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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. & Ruiz Ortega, Esther, 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. 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).
    2. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    3. 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.
    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.

  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. 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.
    2. 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.
    3. Borenstein, Denis & Perlin, Marcelo S. & Imasato, Takeyoshi, 2022. "The Academic Inbreeding Controversy: Analysis and Evidence from Brazil," Journal of Informetrics, Elsevier, vol. 16(2).
    4. 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.
    5. 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.
    6. 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.
    7. Timur Narbaev & Diana Amirbekova, 2021. "Research Productivity in Emerging Economies: Empirical Evidence from Kazakhstan," Publications, MDPI, vol. 9(4), pages 1-19, November.

  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. 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.
    2. 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. Stephen L Cheung, 2024. "A meta-analysis of disposition effect experiments," Working Papers 2024-02, University of Sydney, School of Economics.
    5. 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.
    6. 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.
    7. 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.
    8. Marco Pleßner, 2017. "The disposition effect: a survey," Management Review Quarterly, Springer, vol. 67(1), pages 1-30, February.
    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. & Ruiz Ortega, Esther, 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. 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.
    6. 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.
    7. 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.
    8. Christian Francq & Jean-Michel Zakoian, 2019. "Virtual Historical Simulation for estimating the conditional VaR of large portfolios," Papers 1909.04661, arXiv.org.
    9. Noori, Mohammad & Hitaj, Asmerilda, 2023. "Dissecting hedge funds' strategies," International Review of Financial Analysis, Elsevier, vol. 85(C).
    10. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    11. 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.
    12. 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.
    13. 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.
    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.
    15. 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.
    16. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    17. 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).
    18. 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.
    19. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    20. Stavros Degiannakis & Apostolos Kiohos, 2014. "Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 41(2), pages 216-232, March.
    21. Taras Bodnar & Vilhelm Niklasson & Erik Thors'en, 2022. "Volatility Sensitive Bayesian Estimation of Portfolio VaR and CVaR," Papers 2205.01444, arXiv.org.
    22. 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.
    23. 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.
    24. Francq, Christian & Zakoian, Jean-Michel, 2015. "Joint inference on market and estimation risks in dynamic portfolios," MPRA Paper 68100, University Library of Munich, Germany.
    25. 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.
    26. 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).
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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. 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.
    36. 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. 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.
    3. 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.
    4. 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.
    5. 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).
    6. Gunther Capelle-Blancard & Stephanie Monjon, 2014. "The Performance of Socially Responsible Funds: Does the Screening Process Matter?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00802363, HAL.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. 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.
    13. 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).
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Muñoz, Fernando, 2021. "Carbon-intensive industries in Socially Responsible mutual funds' portfolios," International Review of Financial Analysis, Elsevier, vol. 75(C).
    19. 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.
    20. 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).
    21. 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).
    22. 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).
    23. 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.
    24. 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.
    25. 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.
    26. 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).
    27. 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.
    28. Janusz Brzeszczynski & Graham McIntosh, 2012. "Performance of Portfolios Composed of British SRI Stocks," CFI Discussion Papers 1201, Centre for Finance and Investment, Heriot Watt University.
    29. Lars Hornuf & Gül Yüksel, 2022. "The Performance of Socially Responsible Investments: A Meta-Analysis," CESifo Working Paper Series 9724, CESifo.
    30. 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.
    31. 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.
    32. Gerasimos G. Rompotis, 2022. "The ESG ETFs in the UK," Journal of Asset Management, Palgrave Macmillan, vol. 23(2), pages 114-129, March.
    33. 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.
    34. 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.
    35. 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.
    36. 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).
    37. 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).
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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).
    50. 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).
    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. 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.
    56. 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).
    57. 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.
    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. 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.
    60. 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.
    61. 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.
    62. Kathrin Lesser & Christian Walkshäusl, 2018. "International Islamic funds," Review of Financial Economics, John Wiley & Sons, vol. 36(1), pages 72-80, January.
    63. 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).
    64. Rathner, Sebastian, 2013. "The Relative Performance of Socially Responsible Investment Funds. New Evidence from Austria," Working Papers in Economics 2013-1, University of Salzburg.
    65. 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. 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.
    2. 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.
    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. 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).

  2. 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, 2020. "Can Volatility Solve the Naive Portfolio Puzzle?," Papers 2005.03204, arXiv.org, revised Feb 2022.

  3. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Lin, Zih-Ying, 2021. "Investor attention and cryptocurrency performance," Finance Research Letters, Elsevier, vol. 40(C).
    6. 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.
    7. 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).
    8. Arjun R & Suprabha KR, 2018. "Predictive modeling of stock indices closing from web search trends," Papers 1804.01676, arXiv.org.
    9. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    10. 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.
    11. 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.

