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Helena Veiga

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. Peeters, Ronald & Lopes Moreira Da Veiga, María Helena & Vorstaz, Marc, 2022. "Contagion in sequential financial markets: an experimental analysis," DES - Working Papers. Statistics and Econometrics. WS 31230, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Robert Merl, 2021. "Literature Review of Experimental Asset Markets with Insiders," Working Paper Series, Social and Economic Sciences 2021-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    2. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).

  2. Marín Díazaraque, Juan Miguel & Rue, Havard & Lopes Moreira Da Veiga, María Helena & Zea Bermudez, Patrícia de, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Di Zhang & Qiang Niu & Youzhou Zhou, 2022. "Modeling Randomly Walking Volatility with Chained Gamma Distributions," Papers 2207.01151, arXiv.org, revised Oct 2022.

  3. Zea Bermudez, Patrícia de & Marín Díazaraque, Juan Miguel & Lopes Moreira Da Veiga, María Helena, 2019. "Data cloning estimation for asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 28214, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Marín Díazaraque, Juan Miguel & Lopes Moreira Da Veiga, María Helena, 2023. "Data cloning for a threshold asymmetric stochastic volatility model," DES - Working Papers. Statistics and Econometrics. WS 36569, Universidad Carlos III de Madrid. Departamento de Estadística.

  4. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    2. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.

  5. Gloria Gonzalez-Rivera & Joao Henrique Mazzeu & Esther Ruiz & Helena Veiga, 2017. "A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities," Working Papers 201709, University of California at Riverside, Department of Economics.

    Cited by:

    1. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    2. Ding, Lili & Zhao, Zhongchao & Wang, Lei, 2022. "Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?," Applied Energy, Elsevier, vol. 312(C).

  6. Mariti, Massimo B. & Gonçalves Mazzeu, Joao Henrique & Lopes Moreira Da Veiga, María Helena, 2017. "Modeling and forecasting the oil volatility index," DES - Working Papers. Statistics and Econometrics. WS 25985, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Xiao, Jihong & Liu, Hong, 2023. "The time-varying impact of uncertainty on oil market fear: Does climate policy uncertainty matter?," Resources Policy, Elsevier, vol. 82(C).
    2. Shobande Olatunji Abdul & Shodipe Oladimeji Tomiwa, 2020. "Re-Evaluation of World Population Figures: Politics and Forecasting Mechanics," Economics and Business, Sciendo, vol. 34(1), pages 104-125, February.
    3. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Sivaprasad, Sheeja, 2021. "The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model," International Review of Financial Analysis, Elsevier, vol. 74(C).
    4. Olatunji Abdul Shobande & Oladimeji Tomiwa Shodipe, 2021. "Monetary Policy Interdependency in Fisher Effect: A Comparative Evidence," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(1), pages 203-226.
    5. Lu Wang & Shan Li & Chao Liang, 2024. "Exploring the impact of oil security attention on oil volatility: A new perspective," International Finance, Wiley Blackwell, vol. 27(1), pages 61-80, April.

  7. Grané, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    2. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  8. Latoeiro, Pedro & Ramos, Sofía B. & Veiga, Helena, 2013. "Predictability of stock market activity using Google search queries," DES - Working Papers. Statistics and Econometrics. WS ws130605, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    2. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    3. Semen Son Turan, 2014. "Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies," Information Management and Business Review, AMH International, vol. 6(6), pages 317-328.
    4. Gang Chu & Xiao Li & Dehua Shen & Yongjie Zhang, 2021. "Stock Crashes and Jumps Reactions to Information Demand and Supply: An Intraday Analysis," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(3), pages 397-427, September.
    5. Ekinci, Cumhur & Bulut, Ali Eray, 2021. "Google search and stock returns: A study on BIST 100 stocks," Global Finance Journal, Elsevier, vol. 47(C).
    6. Hsieh, Shu-Fan & Chan, Chia-Ying & Wang, Ming-Chun, 2020. "Retail investor attention and herding behavior," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 109-132.
    7. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    8. Gomes, Pedro & Taamouti, Abderrahim, 2016. "In search of the determinants of European asset market comovements," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 103-117.

  9. Lopes Moreira Da Veiga, María Helena & Galán Camacho, Jorge Eduardo & Wiper, Michael Peter, 2013. "Bayesian analysis of dynamic effects in inefficiency : evidence from the Colombian banking sector," DES - Working Papers. Statistics and Econometrics. WS ws131918, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Jorge E. Galán & Michael G. Pollitt, 2014. "Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities," Working Papers EPRG 1403, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.

  10. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.

