IDEAS home Printed from https://ideas.repec.org/f/c/pgo295.html
   My authors  Follow this author

Pedro Cortesão Godinho
(Pedro Cortesao Godinho)

Citations

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

Working papers

  1. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2017. "On the gains of using high frequency data and higher moments in Portfolio Selection," CeBER Working Papers 2017-02, Centre for Business and Economics Research (CeBER), University of Coimbra.

    Cited by:

    1. Seema REHMAN & Saqib SHARIF & Wali ULLAH, 2021. "Higher Realized Moments and Stock Return Predictability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 48-70, December.

  2. Pedro Godinho, 2006. "Monte Carlo Estimation of Project Volatility for Real Options Analysis," GEMF Working Papers 2006-01, GEMF, Faculty of Economics, University of Coimbra.

    Cited by:

    1. Tianyang Wang & James S. Dyer, 2010. "Valuing Multifactor Real Options Using an Implied Binomial Tree," Decision Analysis, INFORMS, vol. 7(2), pages 185-195, June.
    2. Pedro Godinho, 2015. "Estimating State-Dependent Volatility of Investment Projects: A Simulation Approach," GEMF Working Papers 2015-02, GEMF, Faculty of Economics, University of Coimbra.
    3. Miranda, Oscar & Brandão, Luiz E. & Lazo Lazo, Juan, 2017. "A dynamic model for valuing flexible mining exploration projects under uncertainty," Resources Policy, Elsevier, vol. 52(C), pages 393-404.
    4. Pareja Vasseur, Julián. DBA & Prada Sánchez, Marcela & Moreno Escobar, Martha, 2019. "Volatilidad en Opciones Reales: Revisión Literaria y un Caso de Aplicación en el Sector Petrolero Colombiano || Real Options Volatility: Literature Review and a Case of Application in the Colombian Oi," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 27(1), pages 136-155, June.
    5. Maria-Teresa Bosch-Badia & Joan Montllor-Serrats & Maria-Antonia Tarrazon-Rodon, 2015. "Corporate Social Responsibility: A Real Options Approach to the Challenge of Financial Sustainability," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-37, May.
    6. Zhang, Mingming & Liu, Liyun & Wang, Qunwei & Zhou, Dequn, 2020. "Valuing investment decisions of renewable energy projects considering changing volatility," Energy Economics, Elsevier, vol. 92(C).
    7. Rosa-Isabel González-Muñoz & Jesús Molina-Muñoz & Andrés Mora-Valencia & Javier Perote, 2024. "Real Options Volatility Surface for Valuing Renewable Energy Projects," Energies, MDPI, vol. 17(5), pages 1-13, March.
    8. Steffen Wehkamp & Lucas Schmeling & Lena Vorspel & Fabian Roelcke & Kai-Lukas Windmeier, 2020. "District Energy Systems: Challenges and New Tools for Planning and Evaluation," Energies, MDPI, vol. 13(11), pages 1-20, June.
    9. E. Brandão, Luiz & Dyer, James S. & Hahn, Warren J., 2012. "Volatility estimation for stochastic project value models," European Journal of Operational Research, Elsevier, vol. 220(3), pages 642-648.
    10. Carlos Andrés Zapata Quimbayo, 2020. "OPCIONES REALES Una guía teórico-práctica para la valoración de inversiones bajo incertidumbre mediante modelos en tiempo discreto y simulación de Monte Carlo," Books, Universidad Externado de Colombia, Facultad de Finanzas, Gobierno y Relaciones Internacionales, number 138, April.
    11. Schachter, J.A. & Mancarella, P., 2016. "A critical review of Real Options thinking for valuing investment flexibility in Smart Grids and low carbon energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 261-271.

Articles

  1. Helder Sebastião & Pedro Godinho, 2021. "Forecasting and trading cryptocurrencies with machine learning under changing market conditions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.

    Cited by:

