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Andre Alves Portela Santos

Not to be confused with: Andre Oliveira Santos

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Santos, André A. P. & Nogales, Francisco J., 2009. "Comparing univariate and multivariate models to forecast portfolio value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws097222, Universidad Carlos III de Madrid. Departamento de Estadística.

    Mentioned in:

    1. Multivariate Versus Univariate Forecasts – Which is Best for Forecasting?
      by Clive Jones in Business Forecasting on 2013-06-10 20:57:40

Working papers

  1. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.

    Cited by:

    1. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    2. Caratozzolo, Vincenzo & Misuri, Alessio & Cozzani, Valerio, 2022. "A generalized equipment vulnerability model for the quantitative risk assessment of horizontal vessels involved in Natech scenarios triggered by floods," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    3. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    4. Caio Vigo Pereira, 2020. "Portfolio Efficiency with High-Dimensional Data as Conditioning Information," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202015, University of Kansas, Department of Economics, revised Sep 2020.
    5. Claudia ANTAL-VAIDA, 2021. "Basic Hyperparameters Tuning Methods for Classification Algorithms," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 25(2), pages 64-74.

  2. Perlin, Marcelo & Santos, André & Imasato, Takeyoshi & Borenstein, Denis & Da Silva, Sergio, 2017. "The Brazilian scientific output published in journals: A study based on a large CV database," MPRA Paper 79662, University Library of Munich, Germany.

    Cited by:

    1. Ernesto Galbán-Rodríguez & Déborah Torres-Ponjuán & Yohannis Martí-Lahera & Ricardo Arencibia-Jorge, 2019. "Measuring the Cuban scientific output in scholarly journals through a comprehensive coverage approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1019-1043, November.
    2. Yu-Wei Chang & Dar-Zen Chen & Mu-Hsuan Huang, 2020. "Discovering types of research performance of scientists with significant contributions," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1529-1552, August.
    3. Xiancheng Li & Wenge Rong & Haoran Shi & Jie Tang & Zhang Xiong, 2018. "The impact of conference ranking systems in computer science: a comparative regression analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 879-907, August.
    4. Timur Narbaev & Diana Amirbekova, 2021. "Research Productivity in Emerging Economies: Empirical Evidence from Kazakhstan," Publications, MDPI, vol. 9(4), pages 1-19, November.
    5. Borenstein, Denis & Perlin, Marcelo S. & Imasato, Takeyoshi, 2022. "The Academic Inbreeding Controversy: Analysis and Evidence from Brazil," Journal of Informetrics, Elsevier, vol. 16(2).
    6. Yu-Wei Chang, 2021. "Characteristics of high research performance authors in the field of library and information science and those of their articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3373-3391, April.
    7. Marcelo S. Perlin & Takeyoshi Imasato & Denis Borenstein, 2018. "Is predatory publishing a real threat? Evidence from a large database study," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 255-273, July.

  3. Fabricio Tourrucôo & João F. Caldeira & Guilherme V. Moura & André A. P. Santos, 2016. "Forecasting The Yield Curve With The Arbitrage-Free Dynamic Nelson-Siegel Model: Brazilian Evidence," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 028, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    Cited by:

    1. Amira Abid & Fathi Abid, 2024. "Sovereign Credit Risk in Saudi Arabia, Morocco and Egypt," JRFM, MDPI, vol. 17(7), pages 1-20, July.
    2. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    3. Eduardo Mineo & Airlane Pereira Alencar & Marcelo Moura & Antonio Elias Fabris, 2020. "Forecasting the Term Structure of Interest Rates with Dynamic Constrained Smoothing B-Splines," JRFM, MDPI, vol. 13(4), pages 1-14, April.

  4. R. Ferreira, Alexandre & A. P. Santos, Andre, 2016. "On the choice of covariance specifications for portfolio selection problems," MPRA Paper 73259, University Library of Munich, Germany.

    Cited by:

    1. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    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).

  5. Guilherme Valle Moura & João Frois Caldeira & André Santos, 2014. "Seleção De Carteiras Utilizando O Modelofama-French-Carhart," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 117, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    Cited by:

    1. Paulo Ferreira Naibert & João F. Caldeira, 2016. "Seleção De Carteiras Com Restrição Das Normas Das Posições: Uma Comparação Empírica Entre Diferentes Níveis De Restrição De Exposição Para Dados Da Bm&Fbovespa," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 132, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    2. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.

  6. Goulart, Marco & Da Costa Jr, Newton & Santos, Andre & Takase, Emilio & Da Silva, Sergio, 2013. "Psychophysiological correlates of the disposition effect," MPRA Paper 48227, University Library of Munich, Germany.

    Cited by:

    1. Daiane De Bortoli & Newton da Costa Jr. & Marco Goulart & Jéssica Campara, 2019. "Personality traits and investor profile analysis: A behavioral finance study," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-18, March.
    2. Rau, Holger A., 2015. "The disposition effect in team investment decisions: Experimental evidence," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 272-282.
    3. Dorow, Anderson & da Costa, Newton & Takase, Emilio & Prates, Wlademir & Da Silva, Sergio, 2018. "On the neural substrates of the disposition effect and return performance," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 16-21.
    4. Dorow, Anderson & Da Costa Jr, Newton & Takase, Emilio & Prates, Wlademir & Da Silva, Sergio, 2017. "On the neural substrates of the disposition effect and return performance," MPRA Paper 83354, University Library of Munich, Germany.
    5. Marco Pleßner, 2017. "The disposition effect: a survey," Management Review Quarterly, Springer, vol. 67(1), pages 1-30, February.
    6. Stephen L Cheung, 2024. "A meta-analysis of disposition effect experiments," Working Papers 2024-02, University of Sydney, School of Economics.
    7. Rau, Holger A., 2015. "The disposition effect in team investment decisions: Experimental evidence," University of Göttingen Working Papers in Economics 256, University of Goettingen, Department of Economics.
    8. Richards, Daniel W. & Fenton-O'Creevy, Mark & Rutterford, Janette & Kodwani, Devendra G., 2018. "Is the disposition effect related to investors’ reliance on System 1 and System 2 processes or their strategy of emotion regulation?," Journal of Economic Psychology, Elsevier, vol. 66(C), pages 79-92.
    9. Rau, Holger A., 2014. "The disposition effect and loss aversion: Do gender differences matter?," Economics Letters, Elsevier, vol. 123(1), pages 33-36.