  11. Martín-Barragán, Belén & Ramos, Sofía B. & Veiga, Helena, 2013. "Correlations between oil and stock markets : a wavelet-based approach," DES - Working Papers. Statistics and Econometrics. WS ws130504, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Sakurai, Yuji & Kurosaki, Tetsuo, 2020. "How has the relationship between oil and the US stock market changed after the Covid-19 crisis?," Finance Research Letters, Elsevier, vol. 37(C).
    2. Anoop S Kumar & B Kamaiah, 2017. "Returns And Volatility Spillover Between Asian Equity Markets: A Wavelet Approach," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 62(212), pages 63-84, January -.
    3. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Time-varying energy and stock market integration in Asia," Energy Economics, Elsevier, vol. 80(C), pages 777-792.
    4. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity," Working Papers 026, Centre for Econometric and Allied Research, University of Ibadan.
    5. Marín Díazaraque, Juan Miguel & Rue, Havard & Lopes Moreira Da Veiga, María Helena & Zea Bermudez, Patrícia de, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Pal, Debdatta & Mitra, Subrata K., 2019. "Oil price and automobile stock return co-movement: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 76(C), pages 172-181.
    7. Katarzyna Kuziak & Joanna Górka, 2023. "Dependence Analysis for the Energy Sector Based on Energy ETFs," Energies, MDPI, vol. 16(3), pages 1-30, January.
    8. Hussain, Saiful Izzuan & Nur-Firyal, R. & Ruza, Nadiah, 2022. "Linkage transitions between oil and the stock markets of countries with the highest COVID-19 cases," Journal of Commodity Markets, Elsevier, vol. 28(C).
    9. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2017. "Can stock market investors hedge energy risk? Evidence from Asia," Energy Economics, Elsevier, vol. 66(C), pages 559-570.
    10. Dutta, Anupam, 2018. "Oil and energy sector stock markets: An analysis of implied volatility indexes," Journal of Multinational Financial Management, Elsevier, vol. 44(C), pages 61-68.
    11. Raheem, Ibrahim D., 2022. "Different strokes for different folks: The case of oil shocks and emerging equity markets," Energy Economics, Elsevier, vol. 108(C).
    12. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    13. Ordu, Beyza Mina & Oran, Adil & Soytas, Ugur, 2018. "Is food financialized? Yes, but only when liquidity is abundant," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 82-96.
    14. Kocaarslan, Baris & Soytas, Ugur, 2019. "Dynamic correlations between oil prices and the stock prices of clean energy and technology firms: The role of reserve currency (US dollar)," Energy Economics, Elsevier, vol. 84(C).
    15. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Modeling the frequency dynamics of spillovers and connectedness between crude oil and MENA stock markets with portfolio implications," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 397-419.
    16. Aviral Kumar Tiwari & Ibrahim D. Raheem & Seref Bozoklu & Shawkat Hammoudeh, 2022. "The Oil Price‐Macroeconomic fundamentals nexus for emerging market economies: Evidence from a wavelet analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1569-1590, January.
    17. Sarwar, Suleman & Shahbaz, Muhammad & Anwar, Awais & Tiwari, Aviral Kumar, 2019. "The importance of oil assets for portfolio optimization: The analysis of firm level stocks," Energy Economics, Elsevier, vol. 78(C), pages 217-234.
    18. Gourène, Grakolet Arnold Zamereith & Mendy, Pierre, 2015. "Oil Prices and African Stock Markets Co-movement: A Time and Frequency Analysis," MPRA Paper 75852, University Library of Munich, Germany.
    19. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    20. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    21. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures related for Intra-Day Data?," Tinbergen Institute Discussion Papers 16-006/III, Tinbergen Institute.
    22. Aloui, Chaker & Hkiri, Besma & Lau, Marco Chi Keung & Yarovaya, Larisa, 2018. "Information transmission across stock indices and stock index futures: International evidence using wavelet framework," Research in International Business and Finance, Elsevier, vol. 44(C), pages 411-421.
    23. Mensi, Walid & Rehman, Mobeen Ur & Maitra, Debasish & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2021. "Oil, natural gas and BRICS stock markets: Evidence of systemic risks and co-movements in the time-frequency domain," Resources Policy, Elsevier, vol. 72(C).
    24. Peng, Cheng & Zhu, Huiming & Jia, Xianghua & You, Wanhai, 2017. "Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms," Economic Modelling, Elsevier, vol. 61(C), pages 248-259.
    25. Salisu, Afees A. & Adediran, Idris & Omoke, Philip C. & Tchankam, Jean Paul, 2023. "Gold and tail risks," Resources Policy, Elsevier, vol. 80(C).
    26. Zhenhua Liu & Zhihua Ding & Tao Lv & Jy S. Wu & Wei Qiang, 2019. "Financial factors affecting oil price change and oil-stock interactions: a review and future perspectives," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 207-225, January.
    27. Aqila Rafiuddin & Jennifer Daffodils & Jesus Cuauhtemoc Tellez Gaytan & Gyanendra Singh Sisodia, 2021. "Trend of Oil Prices, Gold, GCC Stocks Market during Covid-19 Pandemic: A Wavelet Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 560-572.
    28. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
    29. Power, Gabriel J. & Eaves, James & Turvey, Calum & Vedenov, Dmitry, 2017. "Catching the curl: Wavelet thresholding improves forward curve modelling," Economic Modelling, Elsevier, vol. 64(C), pages 312-321.
    30. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Yahyaee, Khamis H., 2018. "Extreme dependence and risk spillovers between oil and Islamic stock markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 42-63.
    31. Somayeh Kokabisaghi & Eric J. Pauwels & Katrien Van Meulder & André B. Dorsman, 2018. "Are These Shocks for Real? Sensitivity Analysis of the Significance of the Wavelet Response to Some CKLS Processes," IJFS, MDPI, vol. 6(3), pages 1-12, September.
    32. Fenech, Jean-Pierre & Vosgha, Hamed, 2019. "Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models," Economic Modelling, Elsevier, vol. 77(C), pages 81-91.
    33. Lu Yang & Lei Yang & Kung-Cheng Ho & Shigeyuki Hamori, 2019. "Determinants of the Long-Term Correlation between Crude Oil and Stock Markets," Energies, MDPI, vol. 12(21), pages 1-15, October.
    34. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
    35. Babak Fazelabdolabadi, 2019. "Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    36. Hkiri, Besma & Hammoudeh, Shawkat & Aloui, Chaker & Yarovaya, Larisa, 2017. "Are Islamic indexes a safe haven for investors? An analysis of total, directional and net volatility spillovers between conventional and Islamic indexes and importance of crisis periods," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 124-150.
    37. Tiwari, Aviral Kumar & Jena, Sangram Keshari & Mitra, Amarnath & Yoon, Seong-Min, 2018. "Impact of oil price risk on sectoral equity markets: Implications on portfolio management," Energy Economics, Elsevier, vol. 72(C), pages 120-134.
    38. Xiaojing Cai & Shigeyuki Hamori & Lu Yang & Shuairu Tian, 2020. "Multi-Horizon Dependence between Crude Oil and East Asian Stock Markets and Implications in Risk Management," Energies, MDPI, vol. 13(2), pages 1-24, January.
    39. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Narayan, Seema, 2018. "Technology-investing countries and stock return predictability," Emerging Markets Review, Elsevier, vol. 36(C), pages 159-179.
    40. Jiang, Zhuhua & Yoon, Seong-Min, 2020. "Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis," Energy Economics, Elsevier, vol. 90(C).
    41. Aviral Kumar Tiwari & Sangram Keshari Jena & Satish Kumar & Erik Hille, 2022. "Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach," Annals of Operations Research, Springer, vol. 315(1), pages 429-461, August.
    42. Iwanicz-Drozdowska Małgorzata & Rogowicz Karol & Smaga Paweł, 2023. "Market-moving events and their role in portfolio optimization of generations X, Y, and Z," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(4), pages 371-397, December.
    43. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.
    44. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    45. Smyth, Russell & Narayan, Paresh Kumar, 2018. "What do we know about oil prices and stock returns?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 148-156.
    46. Abuzayed, Bana & Al-Fayoumi, Nedal, 2021. "Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    47. Balli, Faruk & O Balli, Hatice & Nguyen, Thi Thu Ha, 2023. "Dynamic connectedness between crude oil and equity markets: What about the effects of firm's solvency and profitability positions?," Journal of Commodity Markets, Elsevier, vol. 31(C).
    48. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    49. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.
    50. Zhang, Yi, 2018. "Investigating dependencies among oil price and tanker market variables by copula-based multivariate models," Energy, Elsevier, vol. 161(C), pages 435-446.
    51. Al Rababa’a, Abdel Razzaq & Alomari, Mohammad & McMillan, David, 2021. "Multiscale stock-bond correlation: Implications for risk management," Research in International Business and Finance, Elsevier, vol. 58(C).
    52. Kliber, Agata & Łęt, Blanka, 2022. "Degree of connectedness and the transfer of news across the oil market and the European stocks," Energy, Elsevier, vol. 239(PC).
    53. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US Inflation: Evidence from a New Approach," Working Papers 039, Centre for Econometric and Allied Research, University of Ibadan.

  12. Galán Camacho, Jorge Eduardo & Lopes Moreira Da Veiga, María Helena & Wiper, Michael Peter, 2012. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," DES - Working Papers. Statistics and Econometrics. WS ws121007, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Kumbhakar, Subal C. & Peresetsky, Anatoly & Shchetynin, Yevgenii & Zaytsev, Alexey, 2020. "Technical efficiency and inefficiency: Reassurance of standard SFA models and a misspecification problem," MPRA Paper 102797, University Library of Munich, Germany.
    2. Yaguo Deng & Helena Veiga & Michael P. Wiper, 2019. "Efficiency evaluation of hotel chains: a Spanish case study," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 115-139, June.
    3. Wu, Ji & Guo, Mengmeng & Chen, Minghua & Jeon, Bang Nam, 2019. "Market power and risk-taking of banks: Some semiparametric evidence from emerging economies," Emerging Markets Review, Elsevier, vol. 41(C).
    4. Deng, Yaguo & Lopes Moreira Da Veiga, María Helena & Wiper, Michael Peter, 2016. "Efficiency evaluation of Spanish hotel chains," DES - Working Papers. Statistics and Econometrics. WS 23897, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Sarmiento Paipilla, N.M. & Galán, Jorge E., 2015. "The Influence of Risk-taking on Bank Efficiency : Evidence from Colombia," Other publications TiSEM f7a73cdb-55a2-40d3-936f-7, Tilburg University, School of Economics and Management.
    6. Lopes Moreira Da Veiga, María Helena & Galán Camacho, Jorge Eduardo & Wiper, Michael Peter, 2013. "Bayesian analysis of dynamic effects in inefficiency : evidence from the Colombian banking sector," DES - Working Papers. Statistics and Econometrics. WS ws131918, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Jorge E. Galán & Michael G. Pollitt, 2014. "Inefficiency persistence and heterogeneity in Colombian electricity distribution utilities," Working Papers EPRG 1403, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    8. Sarmiento, Miguel & Galán, Jorge E., 2014. "Heterogeneous effects of risk-taking on bank efficiency : a stochastic frontier model with random coefficients," DES - Working Papers. Statistics and Econometrics. WS ws142013, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
    10. Baños, José F. & Rodríguez-Álvarez, Ana & Suárez, Patricia, 2016. "Matching frontiers: A random parameter model approach," Efficiency Series Papers 2016/07, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    11. Marta Arbelo-Pérez & Yaiza Armas-Cruz & Antonio Arbelo, 2022. "Environmental strategy and firm performance: A new methodological proposal," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(8), pages 283-292.
    12. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    13. A. G. Billé & C. Salvioni & R. Benedetti, 2018. "Modelling spatial regimes in farms technologies," Journal of Productivity Analysis, Springer, vol. 49(2), pages 173-185, June.
    14. Feder, Christophe, 2018. "The effects of disruptive innovations on productivity," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 186-193.
    15. Orosco Gavilán, Juan Carlos & Lopes Moreira Da Veiga, María Helena & Wiper, Michael Peter, 2023. "Measuring efficiency of Peruvian universities: a stochastic frontier analysis," DES - Working Papers. Statistics and Econometrics. WS 36250, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Cinzia Daraio, 2017. "A framework for the Assessment of Research and its impacts," DIAG Technical Reports 2017-04, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    17. Hampf, Benjamin, 2015. "Estimating the materials balance condition: A stochastic frontier approach," Darmstadt Discussion Papers in Economics 226, Darmstadt University of Technology, Department of Law and Economics.