    1. Elie Bouri & Christina Christou & Rangan Gupta, 2022. "Forecasting Returns of Major Cryptocurrencies: Evidence from Regime-Switching Factor Models," Working Papers 202213, University of Pretoria, Department of Economics.
    2. Haris Alibašić, 2023. "Developing an Ethical Framework for Responsible Artificial Intelligence (AI) and Machine Learning (ML) Applications in Cryptocurrency Trading: A Consequentialism Ethics Analysis," FinTech, MDPI, vol. 2(3), pages 1-14, July.
    3. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    4. Yi-Hsiang Lu & Ching-Chiang Yeh & Yu-Mei Kuo, 2024. "Exploring the critical factors affecting the adoption of blockchain: Taiwan’s banking industry," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    5. Hakan Pabuccu & Adrian Barbu, 2024. "Feature selection with annealing for forecasting financial time series," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.
    6. Maghsoodi, Abtin Ijadi, 2023. "Cryptocurrency portfolio allocation using a novel hybrid and predictive big data decision support system," Omega, Elsevier, vol. 115(C).
    7. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    8. Emilio Abad-Segura & Alfonso Infante-Moro & Mariana-Daniela González-Zamar & Eloy López-Meneses, 2021. "Blockchain Technology for Secure Accounting Management: Research Trends Analysis," Mathematics, MDPI, vol. 9(14), pages 1-26, July.
    9. Soria, Jorge & Moya, Jorge & Mohazab, Amin, 2023. "Optimal mining in proof-of-work blockchain protocols," Finance Research Letters, Elsevier, vol. 53(C).
    10. Mingbo Zheng & Gen-Fu Feng & Xinxin Zhao & Chun-Ping Chang, 2023. "The transaction behavior of cryptocurrency and electricity consumption," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-18, December.
    11. Tina Linden & Tina Shirazi, 2023. "Markets in crypto-assets regulation: Does it provide legal certainty and increase adoption of crypto-assets?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-30, December.
    12. Husam Rjoub & Tomiwa Sunday Adebayo & Dervis Kirikkaleli, 2023. "Blockchain technology-based FinTech banking sector involvement using adaptive neuro-fuzzy-based K-nearest neighbors algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    13. Şirin Özlem & Omer Faruk Tan, 2022. "Predicting cash holdings using supervised machine learning algorithms," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-19, December.
    14. Nuray Tosunoğlu & Hilal Abacı & Gizem Ateş & Neslihan Saygılı Akkaya, 2023. "Artificial neural network analysis of the day of the week anomaly in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.
    15. Yu Song & Bo Chen & Xin-Yi Wang, 2023. "Cryptocurrency technology revolution: are Bitcoin prices and terrorist attacks related?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-20, December.
    16. Laurens Swinkels, 2023. "Empirical evidence on the ownership and liquidity of real estate tokens," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-29, December.
    17. Ladislav Kristoufek, 2022. "On the role of stablecoins in cryptoasset pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    18. Zhiqi Feng & Yongli Li & Xiaochen Ma, 2023. "Blockchain-oriented approach for detecting cyber-attack transactions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
    19. Sudersan Behera & Sarat Chandra Nayak & A. V. S. Pavan Kumar, 2024. "Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1219-1258, August.
    20. Adrian Millea, 2021. "Deep Reinforcement Learning for Trading—A Critical Survey," Data, MDPI, vol. 6(11), pages 1-25, November.
    21. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    22. Wang, Yaqi & Wang, Chunfeng & Sensoy, Ahmet & Yao, Shouyu & Cheng, Feiyang, 2022. "Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning," Research in International Business and Finance, Elsevier, vol. 62(C).
    23. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.
    24. Duygu Ider & Stefan Lessmann, 2022. "Forecasting Cryptocurrency Returns from Sentiment Signals: An Analysis of BERT Classifiers and Weak Supervision," Papers 2204.05781, arXiv.org, revised Mar 2023.
    25. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
    26. Fakhfekh, Mohamed & Bejaoui, Azza & Bariviera, Aurelio F. & Jeribi, Ahmed, 2024. "Dependence structure between NFT, DeFi and cryptocurrencies in turbulent times: An Archimax copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    27. Petr Suler & Zuzana Rowland & Tomas Krulicky, 2021. "Evaluation of the Accuracy of Machine Learning Predictions of the Czech Republic’s Exports to the China," JRFM, MDPI, vol. 14(2), pages 1-30, February.
    28. Abdul Jabbar & Syed Qaisar Jalil, 2024. "A Comprehensive Analysis of Machine Learning Models for Algorithmic Trading of Bitcoin," Papers 2407.18334, arXiv.org.
    29. Luis Lorenzo & Javier Arroyo, 2023. "Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    30. Albert Antwi & Emmanuel N. Gyamfi & Anokye M. Adam, 2024. "Forecasting tail risk of skewed financial returns having exponential‐polynomial tails," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2731-2748, November.
    31. Wujun Lv & Tao Pang & Xiaobao Xia & Jingzhou Yan, 2023. "Dynamic portfolio choice with uncertain rare-events risk in stock and cryptocurrency markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    32. Fantazzini, Dean & Calabrese, Raffaella, 2021. "Crypto-exchanges and Credit Risk: Modelling and Forecasting the Probability of Closure," MPRA Paper 110391, University Library of Munich, Germany.
    33. Marcel C. Minutolo & Werner Kristjanpoller & Prakash Dheeriya, 2022. "Impact of COVID-19 effective reproductive rate on cryptocurrency," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-27, December.
    34. Alessio Brini & Jimmie Lenz, 2024. "A comparison of cryptocurrency volatility-benchmarking new and mature asset classes," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-38, December.
    35. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2023. "The predictive power of Bitcoin prices for the realized volatility of US stock sector returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    36. Oluwadamilare Omole & David Enke, 2024. "Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.
    37. De Blasis, Riccardo & Galati, Luca & Webb, Alexander & Webb, Robert I., 2022. "Intelligent design: Stablecoins (in)stability and collateral during market turbulence," Economics & Statistics Discussion Papers esdp22088, University of Molise, Department of Economics.
    38. Walid Mensi & Mariya Gubareva & Hee-Un Ko & Xuan Vinh Vo & Sang Hoon Kang, 2023. "Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    39. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    40. Iqbal H. Sarker, 2023. "Machine Learning for Intelligent Data Analysis and Automation in Cybersecurity: Current and Future Prospects," Annals of Data Science, Springer, vol. 10(6), pages 1473-1498, December.
    41. Haji Suleman Ali & Feiyan Jia & Zhiyuan Lou & Jingui Xie, 2023. "Effect of blockchain technology initiatives on firms’ market value," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-35, December.
    42. Rubaiyat Ahsan Bhuiyan & Afzol Husain & Changyong Zhang, 2023. "Diversification evidence of bitcoin and gold from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
    43. Waqas Hanif & Hee-Un Ko & Linh Pham & Sang Hoon Kang, 2023. "Dynamic connectedness and network in the high moments of cryptocurrency, stock, and commodity markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    44. Dongyoung Kim & Sungwon Jung & Yongwook Jeong, 2021. "Theft Prediction Model Based on Spatial Clustering to Reflect Spatial Characteristics of Adjacent Lands," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    45. Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2023. "A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return forecasting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    46. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    47. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    48. Ahmed BenSaïda, 2023. "The linkage between Bitcoin and foreign exchanges in developed and emerging markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    49. Danilo Bazzanella & Andrea Gangemi, 2023. "Bitcoin: a new proof-of-work system with reduced variance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-14, December.

