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Michel Dacorogna

Citations

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

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. U. A. Muller & M. M. Dacorogna & R. D. Dave & O. V. Pictet & R. B. Olsen & J.R. Ward, "undated". "Fractals and Intrinsic Time - a Challenge to Econometricians," Working Papers 1993-08-16, Olsen and Associates.

    Mentioned in:

    1. Taylor Effect and Empirical Scaling Law :: Rmetrics
      by Mahalanobis in Mahalanobis on 2006-10-22 04:19:00

Working papers

  1. Marcel Brautigam & Michel Dacorogna & Marie Kratz, 2019. "Pro-Cyclicality of Traditional Risk Measurements: Quantifying and Highlighting Factors at its Source," Papers 1903.03969, arXiv.org, revised Dec 2019.

    Cited by:

    1. Marcel Bräutigam & Marie Kratz, 2019. "Bivariate FCLT for the Sample Quantile and Measures of Dispersion for Augmented GARCH(p, q) processes," Working Papers hal-02176276, HAL.
    2. Marcel Brautigam & Marie Kratz, 2020. "The Impact of the Choice of Risk and Dispersion Measure on Procyclicality," Papers 2001.00529, arXiv.org.
    3. Marcel, Bräutigam & Marie, Kratz, 2019. "Bivariate FCLT for the Sample Quantile and Measures of Dispersion for Augmented GARCH(p, q) processes," ESSEC Working Papers WP1909, ESSEC Research Center, ESSEC Business School.

  2. Marcel, Bräutigam & Michel, Dacorogna & Marie, Kratz, 2018. "Predicting risk with risk measures : an empirical study," ESSEC Working Papers WP1803, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Marcel, Bräutigam & Marie, Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," ESSEC Working Papers WP1807, ESSEC Research Center, ESSEC Business School.
    2. Marcel Bräutigam & Marie Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," Working Papers hal-02296832, HAL.

  3. Dacorogna, Michel M, 2017. "Approaches and Techniques to Validate Internal Model Results," MPRA Paper 79632, University Library of Munich, Germany.

    Cited by:

    1. Borgonovo, Emanuele & Clemente, Gian Paolo & Rabitti, Giovanni, 2024. "Why insurance regulators need to require sensitivity settings of internal models for their approval," Finance Research Letters, Elsevier, vol. 60(C).

  4. Apicella, Giovanna & Dacorogna, Michel M, 2016. "A General framework for modelling mortality to better estimate its relationship with interest rate risks," MPRA Paper 75788, University Library of Munich, Germany.

    Cited by:

    1. Wenlong Hu, 2020. "Risk management of guaranteed minimum maturity benefits under stochastic mortality and regime-switching by Fourier space time-stepping framework," Papers 2006.15483, arXiv.org, revised Dec 2020.
    2. Bacinello, Anna Rita & Maggistro, Rosario & Zoccolan, Ivan, 2024. "Risk-neutral valuation of GLWB riders in variable annuities," Insurance: Mathematics and Economics, Elsevier, vol. 114(C), pages 1-14.
    3. Huang, Yiming & Mamon, Rogemar & Xiong, Heng, 2022. "Valuing guaranteed minimum accumulation benefits by a change of numéraire approach," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 1-26.
    4. Rabitti, Giovanni & Borgonovo, Emanuele, 2020. "Is mortality or interest rate the most important risk in annuity models? A comparison of sensitivity analysis methods," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 48-58.
    5. Raj Kumari Bahl & Sotirios Sabanis, 2017. "General Price Bounds for Guaranteed Annuity Options," Papers 1707.00807, arXiv.org.
    6. Anna Rita Bacinello & Ivan Zoccolan, 2019. "Variable annuities with a threshold fee: valuation, numerical implementation and comparative static analysis," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 21-49, June.

  5. Dacorogna, Michel M & Busse, Marc, 2016. "The Price of Being a Systemically Important Financial Institution (SIFI)," MPRA Paper 75787, University Library of Munich, Germany.

    Cited by:

    1. Michel Dacorogna & Juan-José Francisco Miguelez & Marie Kratz, 2016. "Risk neutral versus real-world distribution on puclicly listed bank corporations," Working Papers hal-01373071, HAL.
    2. A. Mantovi, 2019. "Information insensitivity, collateral flows and the logic of financial stability," Economics Department Working Papers 2019-EP01, Department of Economics, Parma University (Italy).

  6. Dacorogna, Michel & Elbahtouri, Laila & Kratz, Marie, 2015. "Explicit diversifiction benefit for dependent risks," ESSEC Working Papers WP1522, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Cuberos A. & Masiello E. & Maume-Deschamps V., 2015. "High level quantile approximations of sums of risks," Dependence Modeling, De Gruyter, vol. 3(1), pages 1-18, October.

