IDEAS home Printed from https://ideas.repec.org/f/c/pta557.html
   My authors  Follow this author

Nick Taylor

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. Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Díaz & Menachem Abudy & To, 2021. "Non-Standard Errors," Working Paper Series, Social and Economic Sciences 2021-11, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian Brownlees & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
    • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Frömmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
    • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Ferrara, Gerardo & Jurkatis, Simon, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
    • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
    • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
    • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    Cited by:

    1. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Management Science Reproducibility Collaboration, 2023. "Reproducibility in Management Science," Department for Strategy and Innovation Working Paper Series 03/2023, WU Vienna University of Economics and Business.
    2. Müller, Isabella & Noth, Felix & Tonzer, Lena, 2022. "A note on the use of syndicated loan data," IWH Discussion Papers 17/2022, Halle Institute for Economic Research (IWH).
    3. Stephen A. Gorman & Frank J. Fabozzi, 2023. "Alternative risk premium: specification noise," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 459-473, October.
    4. Nate Breznau & Eike Mark Rinke & Alexander Wuttke & Hung H. V. Nguyen & Muna Adem & Jule Adriaans & Amalia Alvarez-Benjumea & Henrik K. Andersen & Daniel Auer & Flavio Azevedo & Oke Bahnsen & Dave Bal, 2022. "Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(44), pages 2203150119-, November.
    5. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    6. Christoph Huber & Christian König-Kersting, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck.
    7. Christophe Pérignon & Olivier Akmansoy & Christophe Hurlin & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johanneson & Michael Kirchler & Albert Menkveld & Michael Razen & Utz Weitzel, 2022. "Reproducibility of Empirical Results: Evidence from 1,000 Tests in Finance," Working Papers hal-03810013, HAL.
    8. Dreber, Anna & Johannesson, Magnus, 2023. "A framework for evaluating reproducibility and replicability in economics," I4R Discussion Paper Series 38, The Institute for Replication (I4R).

  2. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and Volatility Spillover effects in Equity Markets during and after the Global Financial Crisis: an MEM approach," Cardiff Economics Working Papers E2018/6, Cardiff University, Cardiff Business School, Economics Section.

    Cited by:

    1. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2023. "Asymmetric volatility spillover between crude oil and other asset markets," Cardiff Economics Working Papers E2023/27, Cardiff University, Cardiff Business School, Economics Section.
    2. Gaoxiu Qiao & Yangli Cao & Feng Ma & Weiping Li, 2023. "Liquidity and realized covariance forecasting: a hybrid method with model uncertainty," Empirical Economics, Springer, vol. 64(1), pages 437-463, January.
    3. Achraf Ghorbel & Wajdi Frikha & Yasmine Snene Manzli, 2022. "Testing for asymmetric non-linear short- and long-run relationships between crypto-currencies and stock markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 387-425, September.
    4. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les & Xu, Danyang, 2021. "Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 55-81.
    5. Suardi, Sandy & Xu, Caihong & Zhou, Z. Ivy, 2022. "COVID-19 pandemic and liquidity commonality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    6. Tongshuai Qiao & Liyan Han, 2023. "COVID‐19 and tail risk contagion across commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(2), pages 242-272, February.
    7. Lahmiri, Salim & Bekiros, Stelios, 2020. "The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    8. Sifat, Imtiaz & Zarei, Alireza & Hosseini, Seyedmehdi & Bouri, Elie, 2022. "Interbank liquidity risk transmission to large emerging markets in crisis periods," International Review of Financial Analysis, Elsevier, vol. 82(C).

  3. Taylor, Nick & Xu, Yongdeng, 2013. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Cardiff Economics Working Papers E2013/7, Cardiff University, Cardiff Business School, Economics Section.

    Cited by:

    1. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 122, Paderborn University, CIE Center for International Economics.
    2. Cipollini, Fabrizio & Gallo, Giampiero M. & Otranto, Edoardo, 2021. "Realized volatility forecasting: Robustness to measurement errors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 44-57.
    3. Carol Alexander & Daniel Heck & Andreas Kaeck, 2021. "The Role of Binance in Bitcoin Volatility Transmission," Papers 2107.00298, arXiv.org, revised Aug 2021.
    4. Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    5. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    6. Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 2020. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 532-555.
    7. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    8. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 125, Paderborn University, CIE Center for International Economics.

  4. Anne Opschoor & Michel van der Wel & Dick van Dijk & Nick Taylor, 2012. "On the Effects of Private Information on Volatility," CREATES Research Papers 2012-08, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Heejoon Han & Dennis Kristensen, 2013. "Asymptotic theory for the QMLE in GARCH-X models with stationary and non-stationary covariates," CeMMAP working papers CWP18/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  5. Nicholas Taylor, 2004. "A New Econometric Model Of Index Arbitrage," Royal Economic Society Annual Conference 2004 69, Royal Economic Society.

    Cited by:

    1. Jieye Qin & Christopher J. Green & Kavita Sirichand, 2019. "Determinants of Nikkei futures mispricing in international markets: Dividend clustering, currency risk, and transaction costs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(10), pages 1269-1300, October.
    2. Laurent Deville & Carole Gresse & Béatrice de Séverac, 2014. "Direct and Indirect Effects of Index ETFs on Spot†Futures Pricing and Liquidity: Evidence from the CAC 40 Index," European Financial Management, European Financial Management Association, vol. 20(2), pages 352-373, March.
    3. Charlie X. Cai & Qi Zhang, 2016. "High†Frequency Exchange Rate Forecasting," European Financial Management, European Financial Management Association, vol. 22(1), pages 120-141, January.
    4. Yu‐Lun Chen & Yen‐Hsien Lee & Robin K. Chou & Ya‐Kai Chang, 2021. "Arbitrage trading and price discovery of the regular and mini Taiwan stock index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 926-948, June.

  6. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.

    Cited by:

    1. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.
    3. Martin Wagner, 2004. "A Comparison of Johansen's, Bierens’ and the Subspace Algorithm Method for Cointegration Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 399-424, July.
    4. Krauss, Christopher & Herrmann, Klaus & Teis, Stefan, 2015. "On the power and size properties of cointegration tests in the light of high-frequency stylized facts," FAU Discussion Papers in Economics 11/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    5. David O. Cushman, 2003. "Further evidence on the size and power of the Bierens and Johansen cointegration procedures," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.
    6. Giulio Cifarelli & Giovanna Paladino, 2008. "Reserve overstocking in a highly integrated world. New evidence from Asia and Latin America," The European Journal of Finance, Taylor & Francis Journals, vol. 14(4), pages 315-336.

  7. Nick Taylor & Dick van Dijk & Philip Hans Franses & André Lucas, 1999. "SETS, Arbitrage Activity, and Stock Price Dynamics," Tinbergen Institute Discussion Papers 99-003/4, Tinbergen Institute.