  2. Pedro Torres & Pedro Godinho, 2020. "The influence of city reputation on T-KIBS concentration," European Planning Studies, Taylor & Francis Journals, vol. 28(10), pages 1960-1978, October.

    Cited by:

    1. Vladimir Pavković & Darjan Karabašević & Jelena Jević & Goran Jević, 2021. "The Relationship between Cities’ Cultural Strength, Reputation, and Tourism Intensity: Empirical Evidence on a Sample of the Best-Reputable European Cities," Sustainability, MDPI, vol. 13(16), pages 1-20, August.
    2. Annadurai Arumugam & Senthilkumar Nakkeeran & Rajalakshmi Subramaniam, 2023. "Exploring the Factors Influencing Heritage Tourism Development: A Model Development," Sustainability, MDPI, vol. 15(15), pages 1-18, August.

  3. Sandra Caçador & Joana Matos Dias & Pedro Godinho, 2020. "Global minimum variance portfolios under uncertainty: a robust optimization approach," Journal of Global Optimization, Springer, vol. 76(2), pages 267-293, February.

    Cited by:

    1. Salo, Ahti & Doumpos, Michalis & Liesiö, Juuso & Zopounidis, Constantin, 2024. "Fifty years of portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(1), pages 1-18.

  4. Luís Lobato Macedo & Pedro Godinho & Maria João Alves, 2020. "A Comparative Study of Technical Trading Strategies Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 349-381, January.

    Cited by:

    1. Jaime Alberto Gómez Vilchis & Federico Hernández Álvarez & Luis Ignacio Román de la Sancha, 2021. "Autómata Evolutivo (AE) para el mercado accionario usando Martingalas y un Algoritmo Genético," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-22, Octubre -.
    2. Marco Corazza & Claudio Pizzi & Andrea Marchioni, 2024. "A financial trading system with optimized indicator setting, trading rule definition, and signal aggregation through Particle Swarm Optimization," Computational Management Science, Springer, vol. 21(1), pages 1-29, June.
    3. Vinícius Ferraz & Thomas Pitz, 2024. "Analyzing the Impact of Strategic Behavior in an Evolutionary Learning Model Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 437-475, February.

  5. Sebastião, Helder & Godinho, Pedro, 2020. "Bitcoin futures: An effective tool for hedging cryptocurrencies," Finance Research Letters, Elsevier, vol. 33(C).