  13. Ramos, Sofía B. & Veiga, Helena, 2010. "Asymmetric effects of oil price fluctuations in international stock markets," DES - Working Papers. Statistics and Econometrics. WS ws100904, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

  14. Ramos, Sofia B. & Veiga, Helena, 2009. "Risk factors in oil and gas industry returns: international evidence," DES - Working Papers. Statistics and Econometrics. WS ws096920, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Moya-Martínez, Pablo & Ferrer-Lapeña, Román & Escribano-Sotos, Francisco, 2014. "Oil price risk in the Spanish stock market: An industry perspective," Economic Modelling, Elsevier, vol. 37(C), pages 280-290.
    2. Gupta, Kartick, 2016. "Oil price shocks, competition, and oil & gas stock returns — Global evidence," Energy Economics, Elsevier, vol. 57(C), pages 140-153.
    3. Daniel J. Tulloch, Ivan Diaz-Rainey, and I.M. Premachandra, 2017. "The Impact of Liberalization and Environmental Policy on the Financial Returns of European Energy Utilities," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    4. Rida Waheed & Chen Wei & Suleman Sarwar & Yulan Lv, 2018. "Impact of oil prices on firm stock return: industry-wise analysis," Empirical Economics, Springer, vol. 55(2), pages 765-780, September.
    5. Ramos, Sofía B. & Veiga, Helena & Wang, Chih-Wei, 2012. "Asymmetric long-run effects in the oil industry," DES - Working Papers. Statistics and Econometrics. WS ws120502, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Boying Li & Chun-Ping Chang & Yin Chu & Bo Sui, 2020. "Oil prices and geopolitical risks: What implications are offered via multi-domain investigations?," Energy & Environment, , vol. 31(3), pages 492-516, May.
    7. Degiannakis, Stavros & Filis, George & Arora, Vipin, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," MPRA Paper 96270, University Library of Munich, Germany.
    8. Ratti, Ronald A. & Hasan, M. Zahid, 2013. "Oil Price Shocks and Volatility in Australian Stock Returns ‎," MPRA Paper 49043, University Library of Munich, Germany.
    9. Mohammad Enamul Hoque & Soo-Wah Low, 2020. "Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework," Mathematics, MDPI, vol. 8(10), pages 1-28, October.
    10. Schaeffer, Roberto & Borba, Bruno S.M.C. & Rathmann, Régis & Szklo, Alexandre & Castelo Branco, David A., 2012. "Dow Jones sustainability index transmission to oil stock market returns: A GARCH approach," Energy, Elsevier, vol. 45(1), pages 933-943.
    11. Waqas Hanif & Jose Arreola Hernandez & Perry Sadorsky & Seong-Min Yoon, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," Post-Print hal-02567429, HAL.
    12. Hui Li & Renjin Sun & Wei-Jen Lee & Kangyin Dong & Rui Guo, 2016. "Assessing Risk in Chinese Shale Gas Investments Abroad: Modelling and Policy Recommendations," Sustainability, MDPI, vol. 8(8), pages 1-17, July.
    13. Aloui, Chaker & Nguyen, Duc Khuong & Njeh, Hassen, 2012. "Assessing the impacts of oil price fluctuations on stock returns in emerging markets," Economic Modelling, Elsevier, vol. 29(6), pages 2686-2695.
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    19. Mishra, Shekhar & Sharif, Arshian & Khuntia, Sashikanta & Meo, Muhammad Saeed & Rehman Khan, Syed Abdul, 2019. "Does oil prices impede Islamic stock indices? Fresh insights from wavelet-based quantile-on-quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 292-304.
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    23. Mohammad Enamul Hoque & Soo-Wah Low, 2022. "Impact of Industry-Specific Risk Factors on Stock Returns of the Malaysian Oil and Gas Industry in a Structural Break Environment," Mathematics, MDPI, vol. 10(2), pages 1-15, January.
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    26. Latoeiro, Pedro & Ramos, Sofía B. & Veiga, Helena, 2013. "Predictability of stock market activity using Google search queries," DES - Working Papers. Statistics and Econometrics. WS ws130605, Universidad Carlos III de Madrid. Departamento de Estadística.
    27. Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
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    34. Mohmmad Enamul Hoque & Soo Wah Low & Mohd Azlan Shah Zaidi, 2020. "Do Oil and Gas Risk Factors Matter in the Malaysian Oil and Gas Industry? A Fama-MacBeth Two Stage Panel Regression Approach," Energies, MDPI, vol. 13(5), pages 1-15, March.
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    44. Wei, Lu & Li, Guowen & Zhu, Xiaoqian & Sun, Xiaolei & Li, Jianping, 2019. "Developing a hierarchical system for energy corporate risk factors based on textual risk disclosures," Energy Economics, Elsevier, vol. 80(C), pages 452-460.
    45. Chien-Chung Nieh & Hsueh-Chu Yao, 2013. "Threshold effects in the capital asset pricing model using panel smooth transition regression (PSTR) Evidence from net oil export and import groups," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 3(2), pages 1-9.
    46. M. Zahid Hasan & Ronald A. Ratti, 2014. "Australian Coal Company Risk Factors: Coal and Oil Prices," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(1), pages 57-67.
    47. Tiwari, Aviral Kumar & Jena, Sangram Keshari & Mitra, Amarnath & Yoon, Seong-Min, 2018. "Impact of oil price risk on sectoral equity markets: Implications on portfolio management," Energy Economics, Elsevier, vol. 72(C), pages 120-134.
    48. Tsuji, Chikashi, 2018. "New DCC analyses of return transmission, volatility spillovers, and optimal hedging among oil futures and oil equities in oil-producing countries," Applied Energy, Elsevier, vol. 229(C), pages 1202-1217.
    49. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    50. Aviral Kumar Tiwari & Sangram Keshari Jena & Satish Kumar & Erik Hille, 2022. "Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach," Annals of Operations Research, Springer, vol. 315(1), pages 429-461, August.
    51. Martín-Barragán, Belén & Ramos, Sofía B. & Veiga, Helena, 2013. "Correlations between oil and stock markets : a wavelet-based approach," DES - Working Papers. Statistics and Econometrics. WS ws130504, Universidad Carlos III de Madrid. Departamento de Estadística.
    52. Swaray, Raymond & Salisu, Afees A., 2018. "A firm-level analysis of the upstream-downstream dichotomy in the oil-stock nexus," Global Finance Journal, Elsevier, vol. 37(C), pages 199-218.
    53. Ronald A. Ratti & M. Zahid Hasan, 2013. "Oil Price Shocks and Volatility in Australian Stock Returns," The Economic Record, The Economic Society of Australia, vol. 89, pages 67-83, June.
    54. Szczygielski, Jan Jakub & Brzeszczyński, Janusz & Charteris, Ailie & Bwanya, Princess Rutendo, 2022. "The COVID-19 storm and the energy sector: The impact and role of uncertainty," Energy Economics, Elsevier, vol. 109(C).
    55. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay, 2014. "Crude oil moments and PNG stock returns," Energy Economics, Elsevier, vol. 44(C), pages 222-235.
    56. Sorana Vătavu & Oana-Ramona Lobonț & Iulia Para & Andrei Pelin, 2018. "Addressing oil price changes through business profitability in oil and gas industry in the United Kingdom," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-22, June.
    57. Restrepo, Natalia & Uribe, Jorge M. & Manotas, Diego, 2018. "Financial risk network architecture of energy firms," Applied Energy, Elsevier, vol. 215(C), pages 630-642.
    58. Sunil K. Mohanty & Stein Frydenberg & Petter Osmundsen & Sjur Westgaard & Christian Skjøld, 2023. "Risk factors in stock returns of U.S. oil and gas companies: evidence from quantile regression analysis," Review of Quantitative Finance and Accounting, Springer, vol. 60(2), pages 715-746, February.
    59. Mohammad Enamul Hoque & Soo-Wah Low & Mohd Azlan Shah Zaidi, 2020. "The Effects of Oil and Gas Risk Factors on Malaysian Oil and Gas Stock Returns: Do They Vary?," Energies, MDPI, vol. 13(15), pages 1-22, July.
    60. Tsai, Chun-Li, 2015. "How do U.S. stock returns respond differently to oil price shocks pre-crisis, within the financial crisis, and post-crisis?," Energy Economics, Elsevier, vol. 50(C), pages 47-62.
    61. Ramos, Sofia B. & Veiga, Helena, 2013. "Oil price asymmetric effects: Answering the puzzle in international stock markets," Energy Economics, Elsevier, vol. 38(C), pages 136-145.
    62. Daniel Wurstbauer & Stephan Lang & Christoph Rothballer & Wolfgang Schaefers, 2016. "Can common risk factors explain infrastructure equity returns? Evidence from European capital markets," Journal of Property Research, Taylor & Francis Journals, vol. 33(2), pages 97-120, April.
    63. Mohammad Enamul Hoque & Soo-Wah Low & Mohd Azlan Shah Zaidi & Lain-Tze Tee & Noor Azlan Ghazali, 2023. "Asymmetric and Lag Effects of Industry Risk Factors on the Malaysian Oil and Gas Stocks," SAGE Open, , vol. 13(3), pages 21582440231, July.
    64. Mª Caridad Sevillano & Francisco Jareño, 2018. "The impact of international factors on Spanish company returns: a quantile regression approach," Risk Management, Palgrave Macmillan, vol. 20(1), pages 51-76, February.
    65. Begüm Yurteri Kösedağlı & Gül Huyugüzel Kışla & A. Nazif Çatık, 2021. "The time-varying effects of oil prices on oil–gas stock returns of the fragile five countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-22, December.
    66. Suleman Sarwar & Rida Waheed & Mehnoor Amir & Muqaddas Khalid, 2018. "Role of Energy on Economy The Case of Micro to Macro Level Analysis," Economics Bulletin, AccessEcon, vol. 38(4), pages 1905-1926.
    67. Seyed Amir Hossein Sabet & Marie-Anne Cam & Richard Heaney, 2012. "Share market reaction to the BP oil spill and the US government moratorium on exploration," Australian Journal of Management, Australian School of Business, vol. 37(1), pages 61-76, April.
    68. Caporale, Guglielmo Maria & Çatık, Abdurrahman Nazif & Huyuguzel Kısla, Gul Serife & Helmi, Mohamad Husam & Akdeniz, Coşkun, 2022. "Oil prices and sectoral stock returns in the BRICS-T countries: A time-varying approach," Resources Policy, Elsevier, vol. 79(C).
    69. Nazif Çatık, Abdurrahman & Huyugüzel Kışla, Gül & Akdeni̇z, Coşkun, 2020. "Time-varying impact of oil prices on sectoral stock returns: Evidence from Turkey," Resources Policy, Elsevier, vol. 69(C).
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  15. Grané, Aurea & Veiga, Helena, 2009. "Wavelet-based detection of outliers in volatility models," DES - Working Papers. Statistics and Econometrics. WS ws090403, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Li, Yushu, 2013. "Wavelet based outlier correction for power controlled turning point detection in surveillance systems," Economic Modelling, Elsevier, vol. 30(C), pages 317-321.
    2. Yushu Li & Simon Reese, 2014. "Wavelet improvement in turning point detection using a hidden Markov model: from the aspects of cyclical identification and outlier correction," Computational Statistics, Springer, vol. 29(6), pages 1481-1496, December.
    3. Li, Yushu & Reese, Simon, 2012. "Wavelet Improvement in Turning Point Detection using a Hidden Markov Model," Working Papers 2012:14, Lund University, Department of Economics, revised 05 Apr 2014.