    Cited by:

    1. Lekkos, Ilias & Milas, Costas, 2004. "Time-varying excess returns on UK government bonds: A non-linear approach," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 45-62, January.
    2. Gaul, Jürgen & Theissen, Erik, 2012. "A partially linear approach to modelling the dynamics of spot and futures prices," CFR Working Papers 13-01, University of Cologne, Centre for Financial Research (CFR).
    3. Canto, Bea & Kräussl, Roman, 2007. "Electronic trading systems and intraday non-linear dynamics: An examination of the FTSE 100 cash and futures returns," CFS Working Paper Series 2007/20, Center for Financial Studies (CFS).
    4. Chen, Shiyi & Chng, Michael T. & Liu, Qingfu, 2021. "The implied arbitrage mechanism in financial markets," Journal of Econometrics, Elsevier, vol. 222(1), pages 468-483.
    5. Chelley-Steeley, Patricia & Siganos, Antonios, 2008. "Momentum profits in alternative stock market structures," Journal of Multinational Financial Management, Elsevier, vol. 18(2), pages 131-144, April.
    6. Chelley-Steeley, Patricia L., 2008. "Market quality changes in the London Stock Market," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2248-2253, October.
    7. Angelidis, Timotheos & Andrikopoulos, Andreas, 2010. "Idiosyncratic risk, returns and liquidity in the London Stock Exchange: A spillover approach," International Review of Financial Analysis, Elsevier, vol. 19(3), pages 214-221, June.
    8. Joseph K.W. Fung & Philip Yu, 2007. "Order Imbalance and the Dynamics of Index and Futures Prices," Working Papers 072007, Hong Kong Institute for Monetary Research.
    9. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    10. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    11. Yiuman Tse & Paramita Bandyopadhyay & Yang‐Pin Shen, 2006. "Intraday Price Discovery in the DJIA Index Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1572-1585, November.
    12. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    13. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    14. Wanbing Zhang & Sisi Zhang & Peibiao Zhao, 2019. "On Double Value at Risk," Risks, MDPI, vol. 7(1), pages 1-22, March.
    15. Assaf, Ata, 2006. "The stochastic volatility in mean model and automation: Evidence from TSE," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 241-253, May.
    16. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    17. Tse, Yiuman & Xiang, Ju, 2005. "Market quality and price discovery: Introduction of the E-mini energy futures," Global Finance Journal, Elsevier, vol. 16(2), pages 164-179, December.
    18. Robles-Fernandez M. Dolores & Nieto Luisa & Fernandez M. Angeles, 2004. "Nonlinear Intraday Dynamics in Eurostoxx50 Index Markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-28, December.
    19. Yiu‐Kuen Tse & Wai‐Sum Chan, 2010. "The Lead–Lag Relation Between The S&P500 Spot And Futures Markets: An Intraday‐Data Analysis Using A Threshold Regression Model," The Japanese Economic Review, Japanese Economic Association, vol. 61(1), pages 133-144, March.
    20. Juan A. Lafuente & Manuel Illueca Muñoz, 2003. "The Effect Of Futures Trading Activity On The Distribution Of Spot Market Returns," Working Papers. Serie EC 2003-23, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    21. Garrett Ian & Taylor Nicholas, 2001. "Intraday and Interday Basis Dynamics: Evidence from the FTSE 100 Index Futures Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(2), pages 1-22, July.
    22. Ivan Paya & David A. Peel, 2011. "Systematic sampling of nonlinear models: Evidence on speed of adjustment in index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 192-203, February.
    23. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    24. Charlie X. Cai & Robert Hudson & Kevin Keasey, 2004. "Intra Day Bid‐Ask Spreads, Trading Volume and Volatility: Recent Empirical Evidence from the London Stock Exchange," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 647-676, June.
    25. Stephen Norman, 2009. "Testing for a unit root against ESTAR nonlinearity with a delay parameter greater than one," Economics Bulletin, AccessEcon, vol. 29(3), pages 2152-2173.
    26. Christopher L. Gilbert & Herbert A. Rijken, 2006. "How is Futures Trading Affected by the Move to a Computerized Trading System? Lessons from the LIFFE FTSE 100 Contract," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(7‐8), pages 1267-1297, September.

  8. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. David O. Cushman, 2003. "Further evidence on the size and power of the Bierens and Johansen cointegration procedures," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.

  9. Smith, Jeremy & Taylor, Nick & Yadav, Sanjay, 1995. "Comparing the Bias and Misspecification in ARFIMA Models," Economic Research Papers 268691, University of Warwick - Department of Economics.

    Cited by:

    1. Rea, William & Oxley, Les & Reale, Marco & Brown, Jennifer, 2013. "Not all estimators are born equal: The empirical properties of some estimators of long memory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 29-42.
    2. Enrico Onali & John Goddard, 2014. "Are European equity markets efficient? New evidence from fractal analysis," Papers 1402.1440, arXiv.org.
    3. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," CESifo Working Paper Series 2671, CESifo.
    4. Souza, Leonardo Rocha & Smith, Jeremy & Souza, Reinaldo Castro, 2003. "Convex combinations of long memory estimates from different sampling rates," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 489, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    5. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    6. Giorgio Canarella & Stephen M Miller, 2017. "Inflation Persistence Before and After Inflation Targeting: A Fractional Integration Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 78-103, January.
    7. Leonardo Rocha Souza, 2007. "Temporal Aggregation and Bandwidth selection in estimating long memory," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 701-722, September.
    8. Benjamin J. C. Kim & David Karemera, 2006. "Assessing the forecasting accuracy of alternative nominal exchange rate models: the case of long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(5), pages 369-380.
    9. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    10. Shuping Shi & Jun Yu, 2023. "Volatility Puzzle: Long Memory or Antipersistency," Management Science, INFORMS, vol. 69(7), pages 3861-3883, July.
    11. Marmol, Francesc & Arranz, Miguel A., 1998. "Out-of-sample forecast errors in misspecified perturbed long memory processes," DES - Working Papers. Statistics and Econometrics. WS 10684, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Pérez, Ana & Ruiz Ortega, Esther, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Silva, E.M. & Franco, G.C. & Reisen, V.A. & Cruz, F.R.B., 2006. "Local bootstrap approaches for fractional differential parameter estimation in ARFIMA models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1002-1011, November.
    14. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
    15. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    16. Goddard, John & Onali, Enrico, 2012. "Short and long memory in stock returns data," Economics Letters, Elsevier, vol. 117(1), pages 253-255.
    17. Souza, Leonardo R. & Smith, Jeremy, 2004. "Effects of temporal aggregation on estimates and forecasts of fractionally integrated processes: a Monte-Carlo study," International Journal of Forecasting, Elsevier, vol. 20(3), pages 487-502.
    18. Beran, Jan & Ghosh, Sucharita & Schell, Dieter, 2009. "On least squares estimation for long-memory lattice processes," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2178-2194, November.
    19. Steven Clark & T. Coggin, 2011. "Are U.S. stock prices mean reverting? Some new tests using fractional integration models with overlapping data and structural breaks," Empirical Economics, Springer, vol. 40(2), pages 373-391, April.

Articles

  1. Jing Chen & Nick Taylor & Steve Yang & Qian Han, 2022. "Hawkes processes in finance: market structure and impact," The European Journal of Finance, Taylor & Francis Journals, vol. 28(7), pages 621-626, May.