    Cited by:

    1. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    2. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    3. Mo, Bin & Meng, Juan & Zheng, Liping, 2022. "Time and frequency dynamics of connectedness between cryptocurrencies and commodity markets," Resources Policy, Elsevier, vol. 77(C).
    4. Jovanka Lili Matic & Natalie Packham & Wolfgang Karl Härdle, 2023. "Hedging cryptocurrency options," Review of Derivatives Research, Springer, vol. 26(1), pages 91-133, April.
    5. Adediran, Idris A. & Yinusa, Olalekan D. & Lakhani, Kanwal Hammad, 2021. "Where lies the silver lining when uncertainty hang dark clouds over the global financial markets?," Resources Policy, Elsevier, vol. 70(C).
    6. Zhang, Chuanhai & Ma, Huan & Arkorful, Gideon Bruce & Peng, Zhe, 2023. "The impacts of futures trading on volatility and volatility asymmetry of Bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    7. Zhang, Chuanhai & Ma, Huan & Liao, Xiaosai, 2023. "Futures trading activity and the jump risk of spot market: Evidence from the bitcoin market," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    8. Shimeng Shi & Jia Zhai & Yingying Wu, 2024. "Informational inefficiency on bitcoin futures," The European Journal of Finance, Taylor & Francis Journals, vol. 30(6), pages 642-667, April.
    9. Alexandros Koulis & Constantinos Kyriakopoulos, 2021. "Hedge ratio estimation: A note on the Bitcoin future contract," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 125-131.
    10. Dun Li & Dezhi Han & Zibin Zheng & Tien-Hsiung Weng & Kuan-Ching Li & Ming Li & Shaokang Cai, 2024. "Does Short-and-Distort Scheme Really Exist? A Bitcoin Futures Audit Scheme through BIRCH & BPNN Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1649-1671, April.
    11. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    12. Guo, Zi-Yi, 2022. "Risk management of Bitcoin futures with GARCH models," Finance Research Letters, Elsevier, vol. 45(C).
    13. Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
    14. Esparcia, Carlos & Escribano, Ana & Jareño, Francisco, 2024. "Assessing the crypto market stability after the FTX collapse: A study of high frequency volatility and connectedness," International Review of Financial Analysis, Elsevier, vol. 94(C).
    15. Abdulnasser Hatemi-J, 2024. "Testing for the Asymmetric Optimal Hedge Ratios: With an Application to Bitcoin," Papers 2407.19932, arXiv.org, revised Aug 2024.
    16. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2021. "Trading activity and price discovery in Bitcoin futures markets," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 107-120.
    17. Shimeng Shi, 2022. "Bitcoin futures risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2190-2217, December.
    18. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    19. Jun Deng & Huifeng Pan & Shuyu Zhang & Bin Zou, 2021. "Optimal Bitcoin trading with inverse futures," Annals of Operations Research, Springer, vol. 304(1), pages 139-163, September.
    20. Weige Huang & Xiang Gao, 2023. "Forecasting Bitcoin Futures: A Lasso-BMA Two-Step Predictor Selection for Investment and Hedging Strategies," SAGE Open, , vol. 13(1), pages 21582440231, January.
    21. Esparcia, Carlos & López, Raquel, 2024. "Performance of crypto-Forex portfolios based on intraday data," Research in International Business and Finance, Elsevier, vol. 69(C).
    22. Esparcia, Carlos & Escribano, Ana & Jareño, Francisco, 2023. "Did cryptomarket chaos unleash Silvergate's bankruptcy? investigating the high-frequency volatility and connectedness behind the collapse," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    23. Yan Hu & Jian Ni, 2024. "A deep learning‐based financial hedging approach for the effective management of commodity risks," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(6), pages 879-900, June.

  6. Augusto, Mário & Godinho, Pedro & Torres, Pedro, 2019. "Building customers’ resilience to negative information in the airline industry," Journal of Retailing and Consumer Services, Elsevier, vol. 50(C), pages 235-248.

    Cited by:

    1. Wallace, Elaine & Torres, Pedro & Augusto, Mário & Stefuryn, Maryana, 2021. "Outcomes for self-expressive brands followed on social media: Identifying different paths for inner self-expressive and social self-expressive brands," Journal of Business Research, Elsevier, vol. 135(C), pages 519-531.
    2. Rajesh, R. & Agariya, Arun Kumar & Rajendran, Chandrasekharan, 2021. "Predicting resilience in retailing using grey theory and moving probability based Markov models," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    3. Jorge Guadalupe Barrón Torres & Mónica Lorena Sánchez Limón, 2022. "Resiliencia organizacional: una revisión teórica de literatura," Estudios Gerenciales, Universidad Icesi, vol. 38(163), pages 235-249, June.

  7. Pedro Godinho & Pedro Cerqueira, 2018. "The Impact of Expectations, Match Importance, and Results in the Stock Prices of European Football Teams," Journal of Sports Economics, , vol. 19(2), pages 230-278, February.