  16. Veiga, Helena & Vorsatz, Marc, 2008. "The effect of short-selling of the aggregation of information in an experimental asset market," DES - Working Papers. Statistics and Econometrics. WS ws083808, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    2. Robert Merl, 2021. "Literature Review of Experimental Asset Markets with Insiders," Working Paper Series, Social and Economic Sciences 2021-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    3. Powell, O.R., 2010. "Essays on experimental bubble markets," Other publications TiSEM b16ad7ae-3741-4f08-8de7-3, Tilburg University, School of Economics and Management.
    4. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).

  17. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    2. 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.

  18. Grané, Aurea & Veiga, Helena, 2007. "Volatility modelling and accurate minimun capital risk requirements : a comparison among several approaches," DES - Working Papers. Statistics and Econometrics. WS ws074713, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.

  19. Veiga, H. & Vorsatz, M., 2006. "Price manipulation in an experimental asset market," Research Memorandum 024, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. Veiga, Helena & Vorsatz, Marc, 2008. "The effect of short-selling of the aggregation of information in an experimental asset market," DES - Working Papers. Statistics and Econometrics. WS ws083808, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2022. "Manipulation and (Mis)trust in Prediction Markets," Management Science, INFORMS, vol. 68(9), pages 6716-6732, September.
    3. Deck, Cary & Lin, Shengle & Porter, David, 2013. "Affecting policy by manipulating prediction markets: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 48-62.
    4. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    5. Johan Almenberg & Ken Kittlitz & Thomas Pfeiffer, 2009. "An Experiment on Prediction Markets in Science," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-7, December.
    6. Friederike Mengel & Ronald Peeters, 2022. "Do markets encourage risk-seeking behaviour?," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1474-1480, October.
    7. Corgnet, Brice & DeSantis, Mark & Siemroth, Christoph, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Economics Discussion Papers 36273, University of Essex, Department of Economics.
    8. Boris Maciejovsky & David V. Budescu, 2020. "Too Much Trust in Group Decisions: Uncovering Hidden Profiles by Groups and Markets," Organization Science, INFORMS, vol. 31(6), pages 1497-1514, November.
    9. Peeters, R.J.A.P. & Wolk, K.L., 2014. "Eliciting and aggregating individual expectations: An experimental study," Research Memorandum 029, Maastricht University, Graduate School of Business and Economics (GSBE).
    10. Powell, O.R., 2010. "Essays on experimental bubble markets," Other publications TiSEM b16ad7ae-3741-4f08-8de7-3, Tilburg University, School of Economics and Management.
    11. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
    12. Helena Veiga & Marc Vorsatz, 2008. "Aggregation and Dissemination of Information in Experimental Asset Markets in the Presence of a Manipulator," Working Papers 2008-29, FEDEA.