    Cited by:

    1. Kyungsub Lee, 2024. "Discrete Hawkes process with flexible residual distribution and filtered historical simulation," Papers 2401.13890, arXiv.org.

  2. Taylor, Nick, 2019. "Forecasting returns in the VIX futures market," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1193-1210.

    Cited by:

    1. Hsiu-Chuan Lee & Donald Lien & Her-Jiun Sheu, 2023. "Hedging performance of volatility index futures: a partial cointegration approach," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 265-294, July.
    2. Vera Ivanyuk, 2022. "Methodology for Constructing an Experimental Investment Strategy Formed in Crisis Conditions," Economies, MDPI, vol. 10(12), pages 1-19, December.
    3. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Sivaprasad, Sheeja, 2021. "The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model," International Review of Financial Analysis, Elsevier, vol. 74(C).
    4. Yun‐Huan Lee & Tzu‐Hsiang Liao & Hsiu‐Chuan Lee, 2022. "Overnight returns of industry exchange‐traded funds, investor sentiment, and futures market returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1114-1134, June.
    5. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    6. Yuru Sun & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Gael M. Martin, 2023. "Optimal probabilistic forecasts for risk management," Papers 2303.01651, arXiv.org.
    7. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).

  3. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
    See citations under working paper version above.
  4. Taylor, Nick, 2017. "Realised variance forecasting under Box-Cox transformations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 770-785.

    Cited by:

    1. A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
    2. Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021. "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints 230679, ZBW - Leibniz Information Centre for Economics.
    3. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    4. Xin Du & Kai Moriyama & Kumiko Tanaka-Ishii, 2023. "Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation," Papers 2310.14536, arXiv.org.
    5. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    6. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    7. Deev, Oleg & Plíhal, Tomáš, 2022. "How to calm down the markets? The effects of COVID-19 economic policy responses on financial market uncertainty," Research in International Business and Finance, Elsevier, vol. 60(C).

  5. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    See citations under working paper version above.
  6. Nick Taylor, 2017. "Risk Control: Who Cares?," European Financial Management, European Financial Management Association, vol. 23(1), pages 153-179, January.

    Cited by:

    1. Nick Taylor, 2023. "The Determinants of Volatility Timing Performance," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1228-1257.

  7. Adrian R. Bell & Chris Brooks & Nick Taylor, 2016. "Time-varying price discovery in the eighteenth century: empirical evidence from the London and Amsterdam stock markets," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 10(1), pages 5-30, january.

    Cited by:

    1. Hou, Yang & Nartea, Gilbert, 2017. "Price Discovery in the Stock Index Futures Market: Evidence from the Chinese stock market crash," MPRA Paper 81995, University Library of Munich, Germany.
    2. Hou, Yang & Li, Steven, 2017. "Time-Varying Price Discovery and Autoregressive Loading Factors: Evidence from S&P 500 Cash and E-Mini Futures Markets," MPRA Paper 81999, University Library of Munich, Germany.
    3. Yang Hu & Yang (Greg) Hou & Les Oxley, 2019. "Spot and Futures Prices of Bitcoin: Causality, Cointegration and Price Discovery from a Time-Varying Perspective," Working Papers in Economics 19/13, University of Waikato.
    4. Hu, Yang & Hou, Yang Greg & Oxley, Les, 2020. "What role do futures markets play in Bitcoin pricing? Causality, cointegration and price discovery from a time-varying perspective?," International Review of Financial Analysis, Elsevier, vol. 72(C).

  8. Nicholas Taylor, 2015. "Realized volatility forecasting in an international context," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 503-509, April.

    Cited by:

    1. Hwang, Eunju & Hong, Won-Tak, 2021. "A multivariate HAR-RV model with heteroscedastic errors and its WLS estimation," Economics Letters, Elsevier, vol. 203(C).
    2. Won-Tak Hong & Jiwon Lee & Eunju Hwang, 2020. "A Note on the Asymptotic Normality Theory of the Least Squares Estimates in Multivariate HAR-RV Models," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    3. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.

  9. Leung, W.S. & Taylor, N. & Evans, K.P., 2015. "The determinants of bank risks: Evidence from the recent financial crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 277-293.

    Cited by:

    1. Raouf, Hajar & Ahmed, Habib, 2022. "Risk governance and financial stability: A comparative study of conventional and Islamic banks in the GCC," Global Finance Journal, Elsevier, vol. 52(C).
    2. Saibal Ghosh, 2023. "Stability versus soundness: what matters for women central bank governors?," Economic Change and Restructuring, Springer, vol. 56(4), pages 2315-2338, August.
    3. Hussien Mohsen Ahmed & Sherif Ismail El-Halaby & Hebatallah Ahmed Soliman, 2022. "The consequence of the credit risk on the financial performance in light of COVID-19: Evidence from Islamic versus conventional banks across MEA region," Future Business Journal, Springer, vol. 8(1), pages 1-22, December.
    4. Daniela Venanzi, 2019. "Da che dipende il rischio delle banche? Il beta fondamentale delle banche europee (What does banks' riskiness depend on? The fundamental beta of Europe's banks)," Moneta e Credito, Economia civile, vol. 72(286), pages 105-131.
    5. Solomon Y. Deku & Alper Kara & Nodirbek Karimov, 2021. "Do investors value frequent issuers in securitization?," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1247-1282, November.
    6. Wu, Meng-Wen & Shen, Chung Hua, 2019. "Effects of shadow banking on bank risks from the view of capital adequacy," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 176-197.
    7. Pilar Gómez-Fernández-Aguado & Purificación Parrado-Martínez & Antonio Partal-Ureña, 2018. "Risk Profile Indicators and Spanish Banks’ Probability of Default from a Regulatory Approach," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
    8. Parrado-Martínez, Purificación & Gómez-Fernández-Aguado, Pilar & Partal-Ureña, Antonio, 2019. "Factors influencing the European bank’s probability of default: An application of SYMBOL methodology," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 223-240.
    9. Davide Salvatore Mare & Dieter Gramlich, 2021. "Risk exposures of European cooperative banks: a comparative analysis," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 1-23, January.
    10. Cicchiello, Antonella Francesca & Cotugno, Matteo & Perdichizzi, Salvatore & Torluccio, Giuseppe, 2022. "Do capital buffers matter? Evidence from the stocks and flows of nonperforming loans," International Review of Financial Analysis, Elsevier, vol. 84(C).
    11. Samaresh Bardhan & Rajesh Sharma & Vivekananda Mukherjee, 2019. "Threshold Effect of Bank-specific Determinants of Non-performing Assets: An Application in Indian Banking," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(1_suppl), pages 1-34, April.
    12. CNV Krishnan & Yu He, 2022. "Investor Perception, Market Reaction, and Post-Issue Performance in Bank Seasoned Equity Offerings," JRFM, MDPI, vol. 15(7), pages 1-21, June.
    13. Roshanthi Dias, 2021. "Capital regulation and bank risk‐taking – new global evidence," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 847-884, March.

  10. Nicholas Taylor, 2014. "The Economic Value of Volatility Forecasts: A Conditional Approach," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 433-478.