    Cited by:

    1. Oguz Ersan & Ender Demir, 2017. "New Season New Hopes: Off-Season Optimism," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 5(4), pages 36-49.
    2. Fakhrul Hasan & Basil Al-Najjar, 2024. "Exploring the connections: Dividend announcements, stock market returns, and major sporting events," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 889-923, October.
    3. Altuğ Tanaltay & Amirreza Safari Langroudi & Raha Akhavan-Tabatabaei & Nihat Kasap, 2021. "Can Social Media Predict Soccer Clubs’ Stock Prices? The Case of Turkish Teams and Twitter," SAGE Open, , vol. 11(2), pages 21582440211, April.

  8. Pedro Godinho, 2018. "Simulation-based estimation of state-dependent project volatility," The Engineering Economist, Taylor & Francis Journals, vol. 63(3), pages 188-216, July.

    Cited by:

    1. Rosa-Isabel González-Muñoz & Jesús Molina-Muñoz & Andrés Mora-Valencia & Javier Perote, 2024. "Real Options Volatility Surface for Valuing Renewable Energy Projects," Energies, MDPI, vol. 17(5), pages 1-13, March.

  9. Torres, Pedro & Augusto, Mário & Godinho, Pedro, 2017. "Predicting high consumer-brand identification and high repurchase: Necessary and sufficient conditions," Journal of Business Research, Elsevier, vol. 79(C), pages 52-65.

    Cited by:

    1. Thac Dang‐Van & Tan Vo‐Thanh & Jianming Wang & Ninh Nguyen, 2023. "Luxury hotels' green practices and consumer brand identification: The roles of perceived green service innovation and perceived values," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4568-4583, November.
    2. Büyükdağ, Naci & Kitapci, Olgun, 2021. "Antecedents of consumer-brand identification in terms of belonging brands," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    3. Michaela Merk & Géraldine Michel, 2019. "The dark side of salesperson brand identification in the luxury sector: When brand orientation generates management issues and negative customer perception," Post-Print hal-02045833, HAL.
    4. Ayşegül Acar & Naci Büyükdağ & Burak Türten & Ersin Diker & Gülsüm Çalışır, 2024. "The role of brand identity, brand lifestyle congruence, and brand satisfaction on repurchase intention: a multi-group structural equation model," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    5. Merk, Michaela & Michel, Géraldine, 2019. "The dark side of salesperson brand identification in the luxury sector: When brand orientation generates management issues and negative customer perception," Journal of Business Research, Elsevier, vol. 102(C), pages 339-352.
    6. Chatzipanagiotou, Kalliopi & Christodoulides, George & Veloutsou, Cleopatra, 2019. "Managing the consumer-based brand equity process: A cross-cultural perspective," International Business Review, Elsevier, vol. 28(2), pages 328-343.
    7. Abosag, Ibrahim & Ramadan, Zahy B. & Baker, Tom & Jin, Zhongqi, 2020. "Customers' need for uniqueness theory versus brand congruence theory: The impact on satisfaction with social network sites," Journal of Business Research, Elsevier, vol. 117(C), pages 862-872.
    8. Saloua Bennaghmouch & Martine Deparis & Hanene Oueslati & Marie-Catherine Paquier & Gerald Cohen & Laurent Grimal & Hocine Sadok, 2021. "Franchise et RSE : impact social et environnemental de la franchise," Working Papers hal-03694438, HAL.
    9. Davood Ghorbanzadeh & K. D. V. Prasad & Natalia Alekseevna Prodanova & Iskandar Muda & Joko Suryono & Nafisa Yuldasheva, 2024. "Exploration of the concept of brand love in city branding: antecedents and consequences," Place Branding and Public Diplomacy, Palgrave Macmillan, vol. 20(2), pages 142-156, June.
    10. Daria Plotkina & Landisoa Rabeson, 2022. "The role of transactionality of mobile branded apps in brand experience and its impact on loyalty," Journal of Brand Management, Palgrave Macmillan, vol. 29(5), pages 470-483, September.
    11. Jake An & Diem Khac Xuan Do & Liem Viet Ngo & Tran Ha Minh Quan, 2019. "Turning brand credibility into positive word-of-mouth: integrating the signaling and social identity perspectives," Journal of Brand Management, Palgrave Macmillan, vol. 26(2), pages 157-175, March.
    12. Augusto, Mário & Godinho, Pedro & Torres, Pedro, 2019. "Building customers’ resilience to negative information in the airline industry," Journal of Retailing and Consumer Services, Elsevier, vol. 50(C), pages 235-248.

  10. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.

    Cited by:

    1. Brito Rui Pedro & Sebastião Helder & Godinho Pedro, 2018. "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business, Sciendo, vol. 65(4), pages 365-383, December.
    2. Zia-ur-Rehman Rao & Muhammad Zubair Tauni & Tanveer Ahsan & Muhammad Umar, 2020. "Do mutual funds have consistency in their performance?," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 19(2), pages 139-153, May.