  20. Ruiz Ortega, Esther & Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series 015, University of Pavia, Department of Economics and Management.
    2. Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Econometric Institute Research Papers EI 2012-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Kwan, Wilson & Li, Wai Keung & Li, Guodong, 2012. "On the estimation and diagnostic checking of the ARFIMA–HYGARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3632-3644.
    4. Dalla, Violetta, 2015. "Power transformations of absolute returns and long memory estimation," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 1-18.
    5. Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
    6. Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
    7. Lopes, Sílvia R.C. & Prass, Taiane S., 2014. "Theoretical results on fractionally integrated exponential generalized autoregressive conditional heteroskedastic processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 278-307.
    8. Carl Lönnbark, 2016. "Asymmetry with respect to the memory in stock market volatilities," Empirical Economics, Springer, vol. 50(4), pages 1409-1419, June.
    9. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    10. Jun-Jie Chen & Bo Zheng & Lei Tan, 2013. "Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-11, November.
    11. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2013. "Realized Stochastic Volatility with Leverage and Long Memory," CIRJE F-Series CIRJE-F-880, CIRJE, Faculty of Economics, University of Tokyo.
    12. Saker Sabkha & Christian de Peretti & Dorra Hmaied, 2018. "The Credit Default Swap market contagion during recent crises: International evidence," Post-Print hal-01572510, HAL.
    13. Luis A. Gil-Alana & Guglielmo M. Caporale, 2008. "Modelling the US, the UK and Japanese unemployment rates. Fractional integrationand structural breaks," Faculty Working Papers 11/08, School of Economics and Business Administration, University of Navarra.
    14. Pérez, Ana & Ruiz, Esther & Veiga, Helena, 2009. "A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3593-3600, August.
    15. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.
    16. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 637-668, September.
    17. Helena Veiga, 2009. "Financial Stylized Facts and the Taylor-Effect in Stochastic Volatility Models," Economics Bulletin, AccessEcon, vol. 29(1), pages 265-276.
    18. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    19. Rodríguez, Mª José & Ruiz Ortega, Esther, 2009. "GARCH models with leverage effect : differences and similarities," DES - Working Papers. Statistics and Econometrics. WS ws090302, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Jun-jie Chen & Bo Zheng & Lei Tan, 2014. "Agent-based model with asymmetric trading and herding for complex financial systems," Papers 1407.5258, arXiv.org.
    21. Veiga, Helena, 2006. "A two factor long memory stochastic volatility model," DES - Working Papers. Statistics and Econometrics. WS ws061303, Universidad Carlos III de Madrid. Departamento de Estadística.
    22. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    23. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    24. Taiane S. Prass & S'ilvia R. C. Lopes, 2013. "Risk Measure Estimation On Fiegarch Processes," Papers 1305.5238, arXiv.org.

  21. Veiga, Helena, 2006. "A two factor long memory stochastic volatility model," DES - Working Papers. Statistics and Econometrics. WS ws061303, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. J. Arteche, 2012. "Semiparametric Inference in Correlated Long Memory Signal Plus Noise Models," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 440-474.

  22. Danilo Coelho & Helena Veiga & R?rt Veszteg, 2005. "Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal," UFAE and IAE Working Papers 636.05, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

    Cited by:

    1. Fernández-Sainz, Ana I. & Rodríguez-Póo, Juan M., 2010. "An Empirical Investigation of Parametric and Semiparametric Estimation Methods in Sample Selection Models = Investigación empírica de métodos de estimación paramétricos y semiparamétricos de modelos d," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 10(1), pages 99-120, December.

Articles

  1. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    See citations under working paper version above.
  2. P. de Zea Bermudez & J. Miguel Marín & Helena Veiga, 2020. "Data cloning estimation for asymmetric stochastic volatility models," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1057-1074, November.
    See citations under working paper version above.
  3. Ramos, Sofia B. & Latoeiro, Pedro & Veiga, Helena, 2020. "Limited attention, salience of information and stock market activity," Economic Modelling, Elsevier, vol. 87(C), pages 92-108.

    Cited by:

    1. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    2. Weihan Zhao & Jianing Zhang, 2024. "Investor Attention and Stock Liquidity in the Chinese Market," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 30(1), pages 65-82, February.
    3. Alrashidi, Rasheed & Baboukardos, Diogenis & Arun, Thankom, 2021. "Audit fees, non-audit fees and access to finance: Evidence from India," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 43(C).
    4. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    5. Lu, Jing & Chen, Rongze, 2023. "Do individual investors pay attention to the information acquisition activities of institutional investors?," Finance Research Letters, Elsevier, vol. 58(PD).
    6. Chen, Chen & Lu, Xiaomeng & Zhang, Yixing, 2023. "Is attention-based stock buying profitable? Empirical evidence from Chinese individual investors," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    7. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).

  4. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.

    Cited by:

    1. Marín Díazaraque, Juan Miguel & Rue, Havard & Lopes Moreira Da Veiga, María Helena & Zea Bermudez, Patrícia de, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Casas, Isabel & Lopes Moreira Da Veiga, María Helena, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Marín Díazaraque, Juan Miguel & Lopes Moreira Da Veiga, María Helena, 2023. "Data cloning for a threshold asymmetric stochastic volatility model," DES - Working Papers. Statistics and Econometrics. WS 36569, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Antonis Demos, 2023. "Statistical Properties of Two Asymmetric Stochastic Volatility in Mean Models," DEOS Working Papers 2303, Athens University of Economics and Business.
    5. Omar Abbara & Mauricio Zevallos, 2022. "Maximum Likelihood Inference for Asymmetric Stochastic Volatility Models," Econometrics, MDPI, vol. 11(1), pages 1-18, December.

  5. João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019. "Modeling and forecasting the oil volatility index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 773-787, December.
    See citations under working paper version above.
  6. Yaguo Deng & Helena Veiga & Michael P. Wiper, 2019. "Efficiency evaluation of hotel chains: a Spanish case study," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 115-139, June.

    Cited by:

    1. Maziotis, Alexandros & Sala-Garrido, Ramon & Mocholi-Arce, Manuel & Molinos-Senante, Maria, 2023. "Cost and quality of service performance in the Chilean water industry: A comparison of stochastic approaches," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 211-219.
    2. Milagros Gutiérrez-Fernández & Yakira Fernández-Torres, 2020. "Does Gender Diversity Influence Business Efficiency? An Analysis from the Social Perspective of CSR," Sustainability, MDPI, vol. 12(9), pages 1-18, May.
    3. Francisca J. Sánchez-Sánchez & Ana M. Sánchez-Sánchez, 2024. "Evaluating the efficiency and determinants of mass tourism in Spain: a tourist area perspective," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(1), pages 111-145, January.

  7. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.

    Cited by:

    1. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.

  8. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.

    Cited by:

    1. Marín Díazaraque, Juan Miguel & Rue, Havard & Lopes Moreira Da Veiga, María Helena & Zea Bermudez, Patrícia de, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Casas, Isabel & Lopes Moreira Da Veiga, María Helena, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. P. de Zea Bermudez & J. Miguel Marín & Helena Veiga, 2020. "Data cloning estimation for asymmetric stochastic volatility models," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1057-1074, November.
    4. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    5. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.

  9. Galán, Jorge E. & Veiga, Helena & Wiper, Michael P., 2015. "Dynamic effects in inefficiency: Evidence from the Colombian banking sector," European Journal of Operational Research, Elsevier, vol. 240(2), pages 562-571.