  7. Santos, André A. P. & Nogales, Francisco J., 2009. "Comparing univariate and multivariate models to forecast portfolio value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws097222, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.
    2. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    3. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    4. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    5. Zaichao Du & Pei Pei, 2020. "Backtesting portfolio value‐at‐risk with estimated portfolio weights," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 605-619, September.
    6. Francq, Christian & Zakoian, Jean-Michel, 2015. "Joint inference on market and estimation risks in dynamic portfolios," MPRA Paper 68100, University Library of Munich, Germany.
    7. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    8. Fortin, Alain-Philippe & Simonato, Jean-Guy & Dionne, Georges, 2018. "Forecasting Expected Shortfall: Should we use a Multivariate Model for Stock Market Factors?," Working Papers 18-4, HEC Montreal, Canada Research Chair in Risk Management, revised 25 Jun 2021.
    9. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    10. Christian Francq & Jean-Michel Zakoian, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," Papers 1909.04661, arXiv.org.
    11. Fritzsch, Simon & Timphus, Maike & Weiß, Gregor, 2024. "Marginals versus copulas: Which account for more model risk in multivariate risk forecasting?," Journal of Banking & Finance, Elsevier, vol. 158(C).
    12. Makushkin, Mikhail & Lapshin, Victor, 2020. "Modelling tail dependencies between Russian and foreign stock markets: Application for market risk valuation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 30-52.
    13. Noori, Mohammad & Hitaj, Asmerilda, 2023. "Dissecting hedge funds' strategies," International Review of Financial Analysis, Elsevier, vol. 85(C).
    14. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    15. Degiannakis, Stavros & Kiohos, Apostolos, 2014. "Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices," MPRA Paper 80438, University Library of Munich, Germany.
    16. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    17. Bonga-Bonga, Lumengo & Nleya, Lebogang, 2016. "Assessing portfolio market risk in the BRICS economies: use of multivariate GARCH models," MPRA Paper 75809, University Library of Munich, Germany.
    18. Carole Bernard & Ludger Rüschendorf & Steven Vanduffel & Ruodu Wang, 2017. "Risk bounds for factor models," Finance and Stochastics, Springer, vol. 21(3), pages 631-659, July.
    19. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
    20. Jochen Krause & Marc S. Paolella, 2014. "A Fast, Accurate Method for Value-at-Risk and Expected Shortfall," Econometrics, MDPI, vol. 2(2), pages 1-25, June.
    21. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    22. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    23. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    24. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    25. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2016. "What derives the bond portfolio value-at-risk: Information roles of macroeconomic and financial stress factors," SFB 649 Discussion Papers 2016-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Fernanda Maria Müller & Thalles Weber Gössling & Samuel Solgon Santos & Marcelo Brutti Righi, 2024. "A comparison of Range Value at Risk (RVaR) forecasting models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 509-543, April.
    27. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    28. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    29. Duan, Fang, 2022. "Forecasting risk measures based on structural breaks in the correlation matrix," Ruhr Economic Papers 945, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    30. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    31. Shang, Han Lin, 2017. "Functional time series forecasting with dynamic updating: An application to intraday particulate matter concentration," Econometrics and Statistics, Elsevier, vol. 1(C), pages 184-200.
    32. Bams, Dennis & Blanchard, Gildas & Lehnert, Thorsten, 2017. "Volatility measures and Value-at-Risk," International Journal of Forecasting, Elsevier, vol. 33(4), pages 848-863.
    33. Jorge V Pérez-Rodríguez & María Santana-Gallego, 2020. "Modelling tourism receipts and associated risks, using long-range dependence models," Tourism Economics, , vol. 26(1), pages 70-96, February.
    34. 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.
    35. Taras Bodnar & Vilhelm Niklasson & Erik Thors'en, 2022. "Volatility Sensitive Bayesian Estimation of Portfolio VaR and CVaR," Papers 2205.01444, arXiv.org.
    36. Rainer Jobst & Daniel Rösch & Harald Scheule & Martin Schmelzle, 2015. "A Simple Econometric Approach for Modeling Stress Event Intensities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 300-320, April.
    37. Thilo A. Schmitt & Rudi Schäfer & Dominik Wied & Thomas Guhr, 2016. "Spatial dependence in stock returns: local normalization and VaR forecasts," Empirical Economics, Springer, vol. 50(3), pages 1091-1109, May.
    38. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.

  8. Gil-Bazo, Javier & Ruiz-Verdú, Pablo & Santos, André A. P., 2008. "The performance of socially responsible mutual funds: the role of fees and management companies," DEE - Working Papers. Business Economics. WB wb083409, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.

    Cited by:

    1. Slapikaite Indre & Tamosiuniene Rima, 2013. "Socially Responsible Mutual Funds – A Profitable Way of Investing," Scientific Annals of Economics and Business, Sciendo, vol. 60(1), pages 202-214, July.
    2. In, Francis & Kim, Martin & Park, Raphael Jonghyeon & Kim, Sangbae & Kim, Tong Suk, 2014. "Competition of socially responsible and conventional mutual funds and its impact on fund performance," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 160-176.
    3. Saiful Arefeen & Koji Shimada, 2020. "Performance and Resilience of Socially Responsible Investing (SRI) and Conventional Funds during Different Shocks in 2016: Evidence from Japan," Sustainability, MDPI, vol. 12(2), pages 1-20, January.
    4. Gerasimos G. Rompotis, 2022. "The ESG ETFs in the UK," Journal of Asset Management, Palgrave Macmillan, vol. 23(2), pages 114-129, March.
    5. Simona Cosma & Paolo Cucurachi & Vincenzo Gentile & Giuseppe Rimo, 2024. "Sustainable finance disclosure regulation insights: Unveiling socially responsible funds performance during COVID‐19 pandemic and Russia–Ukraine war," Business Strategy and the Environment, Wiley Blackwell, vol. 33(4), pages 3242-3257, May.
    6. Graham McIntosh, 2016. "Socially Responsible Investment and Market Performance: The Case of Energy and Resource Firms," Cambridge Working Papers in Economics 1609, Faculty of Economics, University of Cambridge.
    7. Jonathan Peillex & Sabri Boubaker & Breeda Comyns, 2021. "Does It Pay to Invest in Japanese Women? Evidence from the MSCI Japan Empowering Women Index," Journal of Business Ethics, Springer, vol. 170(3), pages 595-613, May.
    8. Galagedera, Don U.A., 2019. "Modelling social responsibility in mutual fund performance appraisal: A two-stage data envelopment analysis model with non-discretionary first stage output," European Journal of Operational Research, Elsevier, vol. 273(1), pages 376-389.
    9. Gunther Capelle†Blancard & Stéphanie Monjon, 2014. "The Performance of Socially Responsible Funds: Does the Screening Process Matter?," European Financial Management, European Financial Management Association, vol. 20(3), pages 494-520, June.
    10. Lapanan, Nicha, 2018. "The investment behavior of socially responsible individual investors," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 214-226.
    11. Alda, Mercedes & Vicente, Ruth, 2020. "Behavioural analysis of socially responsible investment managers: specialists versus non-specialists," Research in International Business and Finance, Elsevier, vol. 54(C).
    12. Janusz Brzeszczyński & Graham McIntosh, 2014. "Performance of Portfolios Composed of British SRI Stocks," Journal of Business Ethics, Springer, vol. 120(3), pages 335-362, March.
    13. Urquhart, Andrew & Zhang, Hanxiong, 2019. "The performance of technical trading rules in Socially Responsible Investments," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 397-411.
    14. Gunther Capelle-Blancard & Stephanie Monjon, 2014. "The Performance of Socially Responsible Funds: Does the Screening Process Matter?," Post-Print hal-00802363, HAL.
    15. J. Francisco Rubio & Neal Maroney & M. Kabir Hassan, 2018. "Can Efficiency of Returns Be Considered as a Pricing Factor?," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 25-54, June.
    16. Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Asymmetric multifractal behaviour and network connectedness between socially responsible stocks and international oil before and during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    17. Francisco Climent & Paula Mollá & Pilar Soriano, 2020. "The Investment Performance of U.S. Islamic Mutual Funds," Sustainability, MDPI, vol. 12(9), pages 1-18, April.
    18. Edna Aparecida Greggio Possebon & Felippe Aparecido Cippiciani & José Roberto Ferreira Savoia & Frédéric de Mariz, 2024. "ESG Scores and Performance in Brazilian Public Companies," Sustainability, MDPI, vol. 16(13), pages 1-18, July.
    19. Jitmaneeroj, Boonlert, 2023. "Time-varying fund manager skills of socially responsible investing (SRI) funds in developed and emerging markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    20. Wei Rong Ang & Greg N Gregoriou & Hooi Hooi Lean, 2014. "Market-timing skills of socially responsible investment fund managers: The case of North America versus Europe," Journal of Asset Management, Palgrave Macmillan, vol. 15(6), pages 366-377, December.
    21. Federica Ielasi & Monica Rossolini, 2019. "Responsible or Thematic? The True Nature of Sustainability-Themed Mutual Funds," Sustainability, MDPI, vol. 11(12), pages 1-17, June.
    22. Renu Jonwall & Seema Gupta & Shuchi Pahuja, 2024. "Do socially responsible indices outperform conventional indices? Evidence from before and after the onset of Covid‐19," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(5), pages 4995-5011, September.
    23. Ana C. Díaz†Mendoza & Germán López†Espinosa & Miguel A. Martínez, 2014. "The Efficiency of Performance†Based Fee Funds," European Financial Management, European Financial Management Association, vol. 20(4), pages 825-855, September.
    24. Alda, Mercedes & Muñoz, Fernando & Vargas, María, 2022. "Product differentiation in the socially responsible mutual fund industry," Journal of Multinational Financial Management, Elsevier, vol. 64(C).
    25. Orlando Gomes, 2020. "Optimal growth under socially responsible investment: a dynamic theoretical model of the trade-off between financial gains and emotional rewards," International Journal of Corporate Social Responsibility, Springer, vol. 5(1), pages 1-17, December.
    26. Andreas G. F. Hoepner & Lisa Schopohl, 2020. "State Pension Funds and Corporate Social Responsibility: Do Beneficiaries’ Political Values Influence Funds’ Investment Decisions?," Journal of Business Ethics, Springer, vol. 165(3), pages 489-516, September.
    27. Bilbao-Terol, Amelia & Álvarez-Otero, Susana & Bilbao-Terol, Celia & Cañal-Fernández, Verónica, 2017. "Hedonic evaluation of the SRI label of mutual funds using matching methodology," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 213-227.
    28. Guillermo Badía & Maria C. Cortez & Luis Ferruz, 2020. "Socially responsible investing worldwide: Do markets value corporate social responsibility?," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(6), pages 2751-2764, November.
    29. Tamas Barko & Martijn Cremers & Luc Renneboog, 2022. "Shareholder Engagement on Environmental, Social, and Governance Performance," Journal of Business Ethics, Springer, vol. 180(2), pages 777-812, October.
    30. Pablo Durán-Santomil & Luis Otero-González & Renato Heitor Correia-Domingues & Juan Carlos Reboredo, 2019. "Does Sustainability Score Impact Mutual Fund Performance?," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
    31. Nandita Das & Bernadette Ruf & Swarn Chatterjee & Aman Sunder, 2018. "Fund Characteristics and Performances of Socially Responsible Mutual Funds: Do ESG Ratings Play a Role?," Papers 1806.09906, arXiv.org, revised Feb 2023.
    32. Lean, Hooi Hooi & Ang, Wei Rong & Smyth, Russell, 2014. "Performance and Performance Persistence of Socially Responsible Investment Funds in Europe and North America," MPRA Paper 59119, University Library of Munich, Germany.
    33. Yuchao Xiao & Robert Faff & Philip Gharghori & Byoung-Kyu Min, 2017. "The Financial Performance of Socially Responsible Investments: Insights from the Intertemporal CAPM," Journal of Business Ethics, Springer, vol. 146(2), pages 353-364, December.
    34. Christos Kollias & Stephanos Papadamou, 2016. "Environmentally Responsible and Conventional Market Indices’ Reaction to Natural and Anthropogenic Adversity: A Comparative Analysis," Journal of Business Ethics, Springer, vol. 138(3), pages 493-505, October.
    35. Francisco Climent & Pilar Soriano, 2011. "Green and Good? The Investment Performance of US Environmental Mutual Funds," Journal of Business Ethics, Springer, vol. 103(2), pages 275-287, October.
    36. Konstantinos Petridis & Nikolaos Kiosses & Ioannis Tampakoudis & Fouad Ben Abdelaziz, 2023. "Measuring the efficiency of mutual funds: Does ESG controversies score affect the mutual fund performance during the COVID-19 pandemic?," Operational Research, Springer, vol. 23(3), pages 1-29, September.
