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Dimitris Dimitrakopoulos

Personal Details

First Name:Dimitris
Middle Name:
Last Name:Dimitrakopoulos
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RePEc Short-ID:pdi381
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Affiliation

Department of Accounting and Finance
Athens University of Economics and Business (AUEB)

Athens, Greece
https://www.dept.aueb.gr/loxri
RePEc:edi:dfauegr (more details at EDIRC)

Research output

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Jump to: Articles

Articles

  1. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.
  2. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 515-526, November.
  3. Manolis Kavussanos & Ilias Visvikis & Dimitris Dimitrakopoulos, 2010. "Information linkages between Panamax freight derivatives and commodity derivatives markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(1), pages 91-110, March.

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.

Articles

  1. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.

    Cited by:

    1. Bai, Xiwen & Lam, Jasmine Siu Lee, 2021. "Freight rate co-movement and risk spillovers in the product tanker shipping market: A copula analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    2. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    3. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
    4. Pouliasis, Panos K. & Papapostolou, Nikos C. & Kyriakou, Ioannis & Visvikis, Ilias D., 2018. "Shipping equity risk behavior and portfolio management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 178-200.
    5. Rui Manuel Dias & Nuno Teixeira & Pedro Pardal & Teresa Godinho, 2023. "Volatility Transmission Between ASEAN-5 Stock Exchanges: An Approach in the Context of China's Stock Market Crash," International Journal of Corporate Finance and Accounting (IJCFA), IGI Global, vol. 10(1), pages 1-17, January.
    6. 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.
    7. Abouarghoub, Wessam & Nomikos, Nikos K. & Petropoulos, Fotios, 2018. "On reconciling macro and micro energy transport forecasts for strategic decision making in the tanker industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 225-238.
    8. Javier Población & Gregorio Serna, 2021. "Measuring bulk shipping prices risk," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 291-309, June.

  2. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 515-526, November.

    Cited by:

    1. Karmakar, Madhusudan & Shukla, Girja K., 2015. "Managing extreme risk in some major stock markets: An extreme value approach," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 1-25.
    2. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
    3. Qiang Meng & Xiaobo Qu & Kum Thong Yong & Yoke Heng Wong, 2011. "QRA Model‐Based Risk Impact Analysis of Traffic Flow in Urban Road Tunnels," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1872-1882, December.
    4. Adeel Nasir & Kanwal Iqbal Khan & Mário Nuno Mata & Pedro Neves Mata & Jéssica Nunes Martins, 2021. "Optimisation of Time-Varying Asset Pricing Models with Penetration of Value at Risk and Expected Shortfall," Mathematics, MDPI, vol. 9(4), pages 1-38, February.
    5. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    6. Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
    7. Maciel, Leandro, 2021. "A new approach to portfolio management in the Brazilian equity market: Does assets efficiency level improve performance?," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 38-56.
    8. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    9. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    10. Bucevska Vesna, 2013. "An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange," Business Systems Research, Sciendo, vol. 4(1), pages 49-64, March.
    11. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
    12. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
    13. Ibrahim Ergen, 2015. "Two-step methods in VaR prediction and the importance of fat tails," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1013-1030, June.
    14. Ra l de Jes s-Guti rrez & Roberto J. Santill n-Salgado, 2019. "Conditional Extreme Values Theory and Tail-related Risk Measures: Evidence from Latin American Stock Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 127-141.
    15. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.

  3. Manolis Kavussanos & Ilias Visvikis & Dimitris Dimitrakopoulos, 2010. "Information linkages between Panamax freight derivatives and commodity derivatives markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(1), pages 91-110, March.

    Cited by:

    1. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    2. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    3. Yuting Gong & Xueqin Wang & Mo Zhu & Ying‐En Ge & Wenming Shi, 2023. "Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 69-89, January.
    4. Ziaul Haque Munim & Hans-Joachim Schramm, 2017. "Forecasting container shipping freight rates for the Far East – Northern Europe trade lane," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 106-125, March.
    5. Vangelis Tsioumas & Stratos Papadimitriou, 2018. "The dynamic relationship between freight markets and commodity prices revealed," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(2), pages 267-279, June.
    6. Maitra, Debasish & Rehman, Mobeen Ur & Dash, Saumya Ranjan & Kang, Sang Hoon, 2021. "Oil price volatility and the logistics industry: Dynamic connectedness with portfolio implications," Energy Economics, Elsevier, vol. 102(C).
    7. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
    8. Bai, Xiwen & Kavussanos, Manolis G., 2022. "Hedging IMO2020 compliant fuel price exposure using futures contracts," Energy Economics, Elsevier, vol. 110(C).
    9. Sun, Xiaolin & Haralambides, Hercules & Liu, Hailong, 2019. "Dynamic spillover effects among derivative markets in tanker shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 384-409.
    10. Arunava Bandyopadhyay & Prabina Rajib, 2023. "The asymmetric relationship between Baltic Dry Index and commodity spot prices: evidence from nonparametric causality-in-quantiles test," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 217-237, June.
    11. Maitra, Debasish & Chandra, Saurabh & Dash, Saumya Ranjan, 2020. "Liner shipping industry and oil price volatility: Dynamic connectedness and portfolio diversification," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    12. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    13. Regli, Frederik & Adland, Roar, 2019. "Crude oil contango arbitrage and the floating storage decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 100-118.
    14. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    15. Manolis Kavussanos & Siri Pettersen Strandenes & Helen Thanopoulou, 2022. "Special issue: ends of eras and new beginnings: twenty-first century challenges for shipping," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 347-367, June.
    16. Angelopoulos, Jason & Sahoo, Satya & Visvikis, Ilias D., 2020. "Commodity and transportation economic market interactions revisited: New evidence from a dynamic factor model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    17. Yang, Jialin & Ge, Ying-En & Li, Kevin X., 2022. "Measuring volatility spillover effects in dry bulk shipping market," Transport Policy, Elsevier, vol. 125(C), pages 37-47.
    18. Bai, Xiwen & Cheng, Liangqi & Iris, Çağatay, 2022. "Data-driven financial and operational risk management: Empirical evidence from the global tramp shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).

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