  11. Reigadinha, Tânia & Godinho, Pedro & Dias, Joana, 2017. "Portuguese food retailers – Exploring three classic theories of retail location," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 102-116.

    Cited by:

    1. Yıldız, Nurdan & Tüysüz, Fatih, 2019. "A hybrid multi-criteria decision making approach for strategic retail location investment: Application to Turkish food retailing," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    2. Formánek, Tomáš & Sokol, Ondřej, 2022. "Location effects: Geo-spatial and socio-demographic determinants of sales dynamics in brick-and-mortar retail stores," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    3. Aversa, Joseph & Hernandez, Tony & Doherty, Sean, 2021. "Incorporating big data within retail organizations: A case study approach," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    4. Tiyachareonsri, Sirikunya & Chavarnakul, Thira & Chandrachai, Achara & Triukose, Sipat, 2024. "How consumer preference determines site selection in a metropolitan setting: Analysis of retailer perspective to stay ahead of the competition in the aftermath of a large-scale crisis," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    5. Hallak, Rob & Assaker, Guy & O’Connor, Peter & Lee, Craig, 2018. "Firm performance in the upscale restaurant sector: The effects of resilience, creative self-efficacy, innovation and industry experience," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 229-240.
    6. Wonjun Cho & Minho Kim & Hyunjung Kim & Youngsang Kwon, 2020. "Transforming Housing to Commercial Use: A Case Study on Commercial Gentrification in Yeon-nam District, Seoul," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    7. Olga Porro & Francesc Pardo-Bosch & Núria Agell & Mónica Sánchez, 2020. "Understanding Location Decisions of Energy Multinational Enterprises within the European Smart Cities’ Context: An Integrated AHP and Extended Fuzzy Linguistic TOPSIS Method," Energies, MDPI, vol. 13(10), pages 1-29, May.
    8. Adeniyi, Oluwole & Brown, Abraham & Whysall, Paul, 2020. "Retail location preferences: A comparative analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    9. Rice, Murray & Sorenson, Matthew & Aversa, Joseph, 2022. "The geography of lifestyle center growth: The emergence of a retail cluster format in the United States," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    10. Rui Colaço & João de Abreu e Silva, 2021. "Commercial Classification and Location Modelling: Integrating Different Perspectives on Commercial Location and Structure," Land, MDPI, vol. 10(6), pages 1-19, May.
    11. Ceren Erdin & Halil Emre Akbaş, 2019. "A Comparative Analysis of Fuzzy TOPSIS and Geographic Information Systems (GIS) for the Location Selection of Shopping Malls: A Case Study from Turkey," Sustainability, MDPI, vol. 11(14), pages 1-22, July.
    12. Gonzalo Wandosell & María Concepción Parra-Meroño & Raul Baños, 2019. "Online Store Locator: An Essential Resource for Retailers in the 21st Century," Social Sciences, MDPI, vol. 8(2), pages 1-13, February.

  12. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Efficient skewness/semivariance portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 331-346, September.

    Cited by:

    1. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    2. Heonbae Jeon & Soonbong Lee & Hongseon Kim & Seung Bum Soh & Seongmoon Kim, 2023. "Portfolio Evaluation with the Vector Distance Based on Portfolio Composition," Mathematics, MDPI, vol. 11(1), pages 1-19, January.
    3. C. P. Brás & A. L. Custódio, 2020. "On the use of polynomial models in multiobjective directional direct search," Computational Optimization and Applications, Springer, vol. 77(3), pages 897-918, December.

  13. Nuno Barreira & Pedro Godinho & Paulo Melo, 2013. "Nowcasting unemployment rate and new car sales in south-western Europe with Google Trends," Netnomics, Springer, vol. 14(3), pages 129-165, November.

    Cited by:

    1. Mihaela Simionescu & Javier Cifuentes-Faura, 2022. "Forecasting National and Regional Youth Unemployment in Spain Using Google Trends," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1187-1216, December.
    2. 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.
    3. Jacques Bughin, 2015. "Google searches and twitter mood: nowcasting telecom sales performance," Netnomics, Springer, vol. 16(1), pages 87-105, August.
    4. Dimpfl, Thomas & Langen, Tobias, 2015. "A Cross-Country Analysis of Unemployment and Bonds with Long-Memory Relations," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112921, Verein für Socialpolitik / German Economic Association.
    5. Mihaela Simionescu & Dalia Streimikiene & Wadim Strielkowski, 2020. "What Does Google Trends Tell Us about the Impact of Brexit on the Unemployment Rate in the UK?," Sustainability, MDPI, vol. 12(3), pages 1-10, January.
    6. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
    7. Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    8. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    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. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    11. N. Nima Haghighi & Xiaoyue Cathy Liu & Ran Wei & Wenwen Li & Hu Shao, 2018. "Using Twitter data for transit performance assessment: a framework for evaluating transit riders’ opinions about quality of service," Public Transport, Springer, vol. 10(2), pages 363-377, August.
    12. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
    13. Nymand-Andersen, Per & Pantelidis, Emmanouil, 2018. "Google econometrics: nowcasting euro area car sales and big data quality requirements," Statistics Paper Series 30, European Central Bank.
    14. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
    15. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
    16. Andrius Grybauskas & Vaida Pilinkienė & Mantas Lukauskas & Alina Stundžienė & Jurgita Bruneckienė, 2023. "Nowcasting Unemployment Using Neural Networks and Multi-Dimensional Google Trends Data," Economies, MDPI, vol. 11(5), pages 1-23, April.
    17. Naccarato, Alessia & Falorsi, Stefano & Loriga, Silvia & Pierini, Andrea, 2018. "Combining official and Google Trends data to forecast the Italian youth unemployment rate," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 114-122.
    18. Simionescu, Mihaela & Cifuentes-Faura, Javier, 2022. "Can unemployment forecasts based on Google Trends help government design better policies? An investigation based on Spain and Portugal," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 1-21.
    19. Gulsah Senturk, 2022. "Can Google Search Data Improve the Unemployment Rate Forecasting Model? An Empirical Analysis for Turkey," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 229-244, July.
    20. 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. Godinho, Pedro & Dias, Joana, 2013. "Two-player simultaneous location game: Preferential rights and overbidding," European Journal of Operational Research, Elsevier, vol. 229(3), pages 663-672.

    Cited by:

    1. Zhang, Chi & Ramirez-Marquez, José Emmanuel & Wang, Jianhui, 2015. "Critical infrastructure protection using secrecy – A discrete simultaneous game," European Journal of Operational Research, Elsevier, vol. 242(1), pages 212-221.
    2. Ramirez-Marquez, José Emmanuel & Li, Qing, 2018. "Locating and protecting facilities from intentional attacks using secrecyAuthor-Name: Zhang, Chi," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 51-62.
    3. Dilek, Hande & Karaer, Özgen & Nadar, Emre, 2018. "Retail location competition under carbon penalty," European Journal of Operational Research, Elsevier, vol. 269(1), pages 146-158.
    4. Yolmeh, Abdolmajid & Baykal-Gürsoy, Melike, 2021. "Weighted network search games with multiple hidden objects and multiple search teams," European Journal of Operational Research, Elsevier, vol. 289(1), pages 338-349.

  15. Godinho, Pedro & Branco, Fernando G., 2012. "Adaptive policies for multi-mode project scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 216(3), pages 553-562.

    Cited by:

    1. Gutjahr, Walter J., 2015. "Bi-Objective Multi-Mode Project Scheduling Under Risk Aversion," European Journal of Operational Research, Elsevier, vol. 246(2), pages 421-434.
    2. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    3. Pedro Godinho & João Paulo Costa, 2020. "A stochastic model and algorithms for determining efficient time–cost tradeoffs for a project activity," Operational Research, Springer, vol. 20(1), pages 319-348, March.
    4. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).

  16. Pedro Godinho, 2012. "Can abnormal returns be earned on bandwidth-bounded currencies? Evidence from a genetic algorithm," Economic Issues Journal Articles, Economic Issues, vol. 17(1), pages 1-26, March.

    Cited by:

    1. Luís Lobato Macedo & Pedro Godinho & Maria João Alves, 2020. "A Comparative Study of Technical Trading Strategies Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 349-381, January.
    2. Simone Cirillo & Stefan Lloyd & Peter Nordin, 2014. "Evolving intraday foreign exchange trading strategies utilizing multiple instruments price series," Papers 1411.2153, arXiv.org.

  17. Pedro Godinho & Joana Dias, 2011. "Fuel taxes and tolls in cost-benefit analysis," Economics Bulletin, AccessEcon, vol. 31(2), pages 1372-1378.

    Cited by:

    1. Massiani, Jérôme & Maltese, Ila, 2022. "Thirty years of socio-economic evaluation of the Lyon–Turin High–Speed rail project," Research in Transportation Economics, Elsevier, vol. 94(C).

  18. Pedro Godinho & Joao Paulo Costa & Joana Fialho & Ricardo Afonso, 2011. "Some issues about the application of the analytic hierarchy process to R&D project selection," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 13(1), pages 26-41.

    Cited by:

    1. García-Melón, Mónica & Poveda-Bautista, Rocío & Del Valle M., José L., 2015. "Using the strategic relative alignment index for the selection of portfolio projects application to a public Venezuelan Power Corporation," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 54-66.

  19. Godinho, Pedro & Dias, Joana, 2010. "A two-player competitive discrete location model with simultaneous decisions," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1419-1432, December.