  7. Dacorogna, Michel & Kratz, Marie, 2015. "Living in a Stochastic World and Managing Complex Risks," ESSEC Working Papers WP1517, ESSEC Research Center, ESSEC Business School.

    Cited by:

    1. Apicella, Giovanna & Dacorogna, Michel M, 2016. "A General framework for modelling mortality to better estimate its relationship with interest rate risks," MPRA Paper 75788, University Library of Munich, Germany.
    2. Nehla, Debbabi & Marie, Kratz & Mamadou , Mboup, 2016. "A self-calibrating method for heavy tailed data modeling : Application in neuroscience and finance," ESSEC Working Papers WP1619, ESSEC Research Center, ESSEC Business School.
    3. Nehla Debbabi & Marie Kratz & Mamadou Mboup, 2016. "A self-calibrating method for heavy tailed data modeling : Application in neuroscience and finance," Working Papers hal-01424298, HAL.

  8. Marc Busse & Michel Dacorogna & Marie Kratz, 2013. "The impact of systemic risk on the diversification benefits of a risk portfolio," Papers 1312.0506, arXiv.org.

    Cited by:

    1. Suzanne Emmer & Marie Kratz & Dirk Tasche, 2013. "What Is the Best Risk Measure in Practice? A Comparison of Standard Measures," Working Papers hal-00921283, HAL.
    2. Feng, Runhuan & Shimizu, Yasutaka, 2016. "Applications of central limit theorems for equity-linked insurance," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 138-148.
    3. Le, Richard & Ku, Hyejin, 2022. "Reducing systemic risk in a multi-layer network using reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    4. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    5. Alexandru V. Asimit & Raluca Vernic & Ricardas Zitikis, 2016. "Background Risk Models and Stepwise Portfolio Construction," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 805-827, September.
    6. Isshaq, Zangina & Faff, Robert, 2016. "Does the uncertainty of firm-level fundamentals help explain cross-sectional differences in liquidity commonality?," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 153-161.

  9. Bürgi, Roland & Dacorogna, Michel M & Iles, Roger, 2008. "Risk aggregation, dependence structure and diversification benefit," MPRA Paper 10054, University Library of Munich, Germany.

    Cited by:

    1. Dacorogna, Michel M, 2017. "Approaches and Techniques to Validate Internal Model Results," MPRA Paper 79632, University Library of Munich, Germany.
    2. Xia Han & Liyuan Lin & Ruodu Wang, 2022. "Diversification quotients: Quantifying diversification via risk measures," Papers 2206.13679, arXiv.org, revised Jul 2024.
    3. Chaoubi, Ihsan & Cossette, Hélène & Gadoury, Simon-Pierre & Marceau, Etienne, 2020. "On sums of two counter-monotonic risks," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 47-60.
    4. Arbenz, Philipp & Hummel, Christoph & Mainik, Georg, 2012. "Copula based hierarchical risk aggregation through sample reordering," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 122-133.
    5. Han, Xia & Lin, Liyuan & Wang, Ruodu, 2023. "Diversification quotients based on VaR and ES," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 185-197.

  10. Stefan Denzler & Michel M. Dacorogna & Ulrich A. Mueller & Alexander McNeil, 2005. "From Default Probabilities To Credit Spreads: Credit Risk Models Do Explain Market Prices," Finance 0504011, University Library of Munich, Germany.

    Cited by:

    1. Tzeng, Kae-Yih & Su, Yi-Kai, 2024. "Can U.S. macroeconomic indicators forecast cryptocurrency volatility?," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    2. John A. Major, 2019. "Methodological Considerations in the Statistical Modeling of Catastrophe Bond Prices," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 22(1), pages 39-56, March.
    3. Mirza, Nawazish & Rahat, Birjees & Naqvi, Bushra & Rizvi, Syed Kumail Abbas, 2023. "Impact of Covid-19 on corporate solvency and possible policy responses in the EU," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 181-190.
    4. Andreasen, Eugenia & Valenzuela, Patricio, 2016. "Financial openness, domestic financial development and credit ratings," Finance Research Letters, Elsevier, vol. 16(C), pages 11-18.
    5. P. Zhukov E. & П. Жуков Е., 2018. "Разве стоимость компании действительно зависит от средневзвешенной стоимости капитала и свободного денежного потока? Свидетельства иррациональности в нефтегазовом секторе // Does Enterprise Value Real," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 6(1), pages 17-28.
    6. Albrecher, Hansjörg & Dacorogna, Michel M, 2024. "Allocating Capital to Time: Introducing Credit Migration for Measuring Time-Related Risks," MPRA Paper 122323, University Library of Munich, Germany.
    7. Khan, Mohammad Azeem & Ahmad, Wasim, 2022. "Fresh evidence on the relationship between market power and default risk of Indian banks," Finance Research Letters, Elsevier, vol. 46(PA).
    8. Mitra, Sovan & Karathanasopoulos, Andreas & Sermpinis, Georgios & Dunis, Christian & Hood, John, 2015. "Operational risk: Emerging markets, sectors and measurement," European Journal of Operational Research, Elsevier, vol. 241(1), pages 122-132.