  4. 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.
  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.

    Cited by:

    1. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Adam Clements & Mark Bernard Doolan, 2020. "Combining multivariate volatility forecasts using weighted losses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 628-641, July.
    7. 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. 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.
    9. 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.

  6. 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.
  7. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Ausloos, Marcel & Cerqueti, Roy & Bartolacci, Francesca & Castellano, Nicola G., 2018. "SME investment best strategies. Outliers for assessing how to optimize performance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 754-765.
    7. 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.
    8. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    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.

  8. 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. 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).
    2. Candelon, Bertrand & Luisi , Angelo & Roccazzella, Francesco, 2022. "Fragmentation in the European Monetary Union: Is it really over?," LIDAM Reprints LFIN 2022001, Université catholique de Louvain, Louvain Finance (LFIN).
    3. 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.
    4. 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.
    5. 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, Polish Statistical Association, vol. 21(1), pages 123-136, March.
    6. 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.
    7. Kapetanios, George & Serlenga, Laura & Shin, Yongcheol, 2021. "Estimation and inference for multi-dimensional heterogeneous panel datasets with hierarchical multi-factor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 504-531.
    8. 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.
    9. 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.
    10. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    11. 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).
    12. 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.
    13. Choi, Ahjin & Kang, Kyu Ho, 2023. "Modeling the time-varying dynamic term structure of interest rates," Journal of Banking & Finance, Elsevier, vol. 153(C).
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
    19. Caro Navarro, Ángela & Peña, Daniel, 2018. "Estimation of the common component in Dynamic Factor Models," DES - Working Papers. Statistics and Econometrics. WS 27047, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. 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.
    21. 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.
    22. Jiahe Lin & George Michailidis, 2019. "Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models," Papers 1912.04146, arXiv.org, revised May 2020.

  9. 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. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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.

  10. 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. 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. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Talpsepp, Tõnn & Liivamägi, Kristjan & Vaarmets, Tarvo, 2020. "Academic abilities, education and performance in the stock market," Journal of Banking & Finance, Elsevier, vol. 117(C).
    10. Talpsepp, Tõnn & Vaarmets, Tarvo, 2019. "The disposition effect, performance, stop loss orders and education," Journal of Behavioral and Experimental Finance, Elsevier, vol. 24(C).
    11. Niu, Xiaofei & Li, Jianbiao, 2019. "How Time Constraint Affects the Disposition Effect?," EconStor Preprints 194618, ZBW - Leibniz Information Centre for Economics.

  11. 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. 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.
    3. Yuezhang Che & Shuyan Chen & Xin Liu, 2022. "Sparse Index Tracking Portfolio with Sector Neutrality," Mathematics, MDPI, vol. 10(15), pages 1-22, July.

  12. 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. 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. 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.
    3. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    4. Antonio Díaz & Carlos Esparcia, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, CEPII research center, issue 166, pages 1-22.
    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].
    6. 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.
    7. 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.
    8. 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.
    9. Gijsbert Suren & Guilherme Moura, 2012. "Heteroskedastic Dynamic Factor Models: A Monte Carlo Study," Economics Bulletin, AccessEcon, vol. 32(4), pages 2884-2898.
    10. 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.
    11. 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.
    12. 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.
    13. 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).
    14. 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).
    15. 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.
    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. 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.

  13. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.

  14. 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.
  15. 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.
  16. 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.

  17. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Vladimir Rankovic & Mikica Drenovak & Branko Uroševic & Ranko Jelic, 2016. "Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach," CESifo Working Paper Series 5731, CESifo.
    8. 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.
    9. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    10. Lützenkirchen, Kristina & Rösch, Daniel & Scheule, Harald, 2013. "Ratings based capital adequacy for securitizations," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5236-5247.
    11. 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).
    12. 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.
    13. 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.
    14. 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.

  18. 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, 2019. "Can robust optimization offer improved portfolio performance?: An empirical study of Indian market," Papers 1908.04962, arXiv.org.
    2. Vaughn Gambeta & Roy Kwon, 2020. "Risk Return Trade-Off in Relaxed Risk Parity Portfolio Optimization," JRFM, MDPI, vol. 13(10), pages 1-28, October.
    3. Man Yiu Tsang & Tony Sit & Hoi Ying Wong, 2022. "Adaptive Robust Online Portfolio Selection," Papers 2206.01064, arXiv.org.
    4. 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.
    5. 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.
    6. 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.

  19. 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.
  20. 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. 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.
    2. 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.
    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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