    37. Dumitrescu, Ariadna & Järvinen, Jesse & Zakriya, Mohammed, 2023. "Hidden Gem or Fool’s Gold: Can passive ESG ETFs outperform the benchmarks?," International Review of Financial Analysis, Elsevier, vol. 86(C).
    38. Massimo Guidolin & Monia Magnani, 2024. "Do US Active Mutual Funds Make Good of Their ESG Promises? Evidence from Portfolio Holdings," Risks, MDPI, vol. 12(2), pages 1-26, February.
    39. Mirza, Nawazish & Naeem, Muhammad Abubakr & Ha Nguyen, Thi Thu & Arfaoui, Nadia & Oliyide, Johnson A., 2023. "Are sustainable investments interdependent? The international evidence," Economic Modelling, Elsevier, vol. 119(C).
    40. Juan Carlos Matallín-Sáez & Amparo Soler-Domínguez & Emili Tortosa-Ausina, 2016. "Does socially responsible mutual fund performance vary over the business cycle? New insights on the role of ethical strategy focus and green industry idiosyncratic risk," Working Papers 2016/03, Economics Department, Universitat Jaume I, Castellón (Spain).
    41. Hooi Hooi Lean & Duc Khuong Nguyen, 2014. "Policy uncertainty and performance characteristics of sustainable investments across regions around the global financial crisis," Working Papers 2014-295, Department of Research, Ipag Business School.
    42. Miwa Nakai & Keiko Yamaguchi & Kenji Takeuchi, 2015. "Can SRI Funds Better Resist Global Financial Crisis? Evidence from Japan," Discussion Papers 1530, Graduate School of Economics, Kobe University.
    43. Greg Filbeck & Timothy A. Krause & Lauren Reis, 2016. "Socially responsible investing in hedge funds," Journal of Asset Management, Palgrave Macmillan, vol. 17(6), pages 408-421, October.
    44. Miwa Nakai & Tomonori Honda & Nariaki Nishino & Kenji Takeuchi, 2013. "An Experimental Study on Motivations for Socially Responsible Investment," Discussion Papers 1314, Graduate School of Economics, Kobe University.
    45. Umar, Zaghum & Kenourgios, Dimitris & Papathanasiou, Sypros, 2020. "The static and dynamic connectedness of environmental, social, and governance investments: International evidence," Economic Modelling, Elsevier, vol. 93(C), pages 112-124.
    46. Fernando García & Jairo González-Bueno & Javier Oliver & Nicola Riley, 2019. "Selecting Socially Responsible Portfolios: A Fuzzy Multicriteria Approach," Sustainability, MDPI, vol. 11(9), pages 1-14, April.
    47. Mansor, F. & Bhatti, M.I. & Ariff, M., 2015. "New evidence on the impact of fees on mutual fund performance of two types of funds," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 35(C), pages 102-115.
    48. Francisco José López-Arceiz & Ana José Bellostas-Pérezgrueso & José Mariano Moneva, 2018. "Evaluation of the Cultural Environment’s Impact on the Performance of the Socially Responsible Investment Funds," Journal of Business Ethics, Springer, vol. 150(1), pages 259-278, June.
    49. Muñoz, Fernando, 2021. "Carbon-intensive industries in Socially Responsible mutual funds' portfolios," International Review of Financial Analysis, Elsevier, vol. 75(C).
    50. El Ghoul, Sadok & Karoui, Aymen, 2017. "Does corporate social responsibility affect mutual fund performance and flows?," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 53-63.
    51. Iván Barreda-Tarrazona & Juan Matallín-Sáez & Mª Balaguer-Franch, 2011. "Measuring Investors’ Socially Responsible Preferences in Mutual Funds," Journal of Business Ethics, Springer, vol. 103(2), pages 305-330, October.
    52. Muñoz, Fernando & Ortiz, Cristina & Vicente, Luis, 2022. "Ethical window dressing: SRI funds are as good as their word," Finance Research Letters, Elsevier, vol. 49(C).
    53. Klinkowska, Olga & Zhao, Yuan, 2023. "Fund flows and performance: New evidence from retail and institutional SRI mutual funds," International Review of Financial Analysis, Elsevier, vol. 87(C).
    54. Amparo Soler-Domínguez & Juan Carlos Matallín-Sáez & Diego Víctor de Mingo-López & Emili Tortosa-Ausina, 2020. "Social responsible mutual funds and lowcarbon economy," Working Papers 2020/15, Economics Department, Universitat Jaume I, Castellón (Spain).
    55. Sebastian Rathner, 2013. "The Influence of Primary Study Characteristics on the Performance Differential Between Socially Responsible and Conventional Investment Funds: A Meta-Analysis," Journal of Business Ethics, Springer, vol. 118(2), pages 349-363, December.
    56. Papathanasiou, Spyros & Koutsokostas, Drosos, 2024. "Sustainability ratings and fund performance: New evidence from European ESG equity mutual funds," Finance Research Letters, Elsevier, vol. 62(PA).
    57. Mariacristina Rossi & Dario Sansone & Arthur van Soest & Costanza Torricelli, 2018. "“Household Preferences for Socially Responsible Investments"," CeRP Working Papers 177, Center for Research on Pensions and Welfare Policies, Turin (Italy).
    58. Reddy, Krishna & Mirza, Nawazish & Naqvi, Bushra & Fu, Mingli, 2017. "Comparative risk adjusted performance of Islamic, socially responsible and conventional funds: Evidence from United Kingdom," Economic Modelling, Elsevier, vol. 66(C), pages 233-243.
    59. Mohd Ziaur Rehman & Md Zulquar Nain & Mohammed Alhashim & Javed Ahmad Bhat, 2024. "Choice between Sustainable versus Conventional Investments—Relative Efficiency Analysis from Global and Regional Stock Markets," Sustainability, MDPI, vol. 16(13), pages 1-25, June.
    60. Beatrice Boumda & Darren Duxbury & Cristina Ortiz & Luis Vicente, 2021. "Do Socially Responsible Investment Funds Sell Losses and Ride Gains? The Disposition Effect in SRI Funds," Sustainability, MDPI, vol. 13(15), pages 1-14, July.
    61. Christine Helliar & Barbara Petracci & Nongnuch Tantisantiwong, 2022. "Comparing SRI funds to conventional funds using a PCA methodology," Journal of Asset Management, Palgrave Macmillan, vol. 23(7), pages 581-595, December.
    62. Guido Abate & Ignazio Basile & Pierpaolo Ferrari, 2021. "The level of sustainability and mutual fund performance in Europe: An empirical analysis using ESG ratings," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1446-1455, September.
    63. Laura Fabregat-Aibar & M. Glòria Barberà-Mariné & Antonio Terceño & Laia Pié, 2019. "A Bibliometric and Visualization Analysis of Socially Responsible Funds," Sustainability, MDPI, vol. 11(9), pages 1-17, May.
    64. Maike van Dijk-de Groot & Andre H.J. Nijhof, 2015. "Socially Responsible Investment Funds: a review of research priorities and strategic options," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 5(3), pages 178-204, July.
    65. Amparo Soler‐Domínguez & Juan Carlos Matallín‐Sáez & Diego Víctor de Mingo‐López & Emili Tortosa‐Ausina, 2021. "Looking for sustainable development: Socially responsible mutual funds and the low‐carbon economy," Business Strategy and the Environment, Wiley Blackwell, vol. 30(4), pages 1751-1766, May.
    66. Kathrin Lesser & Christian Walkshäusl, 2018. "International Islamic funds," Review of Financial Economics, John Wiley & Sons, vol. 36(1), pages 72-80, January.
    67. Fang, Fei & Parida, Sitikantha, 2022. "Sustainable mutual fund performance and flow in the recent years through the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 84(C).
    68. Gasser, Stephan M. & Rammerstorfer, Margarethe & Weinmayer, Karl, 2017. "Markowitz revisited: Social portfolio engineering," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1181-1190.
    69. Ghoul, Sadok El & Karoui, Aymen, 2022. "Fund performance and social responsibility: New evidence using social active share and social tracking error," Journal of Banking & Finance, Elsevier, vol. 143(C).
    70. Rathner, Sebastian, 2013. "The Relative Performance of Socially Responsible Investment Funds. New Evidence from Austria," Working Papers in Economics 2013-1, University of Salzburg.
    71. Juan Meng & Yonghong Jiang & Haiwen Zhao & Ansheng Tanliang, 2024. "Asymmetric Effects of Renewable Energy Markets on China’s Green Financial Markets: A Perspective of Time and Frequency Dynamic Connectedness," Mathematics, MDPI, vol. 12(13), pages 1-15, June.
    72. Lars Hornuf & Gül Yüksel, 2022. "The Performance of Socially Responsible Investments: A Meta-Analysis," CESifo Working Paper Series 9724, CESifo.
    73. Lai Wan-Ni, 2012. "Faith matters? A closer look at the performance of belief-based equity investments," Journal of Asset Management, Palgrave Macmillan, vol. 13(6), pages 421-436, December.