  11. Fulvio Corsi & Gilles Zumbach & Ulrich Müller & Michel Dacorogna, 2004. "Consistent high-precision volatility from high-frequency data," Finance 0407005, University Library of Munich, Germany.

    Cited by:

    1. T. Di Matteo & T. Aste & Michel M. Dacorogna, 2004. "Using the Scaling Analysis to Characterize Financial Markets," Finance 0402014, University Library of Munich, Germany.
    2. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    3. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
    4. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    7. David Mcmillan & Alan Speight, 2008. "Long-memory in high-frequency exchange rate volatility under temporal aggregation," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 251-261.
    8. Basel M. A. Awartani, 2008. "Forecasting volatility with noisy jumps: an application to the Dow Jones Industrial Average stocks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 267-278.
    9. Alexander Saichev & Didier Sornette & Vladimir Filimonov & Fulvio Corsi, 2009. "Homogeneous Volatility Bridge Estimators," Papers 0912.1617, arXiv.org.
    10. Jonathan Dark, 2004. "Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures," Monash Econometrics and Business Statistics Working Papers 5/04, Monash University, Department of Econometrics and Business Statistics.
    11. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    12. Aktas, Osman Ulas & Kryzanowski, Lawrence & Zhang, Jie, 2021. "Volatility spillover around price limits in an emerging market," Finance Research Letters, Elsevier, vol. 39(C).
    13. Gilles Zumbach, 2004. "How the trading activity scales with the company sizes in the FTSE 100," Papers cond-mat/0407769, arXiv.org.
    14. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    15. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    16. Gilles Zumbach, 2004. "How trading activity scales with company size in the FTSE 100," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 441-456.
    17. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    18. Uppal, Raman & DeMiguel, Victor & Plyakha, Yuliya & Vilkov, Grigory, 2010. "Improving Portfolio Selection Using Option-Implied Volatility and Skewness," CEPR Discussion Papers 7686, C.E.P.R. Discussion Papers.
    19. Shcherba, Alexandr, 2014. "Comparing «Realized volatility» models in the VaR calculation for the Russian equity market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 120-136.
    20. Simone Bianco & Roberto Reno, 2009. "Unexpected volatility and intraday serial correlation," Quantitative Finance, Taylor & Francis Journals, vol. 9(4), pages 465-475.
    21. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
    22. Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
    23. Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
    24. Jin-Huei Yeh & Jying-Nan Wang & Chung-Ming Kuan, 2014. "A noise-robust estimator of volatility based on interquantile ranges," Review of Quantitative Finance and Accounting, Springer, vol. 43(4), pages 751-779, November.
    25. Bertrand B. Maillet & Thierry L. Michel, 2005. "The Impact of the 9/11 Events on the American and French Stock Markets," Review of International Economics, Wiley Blackwell, vol. 13(3), pages 597-611, August.
    26. Marina Theodosiou, 2010. "Calendar Time Sampling of High Frequency Financial Asset Price and the Verdict on Jumps," Working Papers 2010-7, Central Bank of Cyprus.
    27. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    28. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.
    29. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    30. Oomen, Roel C. A., 2004. "Modelling realized variance when returns are serially correlated [Modellierung realisierter Varianz bei autokorrelierten Erträgen]," Discussion Papers, Research Unit: Market Processes and Governance SP II 2004-11, WZB Berlin Social Science Center.
    31. Simone Bianco & Roberto Ren'o, 2006. "Unexpected volatility and intraday serial correlation," Papers physics/0610023, arXiv.org.
    32. Philippe Masset & Martin Wallmeier, 2010. "A High†Frequency Investigation of the Interaction between Volatility and DAX Returns," European Financial Management, European Financial Management Association, vol. 16(3), pages 327-344, June.
    33. Thomas Kraus & Heinz Zimmermann, 2002. "Stock Option Listings:Information versus Liquidity Effects," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 138(I), pages 83-97, March.
    34. A. Saichev & D. Sornette & V. Filimonov & F. Corsi, 2014. "Bridge homogeneous volatility estimators," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 87-99, January.
    35. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
    36. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    37. Asger Lunde & Peter Reinhard Hansen, 2004. "Realized Variance and IID Market Microstructure Noise," Econometric Society 2004 North American Summer Meetings 526, Econometric Society.
    38. Buckle, Mike & Chen, Jing & Guo, Qian & Tong, Chen, 2018. "Do ETFs lead the price moves? Evidence from the major US markets," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 91-103.
    39. Bollerslev, Tim & Zhang, Benjamin Y. B., 2003. "Measuring and modeling systematic risk in factor pricing models using high-frequency data," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 533-558, December.
    40. Marcel Dettling & Peter Buhlmann, 2004. "Volatility and risk estimation with linear and nonlinear methods based on high frequency data," Applied Financial Economics, Taylor & Francis Journals, vol. 14(10), pages 717-729.