    Cited by:

    1. Economou, Polychronis & Malefaki, Sonia & Kounetas, Konstantinos, 2019. "Productive Performance and Technology Gaps using a Bayesian Metafrontier Production Function: A cross-country comparison," MPRA Paper 94462, University Library of Munich, Germany.
    2. Levent Kutlu, 2022. "Spatial stochastic frontier model with endogenous weighting matrix," Empirical Economics, Springer, vol. 63(4), pages 1947-1968, October.
    3. Iordanis Parikoglou & Grigorios Emvalomatis & Fiona Thorne, 2022. "Precision livestock agriculture and productive efficiency: The case of milk recording in Ireland," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 109-120, November.
    4. Deng, Yaguo & Lopes Moreira Da Veiga, María Helena & Wiper, Michael Peter, 2016. "Efficiency evaluation of Spanish hotel chains," DES - Working Papers. Statistics and Econometrics. WS 23897, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Sarmiento Paipilla, N.M. & Galán, Jorge E., 2015. "The Influence of Risk-taking on Bank Efficiency : Evidence from Colombia," Other publications TiSEM f7a73cdb-55a2-40d3-936f-7, Tilburg University, School of Economics and Management.
    6. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2021. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Efficiency Series Papers 2021/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    7. Kutlu, Levent & Mamatzakis, Emmanuel & Tsionas, Mike G., 2022. "A principal–agent approach for estimating firm efficiency: Revealing bank managerial behavior," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    8. Tsionas, Euthimios G. & Mamatzakis, Emmanuel C., 2017. "Adjustment costs in the technical efficiency: An application to global banking," European Journal of Operational Research, Elsevier, vol. 256(2), pages 640-649.
    9. Paul, Satya & Shankar, Sriram, 2018. "On estimating efficiency effects in a stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 271(2), pages 769-774.
    10. Vanesa Llorens & Alfredo Martín-Oliver & Vicente Salas-Fumas, 2020. "Productivity, competition and bank restructuring process," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(3), pages 313-340, September.
    11. Sarmiento, Miguel & Galán, Jorge E., 2014. "Heterogeneous effects of risk-taking on bank efficiency : a stochastic frontier model with random coefficients," DES - Working Papers. Statistics and Econometrics. WS ws142013, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
    13. Jean Joseph Minviel & Timo Sipiläinen, 2021. "A dynamic stochastic frontier approach with persistent and transient inefficiency and unobserved heterogeneity," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 575-589, July.
    14. Aggelopoulos, Eleftherios & Georgopoulos, Antonios, 2017. "Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1170-1188.
    15. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2020. "A spatial stochastic frontier model with endogenous frontier and environmental variables," European Journal of Operational Research, Elsevier, vol. 286(1), pages 389-399.
    16. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
    17. Galán, Jorge E. & Pollitt, Michael G., 2014. "Inefficiency persistence and heterogeneity in Colombian electricity utilities," Energy Economics, Elsevier, vol. 46(C), pages 31-44.
    18. Stefany Moreno-Burbano & Andrés Vargas-Vargas & Juan Sebastián Vélez-Velásquez, 2019. "Interest rate dispersion in commercial loans," Borradores de Economia 1088, Banco de la Republica de Colombia.
    19. Cardoso de Mendonça, Mário Jorge & Pereira, Amaro Olimpio & Medrano, Luis Alberto & Pessanha, José Francisco M., 2021. "Analysis of electric distribution utilities efficiency levels by stochastic frontier in Brazilian power sector," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    20. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2023. "Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: Application to the Chinese banking industry," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1360-1373.
    21. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2022. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Economics of Transportation, Elsevier, vol. 31(C).
    22. Christian Castro & Jorge E. Galán, 2019. "Drivers of productivity in the Spanish banking sector: recent evidence," Working Papers 1912, Banco de España.
    23. Ioannis Skevas & Grigorios Emvalomatis & Bernhard Brümmer, 2018. "The effect of farm characteristics on the persistence of technical inefficiency: a case study in German dairy farming," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(1), pages 3-25.
    24. Jorge E. Galán & Yong Tan, 2024. "Green light for green credit? Evidence from its impact on bank efficiency," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 531-550, January.
    25. Jean Joseph Minviel & Timo Sipiläinen, 2018. "Dynamic stochastic analysis of the farm subsidy-efficiency link: evidence from France," Journal of Productivity Analysis, Springer, vol. 50(1), pages 41-54, October.
    26. Cortés-García, J. Salvador & Pérez-Rodríguez, Jorge V., 2024. "Heterogeneity and time-varying efficiency in the Ecuadorian banking sector. An output distance stochastic frontier approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 164-175.
    27. Hirofumi Fukuyama & Yong Tan, 2022. "Deconstructing three‐stage overall efficiency into input, output and stability efficiency components with consideration of market power and loan loss provision: An application to Chinese banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 953-974, January.
    28. Tran, Kien C. & Tsionas, Mike G., 2016. "Zero-inefficiency stochastic frontier models with varying mixing proportion: A semiparametric approach," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1113-1123.
    29. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.
    30. Pavlos Almanidis & Mustafa U. Karakaplan & Levent Kutlu, 2019. "A dynamic stochastic frontier model with threshold effects: U.S. bank size and efficiency," Journal of Productivity Analysis, Springer, vol. 52(1), pages 69-84, December.
    31. Galán, Jorge & Ramos, Sofía B. & Veiga, Helena, 2015. "An analysis of the dynamics of efficiency of mutual funds," DES - Working Papers. Statistics and Econometrics. WS ws1517, Universidad Carlos III de Madrid. Departamento de Estadística.
    32. Skevas, Ioannis & Emvalomatis, Grigorios & Brümmer, Bernhard, 2018. "Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms," European Journal of Operational Research, Elsevier, vol. 271(1), pages 250-261.

  10. Martín-Barragán, Belén & Ramos, Sofia B. & Veiga, Helena, 2015. "Correlations between oil and stock markets: A wavelet-based approach," Economic Modelling, Elsevier, vol. 50(C), pages 212-227.
    See citations under working paper version above.
  11. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    See citations under working paper version above.
  12. Ramos, Sofia B. & Veiga, Helena, 2013. "Oil price asymmetric effects: Answering the puzzle in international stock markets," Energy Economics, Elsevier, vol. 38(C), pages 136-145.

    Cited by:

    1. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2017. "Do oil price asymmetric effects on the stock market persist in multiple time horizons?," Applied Energy, Elsevier, vol. 185(P2), pages 1799-1808.
    2. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2019. "A sectoral analysis of asymmetric nexus between oil price and stock returns," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 241-259.
    3. Chowdhury, Kushal Banik & Garg, Bhavesh, 2023. "Fresh evidence on the oil-stock interactions under heterogeneous market conditions," Finance Research Letters, Elsevier, vol. 54(C).
    4. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    5. Paulo F. Marschner & Paulo Sergio Ceretta, 2021. "The impact of oil price shocks on latin american stock markets: a behavioral approach," Economics Bulletin, AccessEcon, vol. 41(2), pages 457-467.
    6. Li, Lei & Yin, Libo & Zhou, Yimin, 2016. "Exogenous shocks and the spillover effects between uncertainty and oil price," Energy Economics, Elsevier, vol. 54(C), pages 224-234.
    7. Ben Cheikh, Nidhaleddine & Ben Naceur, Sami & Kanaan, Oussama & Rault, Christophe, 2020. "Investigating the Asymmetric Impact of Oil Prices on GCC Stock Markets," IZA Discussion Papers 13853, Institute of Labor Economics (IZA).
    8. Kruel, Maximiliano & Ceretta, Paulo Sergio, 2022. "Asymmetric influences on Latin American stock markets: A quantile approach," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    9. Kim, Myung Suk, 2018. "Impacts of supply and demand factors on declining oil prices," Energy, Elsevier, vol. 155(C), pages 1059-1065.
    10. Tang, Yiding & Zhu, Shujin & Luo, Yan & Duan, Wenjing, 2022. "Input servitization, global value chain, and carbon mitigation: An input-output perspective of global manufacturing industry," Economic Modelling, Elsevier, vol. 117(C).
    11. Ramzi Benkraiem & Thi Hong Van Hoang & Amine Lahiani & Anthony Miloudi, 2018. "Crude oil and equity markets in major European countries: New evidence," Post-Print hal-01914607, HAL.
    12. Jozef Baruník, Evzen Kocenda and Lukáa Vácha, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    13. Jiliang Sheng & Juchao Li & Jun Yang, 2022. "Tail Dependency and Risk Spillover between Oil Market and Chinese Sectoral Stock Markets—An Assessment of the 2013 Refined Oil Pricing Reform," Energies, MDPI, vol. 15(16), pages 1-19, August.
    14. Nan, Shijing & Huo, Yuchen & You, Wanhai & Guo, Yawei, 2022. "Globalization spatial spillover effects and carbon emissions: What is the role of economic complexity?," Energy Economics, Elsevier, vol. 112(C).
    15. Latoeiro, Pedro & Ramos, Sofía B. & Veiga, Helena, 2013. "Predictability of stock market activity using Google search queries," DES - Working Papers. Statistics and Econometrics. WS ws130605, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Guo, Yaoqi & Yu, Chenxi & Zhang, Hongwei & Cheng, Hui, 2021. "Asymmetric between oil prices and renewable energy consumption in the G7 countries," Energy, Elsevier, vol. 226(C).
    17. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2017. "The impact of oil-market shocks on stock returns in major oil-exporting countries: A Markov-switching approach," MPRA Paper 81638, University Library of Munich, Germany.
    18. Mohsin Ali & Wajahat Azmi & Aftab Parvez Khan, 2019. "Portfolio Diversification and Oil Price Shocks: A Sector Wide Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 9(3), pages 251-260.
    19. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    20. Magali Dauvin, 2013. "Energy Prices and the Real Exchange Rate of Commodity-Exporting Countries," Working Papers 2013.102, Fondazione Eni Enrico Mattei.
    21. Bing Xu, 2015. "Oil prices and UK industry-level stock returns," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2608-2627, May.
    22. Ziadat, Salem Adel & McMillan, David G. & Herbst, Patrick, 2022. "Oil shocks and equity returns during bull and bear markets: The case of oil importing and exporting nations," Resources Policy, Elsevier, vol. 75(C).
    23. Boubaker, Heni & Larbi, Ons Ben, 2022. "Dynamic dependence and hedging strategies in BRICS stock markets with oil during crises," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 263-279.
    24. Ferreiro Javier Ojea, 2019. "Structural change in the link between oil and the European stock market: implications for risk management," Dependence Modeling, De Gruyter, vol. 7(1), pages 53-125, January.
    25. Zhu, Xuehong & Chen, Ying & Chen, Jinyu, 2021. "Effects of non-ferrous metal prices and uncertainty on industry stock market under different market conditions," Resources Policy, Elsevier, vol. 73(C).
    26. Badeeb, Ramez Abubakr & Lean, Hooi Hooi, 2018. "Asymmetric impact of oil price on Islamic sectoral stocks," Energy Economics, Elsevier, vol. 71(C), pages 128-139.
    27. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    28. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    29. Lin, Boqiang & Bai, Rui, 2021. "Oil prices and economic policy uncertainty: Evidence from global, oil importers, and exporters’ perspective," Research in International Business and Finance, Elsevier, vol. 56(C).
    30. Das, Debojyoti & Kannadhasan, M., 2020. "The asymmetric oil price and policy uncertainty shock exposure of emerging market sectoral equity returns: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 563-581.
    31. Babak Fazelabdolabadi, 2019. "Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    32. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    33. Ali, Mohsin & Masih, Mansur, 2014. "Does Indian Stock Market Provide Diversification Benefits Against Oil Price Shocks? A Sectoral Analysis," MPRA Paper 58828, University Library of Munich, Germany.
    34. Martín-Barragán, Belén & Ramos, Sofía B. & Veiga, Helena, 2013. "Correlations between oil and stock markets : a wavelet-based approach," DES - Working Papers. Statistics and Econometrics. WS ws130504, Universidad Carlos III de Madrid. Departamento de Estadística.
    35. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    36. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2018. "The impact of oil-market shocks on stock returns in major oil-exporting countries," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 264-280.
    37. NIDHALEDDINE BEN CHEIKH & SAMI BEN NACEUR & OUSSAMA KANAAN & Christophe RAULT, 2019. "Oil Prices and GCC Stock Markets: New Evidence from Vector Smooth Transition Models," LEO Working Papers / DR LEO 2697, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    38. Zaighum, Isma & Aman, Ameenullah & Sharif, Arshian & Suleman, Muhammad Tahir, 2021. "Do energy prices interact with global Islamic stocks? Fresh insights from quantile ARDL approach," Resources Policy, Elsevier, vol. 72(C).
    39. Smyth, Russell & Narayan, Paresh Kumar, 2018. "What do we know about oil prices and stock returns?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 148-156.
    40. Salem Adel Ziadat & David G. McMillan, 2022. "Oil-stock nexus: the role of oil shocks for GCC markets," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 39(5), pages 801-818, May.
    41. Yushu Li & Hyunjoo Kim Karlsson, 2023. "Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1765-1790, April.
    42. Deheri, Abdhut & Ramachandran, M., 2023. "Does Indian economy asymmetrically respond to oil price shocks?," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    43. Iyke, Bernard Njindan & Maheepala, M.M.J.D., 2022. "Conventional monetary policy, COVID-19, and stock markets in emerging economies," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    44. Md Fouad Bin Amin & Mohd Ziaur Rehman, 2022. "Asymmetric Linkages of Oil Prices, Money Supply, and TASI on Sectoral Stock Prices in Saudi Arabia: A Non-Linear ARDL Approach," SAGE Open, , vol. 12(1), pages 21582440211, January.
    45. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    46. Chang, Bisharat Hussain & Sharif, Arshian & Aman, Ameenullah & Suki, Norazah Mohd & Salman, Asma & Khan, Syed Abdul Rehman, 2020. "The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach," Resources Policy, Elsevier, vol. 65(C).
    47. Dinesh Gajurel & Akhila Chawla, 2022. "The oil price crisis and contagion effects on the Canadian economy," Applied Economics, Taylor & Francis Journals, vol. 54(13), pages 1527-1543, March.

  13. Aurea Grané & Helena Veiga, 2012. "Asymmetry, realised volatility and stock return risk estimates," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(2), pages 147-164, August.

    Cited by:

    1. Anita Radman Peša & Elżbieta Wrońska-Bukalska & Jurica Bosna, 2017. "ARDL panel estimation of stock market indices and macroeconomic environment of CEE and SEE countries in the last decade of transition," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(3), pages 205-221, December.

  14. Ramos, Sofia B. & Veiga, Helena, 2011. "Risk factors in oil and gas industry returns: International evidence," Energy Economics, Elsevier, vol. 33(3), pages 525-542, May.
    See citations under working paper version above.
  15. Helena Veiga & Marc Vorsatz, 2010. "Information aggregation in experimental asset markets in the presence of a manipulator," Experimental Economics, Springer;Economic Science Association, vol. 13(4), pages 379-398, December.