    Cited by:

    1. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    2. Márcio Gomes Pinto Garcia & Marcelo Cunha Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "Economic gains of realized volatility in the Brazilian stock market," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(3), pages 319-349.
    3. Nick Taylor, 2023. "The Determinants of Volatility Timing Performance," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1228-1257.
    4. Degiannakis, Stavros & Filis, George, 2019. "Oil price volatility forecasts: What do investors need to know?," MPRA Paper 94445, University Library of Munich, Germany.
    5. Taylor, Nick, 2017. "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, vol. 66(C), pages 480-492.
    6. Nick Taylor, 2017. "Risk Control: Who Cares?," European Financial Management, European Financial Management Association, vol. 23(1), pages 153-179, January.

  11. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.

    Cited by:

    1. Fuess, Roland & Grabellus, Markus & Mager, Ferdinand & Stein, Michael, 2015. "Something in the Air: Information Density, News Surprises, and Price Jumps," Working Papers on Finance 1517, University of St. Gallen, School of Finance.
    2. Ivan Indriawan & Feng Jiao & Yiuman Tse, 2019. "The impact of the US stock market opening on price discovery of government bond futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 779-802, July.
    3. Wu, Ming & Ohk, Ki Yool, 2023. "Who benefits more? Shanghai-Hong Kong stock Connect—“Through Train”," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 409-427.
    4. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    5. Glenn Kit Foong Ho & Sirimon Treepongkaruna & Marvin Wee & Chaiyuth Padungsaksawasdi, 2022. "The effect of short selling on volatility and jumps," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 34-52, February.
    6. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
    7. Kim, Jae H. & Ji, Philip Inyeob, 2015. "Significance testing in empirical finance: A critical review and assessment," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 1-14.
    8. Rodrigo Herrera & Adam Clements, 2020. "A marked point process model for intraday financial returns: modeling extreme risk," Empirical Economics, Springer, vol. 58(4), pages 1575-1601, April.
    9. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112919, Verein für Socialpolitik / German Economic Association.
    10. Firouzi, Shahrokh & Wang, Xiangning, 2021. "The interrelationship between order flow, exchange rate, and the role of American economic news," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. Dion Bongaerts & Richard Roll & Dominik Rösch & Mathijs van Dijk & Darya Yuferova, 2022. "How Do Shocks Arise and Spread Across Stock Markets? A Microstructure Perspective," Management Science, INFORMS, vol. 68(4), pages 3071-3089, April.
    12. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.
    13. van der Wel, M., 2020. "Connecting Silos : On linking macroeconomics and finance, and the role of econometrics therein," ERIM Inaugural Address Series Research in Management 124748, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam..
    14. Hoang, Lai T. & Baur, Dirk G., 2022. "Loaded for bear: Bitcoin private wallets, exchange reserves and prices," Journal of Banking & Finance, Elsevier, vol. 144(C).

  12. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.

    Cited by:

    1. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    2. Noureddine Kouaissah & Amin Hocine, 2021. "Forecasting systemic risk in portfolio selection: The role of technical trading rules," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 708-729, July.
    3. Benjamin R. Auer, 2021. "Have trend-following signals in commodity futures markets become less reliable in recent years?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 533-553, December.
    4. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    5. Cristiana Tudor & Andrei Anghel, 2021. "The Financialization of Crude Oil Markets and Its Impact on Market Efficiency: Evidence from the Predictive Ability and Performance of Technical Trading Strategies," Energies, MDPI, vol. 14(15), pages 1-19, July.
    6. Hong, KiHoon & Wu, Eliza, 2016. "The roles of past returns and firm fundamentals in driving US stock price movements," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 62-75.
    7. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.
    8. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.
    9. Smita Roy Trivedi, 2022. "Technical analysis using Heiken Ashi Stochastic: To catch a trend, use a HASTOC," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1836-1847, April.
    10. Adrian Zoicas‐Ienciu, 2021. "Evaluating active investing with generic trading reactions," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1018-1036, January.
    11. Shi, Huai-Long & Zhou, Wei-Xing, 2017. "Wax and wane of the cross-sectional momentum and contrarian effects: Evidence from the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 397-407.
    12. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    13. Rebecca Westphal & Didier Sornette, 2019. "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series 19-29, Swiss Finance Institute.
    14. Georgios Sermpinis & Arman Hassanniakalager & Charalampos Stasinakis & Ioannis Psaradellis, 2018. "Technical Analysis and Discrete False Discovery Rate: Evidence from MSCI Indices," Papers 1811.06766, arXiv.org, revised Jun 2019.
    15. KiHoon Jimmy Hong & Eliza Wu, 2014. "Can Momentum Factors Be Used to Enhance Accounting Information based Fundamental Analysis in Explaining Stock Price Movements?," Research Paper Series 346, Quantitative Finance Research Centre, University of Technology, Sydney.
    16. Chiarella, Carl & Ladley, Daniel, 2016. "Chasing trends at the micro-level: The effect of technical trading on order book dynamics," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 119-131.
    17. Anghel, Dan Gabriel, 2021. "Data Snooping Bias in Tests of the Relative Performance of Multiple Forecasting Models," Journal of Banking & Finance, Elsevier, vol. 126(C).
    18. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    19. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    20. Martín García, Rodrigo & Ventura Pérez, Enrique & Arguedas Sanz, Raquel, 2020. "Temporal optimisation of signals emitted automatically by securities exchange indicators," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).
    21. Jin, Xiaoye, 2022. "Testing technical trading strategies on China's equity ETFs: A skewness perspective," Emerging Markets Review, Elsevier, vol. 51(PA).
    22. L. Lin & M. Schatz & D. Sornette, 2019. "A simple mechanism for financial bubbles: time-varying momentum horizon," Quantitative Finance, Taylor & Francis Journals, vol. 19(6), pages 937-959, June.
    23. Westphal, Rebecca & Sornette, Didier, 2020. "Market impact and performance of arbitrageurs of financial bubbles in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 1-23.
    24. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    25. Chen, Chien-Hua & Su, Xuan-Qi & Lin, Jun-Biao, 2016. "The role of information uncertainty in moving-average technical analysis: A study of individual stock-option issuance in Taiwan," Finance Research Letters, Elsevier, vol. 18(C), pages 263-272.
    26. Ryan Flugum, 2021. "The trend is an analyst's friend: Analyst recommendations and market technicals," The Financial Review, Eastern Finance Association, vol. 56(2), pages 301-330, May.
    27. Ivanovski, Zoran & Ivanovska, Nadica & Narasanov, Zoran, 2017. "Technical Analysis Accuracy At Macedonian Stock Exchange," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 8(2), pages 105-118.
    28. Mingwei Sun & Paskalis Glabadanidis, 2022. "Can technical indicators predict the Chinese equity risk premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 114-142, March.
    29. Taylor, Nick, 2017. "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, vol. 66(C), pages 480-492.
    30. Ali Fayyaz Munir & Mohd Edil Abd. Sukor & Shahrin Saaid Shaharuddin, 2022. "Adaptive Market Hypothesis and Time-varying Contrarian Effect: Evidence From Emerging Stock Markets of South Asia," SAGE Open, , vol. 12(1), pages 21582440211, January.
    31. Jying‐Nan Wang & Hung‐Chun Liu & Jiangze Du & Yuan‐Teng Hsu, 2019. "Economic benefits of technical analysis in portfolio management: Evidence from global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 890-902, April.
    32. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
    33. Phooi M’ng, Jacinta Chan, 2018. "Dynamically Adjustable Moving Average (AMA’) technical analysis indicator to forecast Asian Tigers’ futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 336-345.
    34. Lee, Yung-Tsung & Kung, Ko-Lun & Liu, I-Chien, 2018. "Profitability and risk profile of reverse mortgages: A cross-system and cross-plan comparison," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 255-266.
    35. Li Lin & Didier Sornette, 2016. "A Simple Mechanism for Financial Bubbles: Time-Varying Momentum Horizon," Swiss Finance Institute Research Paper Series 16-61, Swiss Finance Institute.