  9. Andre Santos & Joao Tusi & Newton Da Costa Jr & Sergio Da Silva, 2005. "Evaluating Brazilian Stock Mutual Funds with Stochastic Frontiers," Finance 0510030, University Library of Munich, Germany.

    Cited by:

    1. Babalos, Vassilios & Mamatzakis, Emmanuel C. & Matousek, Roman, 2015. "The performance of US equity mutual funds," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 217-229.
    2. Jin-Li Hu & Tzu-Pu Chang & Ray Chou, 2014. "Market conditions and the effect of diversification on mutual fund performance: should funds be more concentrative under crisis?," Journal of Productivity Analysis, Springer, vol. 41(1), pages 141-151, February.
    3. Pi‐Hsia Hung & Donald Lien & Yun‐Ju Chien, 2020. "Portfolio concentration and fund manager performance," Review of Financial Economics, John Wiley & Sons, vol. 38(3), pages 423-451, July.
    4. Hung, Pi-Hsia & Lien, Donald & Kuo, Ming-Sin, 2020. "Window dressing in equity mutual funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 338-354.

Articles

  1. DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).

    Cited by:

    1. Kaniel, Ron & Lin, Zihan & Pelger, Markus & Van Nieuwerburgh, Stijn, 2023. "Machine-Learning the Skill of Mutual Fund Managers," CEPR Discussion Papers 18129, C.E.P.R. Discussion Papers.

  2. Santos, André A.P. & Torrent, Hudson S., 2022. "Markowitz meets technical analysis: Building optimal portfolios by exploiting information in trend-following signals," Finance Research Letters, Elsevier, vol. 49(C).

    Cited by:

    1. Hwang, Yoontae & Park, Junpyo & Lee, Yongjae & Lim, Dong-Young, 2023. "Stop-loss adjusted labels for machine learning-based trading of risky assets," Finance Research Letters, Elsevier, vol. 58(PA).

  3. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).

    Cited by:

    1. Bodnar, Olha & Bodnar, Taras & Niklasson, Vilhelm, 2024. "Constructing Bayesian tangency portfolios under short-selling restrictions," Finance Research Letters, Elsevier, vol. 62(PA).
    2. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    3. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    5. Jin Yuan & Xianghui Yuan, 2023. "A Best Linear Empirical Bayes Method for High-Dimensional Covariance Matrix Estimation," SAGE Open, , vol. 13(2), pages 21582440231, June.
    6. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    7. Kuangxi Su & Yinhong Yao & Chengli Zheng & Wenzhao Xie, 2024. "Portfolio Selection Based on EMD Denoising with Correlation Coefficient Test Criterion," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 391-421, January.
    8. Xinyu Huang & Weihao Han & David Newton & Emmanouil Platanakis & Dimitrios Stafylas & Charles Sutcliffe, 2023. "The diversification benefits of cryptocurrency asset categories and estimation risk: pre and post Covid-19," The European Journal of Finance, Taylor & Francis Journals, vol. 29(7), pages 800-825, May.

  4. André A. P. Santos, 2019. "Disentangling the role of variance and covariance information in portfolio selection problems," Quantitative Finance, Taylor & Francis Journals, vol. 19(1), pages 57-76, January.

    Cited by:

    1. Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    2. Moura, Guilherme V. & Santos, André A.P. & Ruiz, Esther, 2020. "Comparing high-dimensional conditional covariance matrices: Implications for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 118(C).

  5. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.

    Cited by:

    1. Lucien Boulet, 2021. "Forecasting High-Dimensional Covariance Matrices of Asset Returns with Hybrid GARCH-LSTMs," Papers 2109.01044, arXiv.org.
    2. Prayut Jain & Shashi Jain, 2019. "Can Machine Learning-Based Portfolios Outperform Traditional Risk-Based Portfolios? The Need to Account for Covariance Misspecification," Risks, MDPI, vol. 7(3), pages 1-27, July.
    3. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2022. "Can Volatility Solve the Naive Portfolio Puzzle?," Villanova School of Business Department of Economics and Statistics Working Paper Series 52, Villanova School of Business Department of Economics and Statistics.

  6. João F. Caldeira & Guilherme V. Moura & André A. P. Santos, 2018. "Yield curve forecast combinations based on bond portfolio performance," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(1), pages 64-82, January.

    Cited by:

    1. Joao F. Caldeira & Rangan Gupta & Tahir Suleman & Hudson S. Torrent, 2019. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Working Papers 201911, University of Pretoria, Department of Economics.
    2. Jaydip Sen & Sidra Mehtab, 2021. "Design and Analysis of Robust Deep Learning Models for Stock Price Prediction," Papers 2106.09664, arXiv.org.

  7. Marcelo S. Perlin & João F. Caldeira & André A. P. Santos & Martin Pontuschka, 2017. "Can We Predict the Financial Markets Based on Google's Search Queries?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(4), pages 454-467, July.

    Cited by:

    1. Lin, Zih-Ying, 2021. "Investor attention and cryptocurrency performance," Finance Research Letters, Elsevier, vol. 40(C).
    2. Bleher, Johannes & Dimpfl, Thomas, 2022. "Knitting Multi-Annual High-Frequency Google Trends to Predict Inflation and Consumption," Econometrics and Statistics, Elsevier, vol. 24(C), pages 1-26.
    3. Zhang, Tonghui & Yuan, Ying & Wu, Xi, 2020. "Is microblogging data reflected in stock market volatility? Evidence from Sina Weibo," Finance Research Letters, Elsevier, vol. 32(C).
    4. Arjun R & Suprabha KR, 2018. "Predictive modeling of stock indices closing from web search trends," Papers 1804.01676, arXiv.org.
    5. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
    6. Palma Lampreia Dos Santos, Maria José, 2018. "Nowcasting and forecasting aquaponics by Google Trends in European countries," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 178-185.
    7. María José Ayala & Nicolás Gonzálvez-Gallego & Rocío Arteaga-Sánchez, 2024. "Google search volume index and investor attention in stock market: a systematic review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-29, December.
    8. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2024. "Google search trends and stock markets: Sentiment, attention or uncertainty?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    9. Dhasmana, Samriddhi & Goel, Sandeep, 2023. "The insidious hyperreality in financial markets: An integrative review with evidence from the Indian financial market," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. Dionisis Th Philippas & Catalin Dragomirescu-Gaina & Stéphane Goutte & Duc Khuong Nguyen, 2021. "Investors’ attention and information losses under market stress," Post-Print hal-03434918, HAL.
    11. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    12. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
    13. Michael Olumekor & Hossam Haddad & Nidal Mahmoud Al-Ramahi, 2023. "The Relationship between Search Engines and Entrepreneurship Development: A Granger-VECM Approach," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    14. Matheus Pereira Libório & Petr Iakovlevitch Ekel & Carlos Augusto Paiva Martins, 2023. "Economic analysis through alternative data and big data techniques: what do they tell about Brazil?," SN Business & Economics, Springer, vol. 3(1), pages 1-16, January.