    Cited by:

    1. Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2023. "When Do Security Markets Aggregate Dispersed Information?," Management Science, INFORMS, vol. 69(6), pages 3697-3729, June.
    2. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2022. "Manipulation and (Mis)trust in Prediction Markets," Management Science, INFORMS, vol. 68(9), pages 6716-6732, September.
    3. Brice Corgnet & Mark DeSantis & David Porter, 2020. "Information Aggregation and the Cognitive Make-up of Traders," Working Papers 20-18, Chapman University, Economic Science Institute.
    4. Deck, Cary & Lin, Shengle & Porter, David, 2013. "Affecting policy by manipulating prediction markets: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 48-62.
    5. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    6. Ro’i Zultan & Todd R. Kaplan & Lawrence Choo, 2018. "Information Aggregation in Arrow-Debreu Markets: An Experiment," Working Papers 1807, Ben-Gurion University of the Negev, Department of Economics.
    7. Alfarano, Simone & Banal-Estanol, Albert & Camacho-Cuena, Eva & Iori, Giulia & Kapar, Burcu, 2020. "Centralized vs decentralized markets in the laboratory: The role of connectivity," MPRA Paper 99129, University Library of Munich, Germany.
    8. Spyros Galanis & Christos A. Ioannou & Stelios Kotronis, 2023. "Information Aggregation Under Ambiguity: Theory and Experimental Evidence," Working Papers 2023_04, Durham University Business School.
    9. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2020. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Working Papers 20-27, Chapman University, Economic Science Institute.
    10. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2017. "Information (Non)Aggregation in Markets with Costly Signal Acquisition," Working Papers 1735, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    11. Corgnet, Brice & DeSantis, Mark & Siemroth, Christoph, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Economics Discussion Papers 36273, University of Essex, Department of Economics.
    12. Boris Maciejovsky & David V. Budescu, 2020. "Too Much Trust in Group Decisions: Uncovering Hidden Profiles by Groups and Markets," Organization Science, INFORMS, vol. 31(6), pages 1497-1514, November.
    13. Cary Deck & David Porter, 2013. "Prediction Markets in the Laboratory," Working Papers 13-05, Chapman University, Economic Science Institute.
    14. Brice Corgnet & Mark Desantis & David Porter, 2021. "Information Aggregation and the Cognitive Make-up of Market Participants," Post-Print hal-03188235, HAL.
    15. Simone Alfarano & Albert Banal-Estañol & Eva Camacho & Giulia Iori & Burcu Kapar & Rohit Rahi, 2024. "Centralized vs decentralized markets: The role of connectivity," Economics Working Papers 1877, Department of Economics and Business, Universitat Pompeu Fabra.
    16. Huber, Jürgen & Kirchler, Michael & Stefan, Matthias, 2014. "Experimental evidence on varying uncertainty and skewness in laboratory double-auction markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 798-809.
    17. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
    18. Brice Corgnet & Mark DeSantis & David Porter, 2015. "Revisiting Information Aggregation in Asset Markets: Reflective Learning & Market Efficiency," Working Papers 15-15, Chapman University, Economic Science Institute.

  16. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.

    Cited by:

    1. Oleg Shirokikh & Grigory Pastukhov & Vladimir Boginski & Sergiy Butenko, 2013. "Computational study of the US stock market evolution: a rank correlation-based network model," Computational Management Science, Springer, vol. 10(2), pages 81-103, June.
    2. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    3. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    5. Milda Norkute, 2015. "Can the sectoral New Keynesian Phillips curve explain inflation dynamics in the Euro Area?," Empirical Economics, Springer, vol. 49(4), pages 1191-1216, December.
    6. Somayeh Kokabisaghi & Eric J. Pauwels & Katrien Van Meulder & André B. Dorsman, 2018. "Are These Shocks for Real? Sensitivity Analysis of the Significance of the Wavelet Response to Some CKLS Processes," IJFS, MDPI, vol. 6(3), pages 1-12, September.
    7. Akouemo, Hermine N. & Povinelli, Richard J., 2016. "Probabilistic anomaly detection in natural gas time series data," International Journal of Forecasting, Elsevier, vol. 32(3), pages 948-956.
    8. Liu, Shuyu & Huang, Shupei & Chi, Yuxi & Feng, Sida & Li, Yang & Sun, Qingru, 2020. "Three-level network analysis of the North American natural gas price: A multiscale perspective," International Review of Financial Analysis, Elsevier, vol. 67(C).
    9. Anupam Dutta & Elie Bouri & David Roubaud, 2021. "Modelling the volatility of crude oil returns: Jumps and volatility forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 889-897, January.
    10. Grané, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Gallegati, Marco & Ramsey, James B. & Semmler, Willi, 2014. "Interest rate spreads and output: A time scale decomposition analysis using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 283-290.
    12. Vladimir Boginski & Sergiy Butenko & Oleg Shirokikh & Svyatoslav Trukhanov & Jaime Gil Lafuente, 2014. "A network-based data mining approach to portfolio selection via weighted clique relaxations," Annals of Operations Research, Springer, vol. 216(1), pages 23-34, May.
    13. Carnero, M. Angeles & Peña, Daniel & Ruiz, Esther, 2012. "Estimating GARCH volatility in the presence of outliers," Economics Letters, Elsevier, vol. 114(1), pages 86-90.
    14. Kojić, Milena & Schlüter, Stephan & Mitić, Petar & Hanić, Aida, 2022. "Economy-environment nexus in developed European countries: Evidence from multifractal and wavelet analysis," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).

  17. Helena Veiga, 2009. "Financial Stylized Facts and the Taylor-Effect in Stochastic Volatility Models," Economics Bulletin, AccessEcon, vol. 29(1), pages 265-276.

    Cited by:

    1. Helena Veiga, 2009. "Comment on "Financial Stylized Facts and the Taylor-Effect in Stochastic Volatility Models" by H. Veiga," Economics Bulletin, AccessEcon, vol. 29(4), pages 2730-2731.
    2. Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
    3. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    4. Dinghai Xu & John Knight, 2013. "Stochastic volatility model under a discrete mixture-of-normal specification," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(2), pages 216-239, April.

  18. Veiga, Helena & Vorsatz, Marc, 2009. "Price manipulation in an experimental asset market," European Economic Review, Elsevier, vol. 53(3), pages 327-342, April.
    See citations under working paper version above.
  19. Pérez, Ana & Ruiz, Esther & Veiga, Helena, 2009. "A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3593-3600, August.

    Cited by:

    1. Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
    2. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    3. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2013. "Realized Stochastic Volatility with Leverage and Long Memory," CIRJE F-Series CIRJE-F-880, CIRJE, Faculty of Economics, University of Tokyo.
    4. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    5. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.
    6. Helena Veiga, 2009. "Financial Stylized Facts and the Taylor-Effect in Stochastic Volatility Models," Economics Bulletin, AccessEcon, vol. 29(1), pages 265-276.
    7. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.

  20. Grané, A. & Veiga, H., 2008. "Accurate minimum capital risk requirements: A comparison of several approaches," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2482-2492, November.

    Cited by:

    1. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
    2. Tsai, Ming-Shann & Chen, Lien-Chuan, 2011. "The calculation of capital requirement using Extreme Value Theory," Economic Modelling, Elsevier, vol. 28(1), pages 390-395.
    3. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. José Manuel Cueto & Aurea Grané & Ignacio Cascos, 2020. "Models for Expected Returns with Statistical Factors," JRFM, MDPI, vol. 13(12), pages 1-17, December.
    5. Tsai, Ming-Shann & Chen, Lien-Chuan, 2011. "The calculation of capital requirement using Extreme Value Theory," Economic Modelling, Elsevier, vol. 28(1-2), pages 390-395, January.
    6. José Manuel Cueto & Aurea Grané & Ignacio Cascos, 2021. "How to Explain the Cross-Section of Equity Returns through Common Principal Components," Mathematics, MDPI, vol. 9(9), pages 1-22, April.
    7. Kerkhof, Jeroen & Melenberg, Bertrand & Schumacher, Hans, 2010. "Model risk and capital reserves," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 267-279, January.
    8. Sebastian Letmathe & Yuanhua Feng & André Uhde, 2021. "Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall," Working Papers CIE 141, Paderborn University, CIE Center for International Economics.
    9. Cueto, José Manuel & Grané Chávez, Aurea & Cascos Fernández, Ignacio, 2019. "Models for expected returns with statistical factors," DES - Working Papers. Statistics and Econometrics. WS 28776, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Cueto, José Manuel & Grané Chávez, Aurea & Cascos Fernández, Ignacio, 2021. "How to explain the cross-section of equity returns through Common Principal Components," DES - Working Papers. Statistics and Econometrics. WS 32258, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Aurea Grané & Helena Veiga, 2012. "Asymmetry, realised volatility and stock return risk estimates," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 11(2), pages 147-164, August.
    12. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.

  21. Ruiz, Esther & Veiga, Helena, 2008. "Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2846-2862, February.
    See citations under working paper version above.
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