  13. Nicholas Taylor, 2014. "Economic forecast quality: information timeliness and data vintage effects," Empirical Economics, Springer, vol. 46(1), pages 145-174, February.

    Cited by:

    1. Oestmann Marco & Bennöhr Lars, 2015. "Determinants of house price dynamics. What can we learn from search engine data?," Review of Economics, De Gruyter, vol. 66(1), pages 99-127, April.
    2. Yang, Ann Shawing, 2020. "Misinformation corrections of corporate news: Corporate clarification announcements," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).

  14. Nicholas Taylor, 2012. "The Economic Significance Of Conditioning Information On Portfolio Efficiency In The Presence Of Costly Short‐Selling," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 35(1), pages 115-135, March.

    Cited by:

    1. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    2. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.

  15. Taylor, Nicholas, 2012. "Measuring the economic value of loan advice," Economics Letters, Elsevier, vol. 117(3), pages 615-618.

    Cited by:

    1. Parnes, Dror, 2015. "Determining the economic value of ambiguous loan portfolios," Finance Research Letters, Elsevier, vol. 13(C), pages 148-154.

  16. Svetlana Mira & Nicholas Taylor, 2011. "Estimating private information usage amongst analysts: evidence from UK earnings forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 679-705, December.

    Cited by:

    1. Young‐Soo Choi & Svetlana Mira & Nicholas Taylor, 2022. "Local versus foreign analysts' forecast accuracy: does herding matter?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1143-1188, April.
    2. Matthias Demmer & Paul Pronobis & Teri Lombardi Yohn, 2019. "Mandatory IFRS adoption and analyst forecast accuracy: the role of financial statement-based forecasts and analyst characteristics," Review of Accounting Studies, Springer, vol. 24(3), pages 1022-1065, September.

  17. Nicholas Taylor, 2011. "Forecast accuracy and effort: The case of US inflation rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 644-665, November.

    Cited by:

    1. Pramesti Getut, 2023. "Parameter least-squares estimation for time-inhomogeneous Ornstein–Uhlenbeck process," Monte Carlo Methods and Applications, De Gruyter, vol. 29(1), pages 1-32, March.
    2. Chang Liu & Raja Nassar & Min Guo, 2015. "A Method of Retail Mortgage Stress Testing: Based on Time‐Frame and Magnitude Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(4), pages 261-274, July.

  18. Nicholas Taylor, 2010. "The Determinants of Future U.S. Monetary Policy: High-Frequency Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2-3), pages 399-420, March.

    Cited by:

    1. James D. Hamilton & Seth Pruitt & Scott Borger, 2010. "Estimating the Market-Perceived Monetary Policy Rule," NBER Working Papers 16412, National Bureau of Economic Research, Inc.
    2. Michael D. Bauer, 2014. "Inflation Expectations and the News," Working Paper Series 2014-9, Federal Reserve Bank of San Francisco.
    3. Moura, Marcelo L. & Gaião, Rafael Ladeira, 2012. "Impact of macroeconomic surprises on the brazilian yield curve and expected inflation," Insper Working Papers wpe_288, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    4. Lapp, John S. & Pearce, Douglas K., 2012. "The impact of economic news on expected changes in monetary policy," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 362-379.
    5. Dunbar, Kwamie & Amin, Abu S., 2015. "The nature and impact of the market forecasting errors in the Federal funds futures market," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 174-192.
    6. Vijay A Murik, 2013. "Measuring monetary policy expectations," Australian Journal of Management, Australian School of Business, vol. 38(1), pages 49-65, April.
    7. Stotz, Olaf, 2018. "A labor news hedge portfolio and the cross-section of expected stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 123-139.
    8. Dick van Dijk & Robin L. Lumsdaine & Michel van der Wel, 2014. "Market Set-Up in Advance of Federal Reserve Policy Decisions," NBER Working Papers 19814, National Bureau of Economic Research, Inc.
    9. Barakchian, S. Mahdi & Crowe, Christopher, 2013. "Monetary policy matters: Evidence from new shocks data," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 950-966.

  19. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.

    Cited by:

    1. Alexander, Carol & Rauch, Johannes, 2021. "A general property for time aggregation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 536-548.
    2. Ghosh, Indranil & Chaudhuri, Tamal Datta & Alfaro-Cortés, Esteban & Gámez, Matías & García, Noelia, 2022. "A hybrid approach to forecasting futures prices with simultaneous consideration of optimality in ensemble feature selection and advanced artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 181(C).

  20. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.

    Cited by:

    1. Sami Gharbi & Jean-Michel Sahut & Frédéric Teulon, 2014. "R&D investments and high-tech firms' stock return volatility," Working Papers 2014-218, Department of Research, Ipag Business School.
    2. Liu, Min & Taylor, James W. & Choo, Wei-Chong, 2020. "Further empirical evidence on the forecasting of volatility with smooth transition exponential smoothing," Economic Modelling, Elsevier, vol. 93(C), pages 651-659.
    3. Hamim, Md. Tanvir, 2020. "R&D Investments and Idiosyncratic Volatility," MPRA Paper 101330, University Library of Munich, Germany.

  21. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    See citations under working paper version above.
  22. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.

    Cited by:

    1. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series 015, University of Pavia, Department of Economics and Management.
    2. Entrop, Oliver & Scholz, Hendrik & Wilkens, Marco, 2009. "The price-setting behavior of banks: An analysis of open-end leverage certificates on the German market," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 874-882, May.
    3. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    4. Chen, Chun-Hung & Yu, Wei-Choun & Zivot, Eric, 2012. "Predicting stock volatility using after-hours information: Evidence from the NASDAQ actively traded stocks," International Journal of Forecasting, Elsevier, vol. 28(2), pages 366-383.
    5. Christophe Perignon & D. Smith, 2009. "The Level and Quality of Value-at-Risk Disclosure by Commercial Banks," Post-Print hal-00496102, HAL.
    6. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    7. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    8. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    9. Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017. "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, vol. 61(C), pages 12-26.
    10. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    11. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    12. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    13. Donggyu Kim & Minseok Shin & Yazhen Wang, 2021. "Overnight GARCH-It\^o Volatility Models," Papers 2102.13467, arXiv.org, revised Jun 2022.
    14. Gaurav Raizada & Vartika Srivastava & S. V. D. Nageswara Rao, 2020. "Shall One Sit “Longer” for a Free Lunch? Impact of Trading Durations on the Realized Variances and Volatility Spillovers," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 1-28, March.
    15. Dohyun Chun & Donggyu Kim, 2022. "State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 105-124, January.
    16. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.
    17. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    18. D Wu & D L Olson, 2010. "Enterprise risk management: coping with model risk in a large bank," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 179-190, February.
    19. Tsiakas, Ilias, 2008. "Overnight information and stochastic volatility: A study of European and US stock exchanges," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 251-268, February.
    20. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
    21. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2020. "Sequential forecasting of downside extreme risk during overnight and daytime: Evidence from the Chinese Stock Market☆," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    22. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    23. Shen, Lihua & Lu, Xinjie & Luu Duc Huynh, Toan & Liang, Chao, 2023. "Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 224-239.
    24. Fang Liang & Lingshan Du & Zhuo Huang, 2023. "Option pricing with overnight and intraday volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1576-1614, November.
    25. Liu, Qingfu & An, Yunbi, 2014. "Risk contributions of trading and non-trading hours: Evidence from Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 17-29.
    26. Todorova, Neda & Souček, Michael, 2014. "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, vol. 11(4), pages 420-428.

  23. Nicholas Taylor, 2004. "Modeling discontinuous periodic conditional volatility: Evidence from the commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(9), pages 805-834, September.

    Cited by:

    1. Abdelhakim Aknouche & Eid Al-Eid, 2012. "Asymptotic inference of unstable periodic ARCH processes," Statistical Inference for Stochastic Processes, Springer, vol. 15(1), pages 61-79, April.
    2. Xu, Kewei & Xiong, Xiong & Li, Xiao, 2021. "The maturity effect of stock index futures: Speculation or carry arbitrage?," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Sobhesh Kumar Agarwalla & Ajay Pandey, 2013. "Expiration‐Day Effects and the Impact of Short Trading Breaks on Intraday Volatility: Evidence from the Indian Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(11), pages 1046-1070, November.
    4. B.B. Chakrabarti & Vivek Rajvanshi, 2017. "Intraday Periodicity and Volatility Forecasting: Evidence from Indian Crude Oil Futures Market," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 16(1), pages 1-28, April.
    5. Agarwalla, Sobhesh Kumar & Pandey, Ajay, 2012. "Whether Cross-Listing, Stock-specific and Market-wide Calendar Events impact Intraday Volatility Dynamics? Evidence from the Indian Stock Market using High-frequency Data," IIMA Working Papers WP2012-11-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    6. Aknouche, Abdelhakim & Al-Eid, Eid & Demouche, Nacer, 2016. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," MPRA Paper 75770, University Library of Munich, Germany, revised 19 Dec 2016.
    7. Abdelhakim Aknouche & Abdelouahab Bibi, 2009. "Quasi‐maximum likelihood estimation of periodic GARCH and periodic ARMA‐GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 19-46, January.
    8. Abdelhakim Aknouche & Eid Al-Eid & Nacer Demouche, 2018. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 485-511, October.

  24. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.

    Cited by:

    1. Evans, Kevin P. & Speight, Alan E.H., 2010. "Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility," Research in International Business and Finance, Elsevier, vol. 24(1), pages 82-101, January.
    2. Ray Chou & Chun-Chou Wu & Nathan Liu, 2009. "Forecasting time-varying covariance with a range-based dynamic conditional correlation model," Review of Quantitative Finance and Accounting, Springer, vol. 33(4), pages 327-345, November.
    3. Evans, Kevin & Speight, Alan, 2010. "International macroeconomic announcements and intraday euro exchange rate volatility," Journal of the Japanese and International Economies, Elsevier, vol. 24(4), pages 552-568, December.
    4. Bowe, Michael & Hyde, Stuart & McFarlane, Lavern, 2013. "Duration, trading volume and the price impact of trades in an emerging futures market," Emerging Markets Review, Elsevier, vol. 17(C), pages 89-105.
    5. Lin, William T. & Tsai, Shih-Chuan & Chiu, Peter, 2016. "Do foreign institutions outperform in the Taiwan options market?," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 101-115.
    6. Sobhesh Kumar Agarwalla & Ajay Pandey, 2013. "Expiration‐Day Effects and the Impact of Short Trading Breaks on Intraday Volatility: Evidence from the Indian Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(11), pages 1046-1070, November.
    7. B.B. Chakrabarti & Vivek Rajvanshi, 2017. "Intraday Periodicity and Volatility Forecasting: Evidence from Indian Crude Oil Futures Market," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 16(1), pages 1-28, April.
    8. Evans, Kevin P. & Speight, Alan E.H., 2010. "Dynamic news effects in high frequency Euro exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 238-258, July.
    9. McMillan, David G. & Speight, Alan E.H. & Evans, Kevin P., 2008. "How useful is intraday data for evaluating daily Value-at-Risk?: Evidence from three Euro rates," Journal of Multinational Financial Management, Elsevier, vol. 18(5), pages 488-503, December.
    10. Agarwalla, Sobhesh Kumar & Pandey, Ajay, 2012. "Whether Cross-Listing, Stock-specific and Market-wide Calendar Events impact Intraday Volatility Dynamics? Evidence from the Indian Stock Market using High-frequency Data," IIMA Working Papers WP2012-11-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    11. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    12. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.

  25. Michael P. Clements & Nick Taylor, 2003. "Evaluating interval forecasts of high-frequency financial data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 445-456.

    Cited by:

    1. Buansing, T.S. Tuang & Golan, Amos & Ullah, Aman, 2020. "An information-theoretic approach for forecasting interval-valued SP500 daily returns," International Journal of Forecasting, Elsevier, vol. 36(3), pages 800-813.
    2. Elena-Ivona DUMITRESCU & Christophe HURLIN & Jaouad MADKOUR, 2011. "Testing Interval Forecasts: A New GMM-based Test," LEO Working Papers / DR LEO 1549, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    3. Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
    4. Yushu Li & Jonas Andersson, 2020. "A likelihood ratio and Markov chain‐based method to evaluate density forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 47-55, January.
    5. Mauricio Lopera & Ramón Javier Mesa & Charle Londoño, 2014. "Evaluando las intervenciones cambiarias en Colombia: 2004-2012," Estudios Gerenciales, Universidad Icesi, March.
    6. Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    7. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    8. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    9. Katarzyna Maciejowska & Jakub Nowotarski & Rafal Weron, 2014. "Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging," HSC Research Reports HSC/14/09, Hugo Steinhaus Center, Wroclaw University of Technology.
    10. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 115-132.
    11. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
    12. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    13. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
    14. Storti, G., 2006. "Minimum distance estimation of GARCH(1,1) models," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1803-1821, December.
    15. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
    16. Tsyplakov, Alexander, 2011. "Evaluating density forecasts: a comment," MPRA Paper 31184, University Library of Munich, Germany.
    17. Carol Alexander & Emese Lazar & Silvia Stanescu, 2011. "Analytic Approximations to GARCH Aggregated Returns Distributions with Applications to VaR and ETL," ICMA Centre Discussion Papers in Finance icma-dp2011-08, Henley Business School, University of Reading.
    18. Dominique, C-Rene, 2013. "Estimating investors' behavior and errors in probabilistic forecasts by the Kolmogorov entropy and noise colors of non-hyperbolic attractors," MPRA Paper 46451, University Library of Munich, Germany.
    19. Tao Hong & Katarzyna Maciejowska & Jakub Nowotarski & Rafal Weron, 2014. "Probabilistic load forecasting via Quantile Regression Averaging of independent expert forecasts," HSC Research Reports HSC/14/10, Hugo Steinhaus Center, Wroclaw University of Technology.
    20. Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Norwegian School of Economics, Department of Business and Management Science.
    21. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    22. Jakub Nowotarski & Rafal Weron, 2013. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," HSC Research Reports HSC/13/12, Hugo Steinhaus Center, Wroclaw University of Technology.
    23. Elena Ivona Dumitrescu & Christophe Hurlin & Jaouad Madkour, 2013. "Testing Interval Forecasts: a GMM-Based Approach," Post-Print hal-01385898, HAL.
    24. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    25. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    26. Sayar Karmakar & Marek Chudy & Wei Biao Wu, 2020. "Long-term prediction intervals with many covariates," Papers 2012.08223, arXiv.org, revised Sep 2021.
    27. Helmut Herwartz & Israel Waichman, 2010. "A comparison of bootstrap and Monte-Carlo testing approaches to value-at-risk diagnosis," Computational Statistics, Springer, vol. 25(4), pages 725-732, December.