  8. Perlin, Marcelo S. & Santos, André A.P. & Imasato, Takeyoshi & Borenstein, Denis & Da Silva, Sergio, 2017. "The Brazilian scientific output published in journals: A study based on a large CV database," Journal of Informetrics, Elsevier, vol. 11(1), pages 18-31.
    See citations under working paper version above.
  9. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.

    Cited by:

    1. 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).
    2. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org, revised Aug 2024.
    3. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    4. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
    5. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    6. Panos K. Pouliasis & Ilias D. Visvikis & Nikos C. Papapostolou & Alexander A. Kryukov, 2020. "A novel risk management framework for natural gas markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 430-459, March.
    7. Robiyanto Robiyanto & Bayu Adi Nugroho & Andrian Dolfriandra Huruta & Budi Frensidy & Suyanto Suyanto, 2021. "Identifying the Role of Gold on Sustainable Investment in Indonesia: The DCC-GARCH Approach," Economies, MDPI, vol. 9(3), pages 1-14, August.
    8. Alessandra Amendola & Vincenzo Candila & Antonio Naimoli & Giuseppe Storti, 2024. "Adaptive combinations of tail-risk forecasts," Papers 2406.06235, arXiv.org.
    9. A Clements & M Doolan, 2018. "Combining Multivariate Volatility Forecasts using Weighted Losses," NCER Working Paper Series 119, National Centre for Econometric Research.
    10. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.

  10. Santos, André Alves Portela & Ferreira, Alexandre R., 2017. "On the choice of covariance specifications for portfolio selection problems," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    See citations under working paper version above.
  11. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.

    Cited by:

    1. Wang, Ce & Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2018. "Has China’s coal consumption already peaked? A demand-side analysis based on hybrid prediction models," Energy, Elsevier, vol. 162(C), pages 272-281.
    2. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    3. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    4. Joao F. Caldeira & Rangan Gupta & Tahir Suleman & Hudson S. Torrent, 2019. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Working Papers 201911, University of Pretoria, Department of Economics.
    5. Hofert, Marius & Prasad, Avinash & Zhu, Mu, 2022. "Multivariate time-series modeling with generative neural networks," Econometrics and Statistics, Elsevier, vol. 23(C), pages 147-164.
    6. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    7. Malgorzata Solarz & Jacek Adamek, 2021. "Factors Affecting Mobile Banking Adoption in Poland: An Empirical Study," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1018-1046.
    8. Simpson, Michael C. & Chatzopoulou, Maria Anna & Oyewunmi, Oyeniyi A. & Le Brun, Niccolo & Sapin, Paul & Markides, Christos N., 2019. "Technoeconomic analysis of internal combustion engine – organic Rankine cycle systems for combined heat and power in energy-intensive buildings," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. Almaguer, F-Javier & Amezcua, Omar González & Morales-Castillo, Javier & Soto-Villalobos, Roberto, 2018. "Riemann and Weierstrass walks revisited," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 518-526.
    10. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
    11. Marcel Ausloos & Roy Cerqueti & Francesca Bartolacci & Nicola G. Castellano, 2018. "SME investment best strategies. Outliers for assessing how to optimize performance," Papers 1807.09583, arXiv.org.
    12. João F. Caldeira, 2020. "Investigating the expectation hypothesis and the risk premium dynamics: new evidence for Brazil," Empirical Economics, Springer, vol. 59(1), pages 395-412, July.
    13. Stona, Filipe & Caldeira, João F., 2019. "Do U.S. factors impact the Brazilian yield curve? Evidence from a dynamic factor model," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 76-89.
    14. Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.

  12. João F. Caldeira & Guilherme V. Moura & , Fabricio Tourrucôo, 2016. "Forecasting the yield curve with the arbitrage-free dynamic Nelson-Siegel model: Brazilian evidence," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(2), pages 221-237.
    See citations under working paper version above.
  13. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Bond portfolio optimization using dynamic factor models," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 128-158.

    Cited by:

    1. Candelon, Bertrand & Luisi , Angelo & Roccazzella, Francesco, 2021. "Fragmentation in the European Monetary Union: Is it really over?," LIDAM Discussion Papers LFIN 2021015, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Potjagailo, Galina & Wolters, Maik H., 2019. "Global financial cycles since 1880," IMFS Working Paper Series 132, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    3. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2019. "Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure," SERIES 03-2019, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Jun 2019.
    4. Choi, Ahjin & Kang, Kyu Ho, 2023. "Modeling the time-varying dynamic term structure of interest rates," Journal of Banking & Finance, Elsevier, vol. 153(C).
    5. Hsiang-Hsi Liu & Chien-Kuo Tseng, 2022. "Common Components in Co-integrated System and Its Estimation and Application: Evidence from Five Stock Markets in Asia-Pacific Chinese Region," Bulletin of Applied Economics, Risk Market Journals, vol. 9(2), pages 101-121.
    6. Joao F. Caldeira & Rangan Gupta & Tahir Suleman & Hudson S. Torrent, 2019. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Working Papers 201911, University of Pretoria, Department of Economics.
    7. Aysu Celgin & Mahmut Gunay, 2020. "Weekly Economic Conditions Index for Turkey," CBT Research Notes in Economics 2018, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    8. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    10. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    11. Awe Olushina Olawale & Adepoju Abosede Adedayo, 2020. "Change-point detection in CO2 emission-energy consumption nexus using a recursive Bayesian estimation approach," Statistics in Transition New Series, Statistics Poland, vol. 21(1), pages 123-136, March.
    12. Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
    13. Wulan Anggraeni & Sudradjat Supian & Sukono & Nurfadhlina Abdul Halim, 2023. "Catastrophe Bond Diversification Strategy Using Probabilistic–Possibilistic Bijective Transformation and Credibility Measures in Fuzzy Environment," Mathematics, MDPI, vol. 11(16), pages 1-30, August.
    14. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    15. Rui Wang, 2019. "Unconventional Monetary Policy in Japan: Empirical Evidence from Estimated Shadow Rate DSGE Model," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-29, June.
    16. Konstantinos Bisiotis & Stelios Psarakis & Athanasios N. Yannacopoulos, 2022. "Affine Term Structure Models: Applications in Portfolio Optimization and Change Point Detection," Mathematics, MDPI, vol. 10(21), pages 1-33, November.
    17. Ma, Shuai & Ma, Xiaoteng & Xia, Li, 2023. "A unified algorithm framework for mean-variance optimization in discounted Markov decision processes," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1057-1067.
    18. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    19. Jiahe Lin & George Michailidis, 2019. "Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models," Papers 1912.04146, arXiv.org, revised May 2020.
    20. Hamill, Philip A. & Li, Youwei & Pantelous, Athanasios A. & Vigne, Samuel A. & Waterworth, James, 2021. "Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    21. Mouloud El Hafidi & Marouane Daoui, 2019. "Chocs de la politique monétaire et croissance économique au Maroc : une approche en terme de modèles FAVAR," Post-Print hal-03311354, HAL.

