Emmanuel & Asiedu, Kofi Fred, 2021. "Agricultural policy and commodity price stabilisation in Ghana: The role of buffer stockholding operations," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 16(4), December.
    9. Krzysztof DRACHAL, 2015. "The Structural Stability of a One-Day Risk Premium in View of the Recent Financial Crisis," Expert Journal of Economics, Sprint Investify, vol. 3(2), pages 136-142.
    10. Charalampos Basdekis & Apostolos Christopoulos & Alexandros Gkolfinopoulos & Ioannis Katsampoxakis, 2022. "VaR as a risk management framework for the spot and futures tanker markets," Operational Research, Springer, vol. 22(4), pages 4287-4352, September.
    11. Muhammad Ahsanuddin & Tayyab Raza Fraz & Samreen Fatima, 2019. "Studying the Volatility of Pakistan Stock Exchange and Shanghai Stock Exchange Markets in the Light of CPEC: An Application of GARCH and EGARCH Modelling," International Journal of Sciences, Office ijSciences, vol. 8(03), pages 125-132, March.
    12. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-RMG: Risk Management (2) 2010-03-13 2016-01-29
  2. NEP-BAN: Banking (1) 2016-01-29
  3. NEP-IAS: Insurance Economics (1) 2016-01-29
  4. NEP-MON: Monetary Economics (1) 2016-02-04
  5. NEP-MST: Market Microstructure (1) 2016-02-04
  6. NEP-ORE: Operations Research (1) 2010-03-13
  7. NEP-SEA: South East Asia (1) 2016-02-04

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