  26. Nicholas Taylor, 2002. "Competition on the London Stock Exchange," European Financial Management, European Financial Management Association, vol. 8(4), pages 399-419, December.

    Cited by:

    1. Galariotis, Emilios C. & Krokida, Styliani-Iris & Spyrou, Spyros I., 2016. "Herd behavior and equity market liquidity: Evidence from major markets," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 140-149.
    2. Patricia Chelley‐Steeley, 2005. "Noise and the Trading Mechanism: the Case of SETS," European Financial Management, European Financial Management Association, vol. 11(3), pages 387-424, June.
    3. Kasch-Haroutounian, Maria & Theissen, Erik, 2006. "Competition between exchanges: Euronext versus Xetra," CFS Working Paper Series 2007/19, Center for Financial Studies (CFS).
    4. Ariadna Dumitrescu, 2010. "Liquidity and Optimal Market Transparency," European Financial Management, European Financial Management Association, vol. 16(4), pages 599-623, September.
    5. Tóth, Bence & Palit, Imon & Lillo, Fabrizio & Farmer, J. Doyne, 2015. "Why is equity order flow so persistent?," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 218-239.
    6. David C. Porter & Carsten Tanggaard & Daniel G. Weaver & Wei Yu, 2008. "Dispersed Trading and the Prevention of Market Failure: the Case of the Copenhagen Stock Exchange," European Financial Management, European Financial Management Association, vol. 14(2), pages 243-267, March.
    7. Pineda, Julián & Cortés, Lina M. & Perote, Javier, 2022. "Financial contagion drivers during recent global crises," Economic Modelling, Elsevier, vol. 117(C).

  27. Taylor, Nicholas, 2002. "The economic and statistical significance of spread forecasts: Evidence from the London Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 26(4), pages 795-818, April.

    Cited by:

    1. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    2. Narayan, Paresh Kumar & Mishra, Sagarika & Narayan, Seema, 2014. "Spread determinants and the day-of-the-week effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 51-60.
    3. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  28. Norman Strong & Nicholas Taylor, 2001. "Time Diversification: Empirical Tests," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(3‐4), pages 263-302, April.

    Cited by:

    1. Ibarra, Raul, 2013. "A spatial dominance approach to evaluate the performance of stocks and bonds: Does the investment horizon matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(4), pages 429-439.
    2. Loh, Lixia, 2013. "Co-movement of Asia-Pacific with European and US stock market returns: A cross-time-frequency analysis," Research in International Business and Finance, Elsevier, vol. 29(C), pages 1-13.
    3. Summers, Barbara & Duxbury, Darren & Hudson, Robert & Keasey, Kevin, 2006. "As time goes by: An investigation of how asset allocation varies with investor age," Economics Letters, Elsevier, vol. 91(2), pages 210-214, May.
    4. Ken Johnston & John Hatem & Elton Scott, 2013. "A note on the evaluation of long-run investment decisions using the sharpe ratio," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(1), pages 150-157, January.
    5. Erkan Kalayci & Ulkem Basdas, 2010. "Does the prospect theory also hold for power traders? Empirical evidence from a Swiss energy company," Review of Financial Economics, John Wiley & Sons, vol. 19(1), pages 38-45, January.
    6. Kalayci, Erkan & Basdas, Ulkem, 2010. "Does the prospect theory also hold for power traders? Empirical evidence from a Swiss energy company," Review of Financial Economics, Elsevier, vol. 19(1), pages 38-45, January.
    7. Lakshman Alles & Louis Murray, 2009. "Investment performance and holding periods: An investigation of the major UK asset classes," Journal of Asset Management, Palgrave Macmillan, vol. 10(5), pages 280-292, December.

  29. Clements, Michael P & Taylor, Nick, 2001. "Robust Evaluation of Fixed-Event Forecast Rationality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(4), pages 285-295, July.

    Cited by:

    1. Goodwin, Thomas & Tian, Jing, 2017. "A state space approach to evaluate multi-horizon forecasts," Working Papers 2017-15, University of Tasmania, Tasmanian School of Business and Economics.
    2. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    3. Ullrich Heilemann & Karsten Müller, 2018. "Wenig Unterschiede – Zur Treffsicherheit Internationaler Prognosen und Prognostiker [Few differences—on the accuracy of international forecasts and forecaster]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 195-233, December.
    4. Tian, Jing & Goodwin, Thomas, 2018. "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers 2018-04, University of Tasmania, Tasmanian School of Business and Economics.
    5. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    6. Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Robust tests of predictive accuracy," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 161-184.
    7. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

  30. Garrett Ian & Taylor Nicholas, 2001. "Intraday and Interday Basis Dynamics: Evidence from the FTSE 100 Index Futures Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(2), pages 1-22, July.

    Cited by:

    1. Canto, Bea & Kräussl, Roman, 2007. "Electronic trading systems and intraday non-linear dynamics: An examination of the FTSE 100 cash and futures returns," CFS Working Paper Series 2007/20, Center for Financial Studies (CFS).
    2. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    3. Michael Graham & Jarno Kiviaho & Jussi Nikkinen, 2013. "Short-term and long-term dependencies of the S&P 500 index and commodity prices," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 583-592, March.
    4. Vipul, 2008. "Mispricing, Volume, Volatility and Open Interest," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 7(3), pages 263-292, December.
    5. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.

  31. Clements, Michael P. & Taylor, Nick, 2001. "Bootstrapping prediction intervals for autoregressive models," International Journal of Forecasting, Elsevier, vol. 17(2), pages 247-267.