  14. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.

    Cited by:

    1. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    3. Makushkin, Mikhail & Lapshin, Victor, 2023. "Dynamic Nelson–Siegel model for market risk estimation of bonds: Practical implementation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 69, pages 5-27.
    4. Schlütter, Sebastian, 2017. "Scenario-based capital requirements for the interest rate risk of insurance companies," ICIR Working Paper Series 28/17, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    5. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    6. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2016. "What derives the bond portfolio value-at-risk: Information roles of macroeconomic and financial stress factors," SFB 649 Discussion Papers 2016-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
    8. Konstantinos Bisiotis & Stelios Psarakis & Athanasios N. Yannacopoulos, 2022. "Affine Term Structure Models: Applications in Portfolio Optimization and Change Point Detection," Mathematics, MDPI, vol. 10(21), pages 1-33, November.

  15. Goulart, Marco & da Costa, Newton C.A. & Andrade, Eduardo B. & Santos, André A.P., 2015. "Hedging against embarrassment," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 310-318.

    Cited by:

    1. Vanessa Martins Valcanover & Igor Bernardi Sonza & Wesley Vieira da Silva, 2020. "Behavioral Finance Experiments: A Recent Systematic Literature Review," SAGE Open, , vol. 10(4), pages 21582440209, November.
    2. Chris Brooks & Ivan Sangiorgi & Anastasiya Saraeva & Carola Hillenbrand & Kevin Money, 2023. "The importance of staying positive: The impact of emotions on attitude to risk," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3232-3261, July.
    3. Daiane De Bortoli & Newton da Costa Jr. & Marco Goulart & Jéssica Campara, 2019. "Personality traits and investor profile analysis: A behavioral finance study," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-18, March.
    4. Tomas Bonavia & Josué Brox-Ponce, 2018. "Shame in decision making under risk conditions: Understanding the effect of transparency," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-16, February.
    5. Muhl, Stefan & Talpsepp, Tõnn, 2018. "Faster learning in troubled times: How market conditions affect the disposition effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 226-236.
    6. Talpsepp, Tõnn & Liivamägi, Kristjan & Vaarmets, Tarvo, 2020. "Academic abilities, education and performance in the stock market," Journal of Banking & Finance, Elsevier, vol. 117(C).
    7. Hermann, Daniel & Mußhoff, Oliver & Rau, Holger A., 2017. "The disposition effect when deciding on behalf of others," University of Göttingen Working Papers in Economics 332, University of Goettingen, Department of Economics.
    8. Talpsepp, Tõnn & Vaarmets, Tarvo, 2019. "The disposition effect, performance, stop loss orders and education," Journal of Behavioral and Experimental Finance, Elsevier, vol. 24(C).
    9. Niu, Xiaofei & Li, Jianbiao, 2019. "How Time Constraint Affects the Disposition Effect?," EconStor Preprints 194618, ZBW - Leibniz Information Centre for Economics.
    10. Paraboni, Ana Luiza & da Costa, Newton, 2021. "Improving the level of financial literacy and the influence of the cognitive ability in this process," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    11. Li, Jianbiao & Niu, Xiaofei & Li, Dahui & Cao, Qian, 2018. "Using Non-Invasive Brain Stimulation to Test the Role of Self-Control in Investor Behavior," EconStor Preprints 177890, ZBW - Leibniz Information Centre for Economics.

  16. André A.P. Santos, 2015. "Beating the market with small portfolios: Evidence from Brazil," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 16(1), pages 22-31.

    Cited by:

    1. Xia, Siwei & Yang, Yuehan & Yang, Hu, 2023. "High-dimensional sparse portfolio selection with nonnegative constraint," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    2. Yuezhang Che & Shuyan Chen & Xin Liu, 2022. "Sparse Index Tracking Portfolio with Sector Neutrality," Mathematics, MDPI, vol. 10(15), pages 1-22, July.
    3. Nadège Ribau-Peltre & Pascal Damel & An Lethi, 2018. "A methodology to avoid over-diversification of funds of equity funds An implementation case study for equity funds of funds in bull markets," Post-Print hal-03027770, HAL.

  17. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.

    Cited by:

    1. Trucíos Maza, Carlos César & Mazzeu, João H. G. & Hallin, Marc & Hotta, Luiz Koodi & Pereira, Pedro L. Valls & Zevallos, Mauricio, 2019. "Forecasting conditional covariance matrices in high-dimensional time series: a general dynamic factor approach," Textos para discussão 505, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    2. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    3. Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
    4. Serdar Neslihanoglu & Stelios Bekiros & John McColl & Duncan Lee, 2021. "Multivariate time-varying parameter modelling for stock markets," Empirical Economics, Springer, vol. 61(2), pages 947-972, August.
    5. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    6. Guilherme Valle Moura & João Frois Caldeira & André Santos, 2014. "Seleção De Carteiras Utilizando O Modelofama-French-Carhart," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 117, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    8. 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).
    9. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    10. Francq, Christian & Sucarrat, Genaro, 2017. "An equation-by-equation estimator of a multivariate log-GARCH-X model of financial returns," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 16-32.
    11. Mengheng Li & Marcel Scharth, 2022. "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 285-301, January.
    12. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    13. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    14. Esparcia, Carlos & Diaz, Antonio & Alonso, Daniel, 2023. "How important is green awareness in energy investment decisions? An environmentally-based rebalancing portfolio study," Energy Economics, Elsevier, vol. 128(C).
    15. Gijsbert Suren & Guilherme Moura, 2012. "Heteroskedastic Dynamic Factor Models: A Monte Carlo Study," Economics Bulletin, AccessEcon, vol. 32(4), pages 2884-2898.
    16. Abdul Aziz, Nor Syahilla & Vrontos, Spyridon & M. Hasim, Haslifah, 2019. "Evaluation of multivariate GARCH models in an optimal asset allocation framework," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 568-596.
    17. Ruili Sun & Tiefeng Ma & Shuangzhe Liu, 2020. "Portfolio selection: shrinking the time-varying inverse conditional covariance matrix," Statistical Papers, Springer, vol. 61(6), pages 2583-2604, December.
    18. Díaz, Antonio & Esparcia, Carlos & López, Raquel, 2022. "The diversifying role of socially responsible investments during the COVID-19 crisis: A risk management and portfolio performance analysis," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 39-60.