    Cited by:

    1. Zhang, Chi & Ramirez-Marquez, José Emmanuel & Wang, Jianhui, 2015. "Critical infrastructure protection using secrecy – A discrete simultaneous game," European Journal of Operational Research, Elsevier, vol. 242(1), pages 212-221.
    2. Ramirez-Marquez, José Emmanuel & Li, Qing, 2018. "Locating and protecting facilities from intentional attacks using secrecyAuthor-Name: Zhang, Chi," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 51-62.
    3. Crönert, Tobias & Martin, Layla & Minner, Stefan & Tang, Christopher S., 2024. "Inverse optimization of integer programming games for parameter estimation arising from competitive retail location selection," European Journal of Operational Research, Elsevier, vol. 312(3), pages 938-953.
    4. Godinho, Pedro & Dias, Joana, 2013. "Two-player simultaneous location game: Preferential rights and overbidding," European Journal of Operational Research, Elsevier, vol. 229(3), pages 663-672.
    5. Berno Buechel & Nils Roehl, 2013. "Robust Equilibria in Location Games," Working Papers CIE 58, Paderborn University, CIE Center for International Economics.
    6. Dilek, Hande & Karaer, Özgen & Nadar, Emre, 2018. "Retail location competition under carbon penalty," European Journal of Operational Research, Elsevier, vol. 269(1), pages 146-158.
    7. Yolmeh, Abdolmajid & Baykal-Gürsoy, Melike, 2021. "Weighted network search games with multiple hidden objects and multiple search teams," European Journal of Operational Research, Elsevier, vol. 289(1), pages 338-349.

  20. Costa, Joao P. & Melo, Paulo & Godinho, Pedro & Dias, Luis C., 2003. "The AGAP system: A GDSS for project analysis and evaluation," European Journal of Operational Research, Elsevier, vol. 145(2), pages 287-303, March.

    Cited by:

    1. Madjid Tavana & Mariya Sodenkamp & Leena Suhl, 2010. "A soft multi-criteria decision analysis model with application to the European Union enlargement," Annals of Operations Research, Springer, vol. 181(1), pages 393-421, December.
    2. M Tavana & M A Sodenkamp, 2010. "A fuzzy multi-criteria decision analysis model for advanced technology assessment at Kennedy Space Center," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(10), pages 1459-1470, October.
    3. Antunes, Francisco & Melo, Paulo & Costa, Joao Paulo, 2007. "Information management in distributed collaborative systems: The case of collaboration studio," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1385-1399, March.
    4. Galo, Nadya Regina & Calache, Lucas Daniel Del Rosso & Carpinetti, Luiz Cesar Ribeiro, 2018. "A group decision approach for supplier categorization based on hesitant fuzzy and ELECTRE TRI," International Journal of Production Economics, Elsevier, vol. 202(C), pages 182-196.
    5. Alessio Ishizaka & Philippe Nemery, 2013. "A Multi-Criteria Group Decision Framework for Partner Grouping When Sharing Facilities," Group Decision and Negotiation, Springer, vol. 22(4), pages 773-799, July.
    6. Jessop, Alan, 2014. "IMP: A decision aid for multiattribute evaluation using imprecise weight estimates," Omega, Elsevier, vol. 49(C), pages 18-29.
    7. Fernandez, Eduardo & Olmedo, Rafael, 2013. "An outranking-based general approach to solving group multi-objective optimization problems," European Journal of Operational Research, Elsevier, vol. 225(3), pages 497-506.
    8. Francineide Morais Bezerra & Paulo Melo & João Paulo Costa, 2014. "Visual and Interactive Comparative Analysis of Individual Opinions: A Group Decision Support Tool," Group Decision and Negotiation, Springer, vol. 23(1), pages 101-125, January.

  21. Pedro Cortesao Godinho & Joao Paulo Costa, 2002. "A note on the use of bicriteria decision trees in capital budgeting," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 4(1), pages 147-158.

    Cited by:

    1. Pedro Godinho & João Paulo Costa, 2004. "The Use of Cost and Time in Project Decision Trees: A model and an application," Notas Económicas, Faculty of Economics, University of Coimbra, issue 20, pages 145-161, December.

  22. A. Ricardo M. Afonso & Pedro M. Cortesão Godinho & João Paulo Costa, 1999. "Linhas de orientação para a selecção de métodos de avaliação de projectos de investimento em sistemas de apoio à decisão," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(4), pages 267-289.

    Cited by:

    1. Costa, Joao P. & Melo, Paulo & Godinho, Pedro & Dias, Luis C., 2003. "The AGAP system: A GDSS for project analysis and evaluation," European Journal of Operational Research, Elsevier, vol. 145(2), pages 287-303, March.

Chapters

    Sorry, no citations of chapters recorded.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.