    Cited by:

    1. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
    2. Borbély, Dóra & Meier, Carsten-Patrick, 2003. "Macroeconomic interval forecasting: the case of assessing the risk of deflation in Germany," Kiel Working Papers 1153, Kiel Institute for the World Economy (IfW Kiel).
    3. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    4. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    5. Schumacher, Christian, 2002. "Forecasting Trend Output in the Euro Area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(8), pages 543-558, December.
    6. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
    7. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    8. Merten, Michael & Rücker, Fabian & Schoeneberger, Ilka & Sauer, Dirk Uwe, 2020. "Automatic frequency restoration reserve market prediction: Methodology and comparison of various approaches," Applied Energy, Elsevier, vol. 268(C).
    9. Marcellino, Massimiliano & Knüppel, Malte & Jordà , Òscar, 2010. "Empirical Simultaneous Confidence Regions for Path-Forecasts," CEPR Discussion Papers 7797, C.E.P.R. Discussion Papers.
    10. Felix Wick & Ulrich Kerzel & Martin Hahn & Moritz Wolf & Trapti Singhal & Daniel Stemmer & Jakob Ernst & Michael Feindt, 2021. "Demand Forecasting of Individual Probability Density Functions with Machine Learning," SN Operations Research Forum, Springer, vol. 2(3), pages 1-39, September.
    11. Chan, W.S & Cheung, S.H & Wu, K.H, 2004. "Multiple forecasts with autoregressive time series models: case studies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 421-430.
    12. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.
    14. Benner, Joachim & Borbély, Dóra & Boss, Alfred & Kamps, Annette & Meier, Carsten-Patrick & Oskamp, Frank & Scheide, Joachim & Schmidt, Rainer, 2003. "Deutschland: Stagnation hält vorerst an," Open Access Publications from Kiel Institute for the World Economy 2984, Kiel Institute for the World Economy (IfW Kiel).
    15. Ahmed, Wajid Shakeel & Sheikh, Jibran & Ur-Rehman, Kashif & Shafi, khuram & Shad, Shafqat Ali & Butt, Faisal Shafique, 2020. "New continuum of stochastic static forecasting model for mutual funds at investment policy level," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    16. Alonso Fernández, Andrés Modesto & Bastos, Guadalupe & García-Martos, Carolina, 2017. "BIAS correction for dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 24029, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    18. Sylvain Robbiano & Matthieu Saumard & Michel Curé, 2016. "Improving prediction performance of stellar parameters using functional models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(8), pages 1465-1476, June.
    19. Reeves, Jonathan J., 2005. "Bootstrap prediction intervals for ARCH models," International Journal of Forecasting, Elsevier, vol. 21(2), pages 237-248.
    20. Meier, Carsten-Patrick, 2004. "Investigating the impact of an appreciation of the euro in a small macroeconometric model of Germany and the euro area," Kiel Working Papers 1204, Kiel Institute for the World Economy (IfW Kiel).
    21. Dag Kolsrud, 2015. "A Time‐Simultaneous Prediction Box for a Multivariate Time Series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 675-693, December.
    22. Galvao, Ana Beatriz & Costa, Sonia, 2013. "Does the euro area forward rate provide accurate forecasts of the short rate?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 131-141.
    23. Michael Wolf & Dan Wunderli, 2012. "Bootstrap joint prediction regions," ECON - Working Papers 064, Department of Economics - University of Zurich, revised May 2013.
    24. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    25. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute.
    26. Òscar Jordà & Malte Knuppel & Massimiliano Marcellino, 2012. "Empirical simultaneous prediction regions for path-forecasts," Working Paper Series 2012-05, Federal Reserve Bank of San Francisco.
    27. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    28. Jae H. Kim, 2004. "Bias-corrected bootstrap prediction regions for vector autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 141-154.
    29. Anna Staszewska‐Bystrova, 2011. "Bootstrap prediction bands for forecast paths from vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(8), pages 721-735, December.
    30. Anna Staszewska-Bystrova, 2009. "Bootstrap Confidence Bands for Forecast Paths," Working Papers 024, COMISEF.
    31. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    32. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
    33. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    34. Valentina Corradi & Norman R. Swanson, 2003. "A Test for Comparing Multiple Misspecified Conditional Distributions," Departmental Working Papers 200314, Rutgers University, Department of Economics.
    35. Kim, Jae H., 2004. "Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators," International Journal of Forecasting, Elsevier, vol. 20(1), pages 85-97.
    36. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    37. Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.
    38. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.
    39. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    40. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    41. Anna Staszewska-Bystrova & Peter Winker, 2016. "Improved bootstrap prediction intervals for SETAR models," Statistical Papers, Springer, vol. 57(1), pages 89-98, March.
    42. Dag Kolsrud, 2007. "Time-simultaneous prediction band for a time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 171-188.

  32. Ian Garrett & Nick Taylor, 2001. "Portfolio diversification and excess comovement in commodity prices," Manchester School, University of Manchester, vol. 69(4), pages 351-368, September.

    Cited by:

    1. Bolong Cao & Shamila Jayasuriya & William Shambora, 2010. "Holding a commodity futures index fund in a globally diversified portfolio: A placebo effect?," Economics Bulletin, AccessEcon, vol. 30(3), pages 1842-1851.
    2. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.

  33. Taylor, Nick & Dijk, Dick van & Franses, Philip Hans & Lucas, Andre, 2000. "SETS, arbitrage activity, and stock price dynamics," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1289-1306, August.
    See citations under working paper version above.
  34. Jeremy Smith & Nick Taylor & Sanjay Yadav, 1997. "Comparing the bias and misspecification in ARFIMA models," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(5), pages 507-527, September.
    See citations under working paper version above.
  35. Bulkley, George & Taylor, Nick, 1996. "A cross-section test of the present value model," Journal of Empirical Finance, Elsevier, vol. 2(4), pages 295-306, February.

    Cited by:

    1. Rambaccussing, Dooruj, 2015. "Revisiting Shiller's excess volatility hypothesis," SIRE Discussion Papers 2015-33, Scottish Institute for Research in Economics (SIRE).
    2. Dooruj Rambaccussing, 2015. "Revisiting Shiller’s excess volatility hypothesis," Dundee Discussion Papers in Economics 287, Economic Studies, University of Dundee.
    3. Rambaccussing, Dooruj, 2015. "Revisiting Shiller’s excess volatility hypothesis," SIRE Discussion Papers 2015-82, Scottish Institute for Research in Economics (SIRE).
    4. McMillan, David G., 2019. "Predicting firm level stock returns: Implications for asset pricing and economic links," The British Accounting Review, Elsevier, vol. 51(4), pages 333-351.
    5. Rambaccussing, Dooruj, 2010. "A real-time trading rule," MPRA Paper 27148, University Library of Munich, Germany.
    6. Rambaccussing, Dooruj, 2009. "Exploiting price misalignements," MPRA Paper 27147, University Library of Munich, Germany.

Chapters

  1. Woon Sau Leung & Nicholas Taylor, 2013. "Testing for contagion: the impact of US structured markets on international financial markets," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 11, pages 256-284, Edward Elgar Publishing.

    Cited by:

    1. Dieter Smeets, 2016. "Financial Contagion During the European Sovereign Debt Crisis," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 4(2), pages 46-59, April.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.