  18. André A P Santos & Luciano N Junkes & Floriano C M Pires Jr, 2014. "Forecasting period charter rates of VLCC tankers through neural networks: A comparison of alternative approaches," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 16(1), pages 72-91, March.

    Cited by:

    1. 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.
    2. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.
    3. Payman Eslami & Kihyo Jung & Daewon Lee & Amir Tjolleng, 2017. "Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 538-550, August.
    4. Christos Katris & Manolis G. Kavussanos, 2021. "Time series forecasting methods for the Baltic dry index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1540-1565, December.
    5. Sangseop Lim & Chang-hee Lee & Won-Ju Lee & Junghwan Choi & Dongho Jung & Younghun Jeon, 2022. "Valuation of the Extension Option in Time Charter Contracts in the LNG Market," Energies, MDPI, vol. 15(18), pages 1-14, September.

  19. Caldeira, João F & Moura, Guilherme Valle & Santos, André Alves Portela, 2013. "Seleção de carteiras utilizando o modelo Fama-French-Carhart," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    See citations under working paper version above.
  20. André A. P. Santos & Francisco J. Nogales & Esther Ruiz, 2013. "Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 400-441, March.
    See citations under working paper version above.
  21. Anna Buchholz & Cesar Cupertino & Roberto Meurer & Andre Portela Santos & Newton Da Costa, 2012. "The market reaction to changes in the Brazilian official interest rate," Applied Economics Letters, Taylor & Francis Journals, vol. 19(14), pages 1359-1364, September.

    Cited by:

    1. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    2. Cavaca, Igor Bastos & Meurer, Roberto, 2024. "The asymmetry and uncertainty effects on the response of the yield curve to Brazilian monetary policy," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 831-844.

  22. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.

    Cited by:

    1. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    2. Xiaochun Liu, 2017. "An integrated macro‐financial risk‐based approach to the stressed capital requirement," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 86-98, September.
    3. Miralles-Quirós, José Luis & Miralles-Quirós, María del Mar, 2017. "The Copula ADCC-GARCH model can help PIIGS to fly," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 1-12.
    4. José Luis Miralles‐Quirós & María Mar Miralles‐Quirós & José Manuel Nogueira, 2019. "Diversification benefits of using exchange‐traded funds in compliance to the sustainable development goals," Business Strategy and the Environment, Wiley Blackwell, vol. 28(1), pages 244-255, January.
    5. Manuel Kleinknecht & Wing Lon Ng, 2015. "Minimizing Basel III Capital Requirements with Unconditional Coverage Constraint," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(4), pages 263-281, October.
    6. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2014. "Bank regulation and international financial stability: A case against the 2006 Basel framework for controlling tail risk in trading books," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 107-130.
    7. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    8. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    9. Vladimir Rankovic & Mikica Drenovak & Branko Uroševic & Ranko Jelic, 2016. "Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach," CESifo Working Paper Series 5731, CESifo.
    10. Ranković, Vladimir & Ivanović, Miloš & Urošević, Branko & Jelic, Ranko, 2017. "Market risk management in a post-Basel II regulatory environmentAuthor-Name: Drenovak, Mikica," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1030-1044.
    11. An Chen & Thai Nguyen & Mitja Stadje, 2018. "Risk management with multiple VaR constraints," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 88(2), pages 297-337, October.
    12. Lützenkirchen, Kristina & Rösch, Daniel & Scheule, Harald, 2013. "Ratings based capital adequacy for securitizations," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5236-5247.
    13. Branko Uroševic & Mikica Drenovak & Vladimir Rankovic & Ranko Jelic & Milos Ivanovic, 2016. "Market Risk Management in a Post-Basel II Regulatory Environment," CESifo Working Paper Series 6293, CESifo.
    14. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2021. "Regulation of bank proprietary trading post 2007–09 crisis: An examination of the Basel framework and Volcker rule," Journal of International Money and Finance, Elsevier, vol. 119(C).

  23. André Alves Portela Santos, 2010. "The Out-of-Sample Performance of Robust Portfolio Optimization," Brazilian Review of Finance, Brazilian Society of Finance, vol. 8(2), pages 141-166.

    Cited by:

    1. Shashank Oberoi & Mohammed Bilal Girach & Siddhartha P. Chakrabarty, 2020. "Can Robust Optimization Offer Improved Portfolio Performance? An Empirical Study of Indian market," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 611-630, September.
    2. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    3. Woo Kim & Jang Kim & So Ahn & Frank Fabozzi, 2013. "What do robust equity portfolio models really do?," Annals of Operations Research, Springer, vol. 205(1), pages 141-168, May.
    4. Shashank Oberoi & Mohammed Bilal Girach & Siddhartha P. Chakrabarty, 2019. "Can robust optimization offer improved portfolio performance?: An empirical study of Indian market," Papers 1908.04962, arXiv.org.
    5. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
    6. Man Yiu Tsang & Tony Sit & Hoi Ying Wong, 2022. "Adaptive Robust Online Portfolio Selection," Papers 2206.01064, arXiv.org.

  24. Javier Gil-Bazo & Pablo Ruiz-Verdú & André Santos, 2010. "The Performance of Socially Responsible Mutual Funds: The Role of Fees and Management Companies," Journal of Business Ethics, Springer, vol. 94(2), pages 243-263, June.
    See citations under working paper version above.
  25. Sergio Da Silva & Newton Da Costa, Jr & Joao Tusi & Andre Santos, 2005. "Evaluating Brazilian mutual funds with stochastic frontiers," Economics Bulletin, AccessEcon, vol. 13(2), pages 1-6.

    Cited by:

    1. Babalos, Vassilios & Mamatzakis, Emmanuel C. & Matousek, Roman, 2015. "The performance of US equity mutual funds," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 217-229.
    2. Jin-Li Hu & Tzu-Pu Chang & Ray Chou, 2014. "Market conditions and the effect of diversification on mutual fund performance: should funds be more concentrative under crisis?," Journal of Productivity Analysis, Springer, vol. 41(1), pages 141-151, February.
    3. Pi‐Hsia Hung & Donald Lien & Yun‐Ju Chien, 2020. "Portfolio concentration and fund manager performance," Review of Financial Economics, John Wiley & Sons, vol. 38(3), pages 423-451, July.
    4. Hung, Pi-Hsia & Lien, Donald & Kuo, Ming-Sin, 2020. "Window dressing in equity mutual funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 338-354.

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