  12. T. Di Matteo & T. Aste & M. M. Dacorogna, 2004. "Long term memories of developed and emerging markets: using the scaling analysis to characterize their stage of development," Papers cond-mat/0403681, arXiv.org.

    Cited by:

    1. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    3. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. Wang, Yuanyuan & Shang, Pengjian, 2018. "A new measurement of financial time irreversibility based on information measures method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 221-230.
    5. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
    6. Onur Özdemir & Anoop S. Kumar, 2024. "Dynamic Efficiency and Herd Behavior During Pre- and Post-COVID-19 in the NFT Market: Evidence from Multifractal Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1255-1279, March.
    7. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and multifractality in the term structure of LIBOR interest rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 603-614.
    8. Siew Ann Cheong, 2013. "Econophysics: An Experimental Course for Advanced Undergraduates in the Nanyang Technological University," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 79-99, July.
    9. Tiwari, Aviral Kumar & Umar, Zaghum & Alqahtani, Faisal, 2021. "Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach," Research in International Business and Finance, Elsevier, vol. 57(C).
    10. Luis Miguel Doncel & Pilar Grau-Carles & Jorge Sainz, 2009. "On the long-term behavior of mutual fund returns," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 653-660.
    11. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    12. Zunino, Luciano & Tabak, Benjamin M. & Serinaldi, Francesco & Zanin, Massimiliano & Pérez, Darío G. & Rosso, Osvaldo A., 2011. "Commodity predictability analysis with a permutation information theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 876-890.
    13. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    14. Riccardo Junior Buonocore & Tomaso Aste & Tiziana Di Matteo, 2015. "Measuring multiscaling in financial time-series," Papers 1509.05471, arXiv.org, revised Sep 2015.
    15. Stosic, Dusan & Stosic, Darko & de Mattos Neto, Paulo S.G. & Stosic, Tatijana, 2019. "Multifractal characterization of Brazilian market sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 956-964.
    16. Gaffeo, Edoardo, 2019. "Leverage and evolving heterogeneous beliefs in a simple agent-based financial market," Finance Research Letters, Elsevier, vol. 29(C), pages 272-279.
    17. Los, Cornelis A. & Yu, Bing, 2008. "Persistence characteristics of the Chinese stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 64-82.
    18. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    19. Jiang, Yonghong & Nie, He & Ruan, Weihua, 2018. "Time-varying long-term memory in Bitcoin market," Finance Research Letters, Elsevier, vol. 25(C), pages 280-284.
    20. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    21. Dilip Kumar & S. Maheswaran, 2015. "Long memory in Indian exchange rates: an application of power-law scaling analysis," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 8(1-2), pages 90-107, July.
    22. J. Coulon & Y. Malevergne, 2011. "Heterogeneous expectations and long-range correlation of the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1329-1356, November.
    23. Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006. "From default probabilities to credit spreads: Credit risk models do explain market prices," Finance Research Letters, Elsevier, vol. 3(2), pages 79-95, June.
    24. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    25. Hasan, Rashid & Mohammad, Salim M., 2015. "Multifractal analysis of Asian markets during 2007–2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 746-761.
    26. He, Ling-Yun & Fan, Ying & Wei, Yi-Ming, 2009. "Impact of speculator's expectations of returns and time scales of investment on crude oil price behaviors," Energy Economics, Elsevier, vol. 31(1), pages 77-84, January.
    27. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    28. Kristoufek, Ladislav, 2009. "R/S analysis and DFA: finite sample properties and confidence intervals," MPRA Paper 16446, University Library of Munich, Germany.
    29. Baldovin, Fulvio & Caporin, Massimiliano & Caraglio, Michele & Stella, Attilio L. & Zamparo, Marco, 2015. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Journal of Econometrics, Elsevier, vol. 187(2), pages 486-497.
    30. Marcus F. da Silva & Eder Johnson de Area Leão Pereira & Idaraí Santos de Santana & José Garcia Vivas Miranda, 2013. "Pattern of fluctuations in the exchange rate change from fixed to floating, in Brazil, Argentina and Mexico," Economics Bulletin, AccessEcon, vol. 33(2), pages 1547-1555.
    31. Sonali Agarwal & Anshul Vats, 2024. "A Comparative Study of Financial Crises: Fractal Dissection of Investor Rationality," Vision, , vol. 28(2), pages 193-209, April.
    32. Aditya Banerjee & Samit Paul, 2024. "Idiosyncrasies of Intraday Risk in Emerging and Developed Markets: Efficacy of the MCS-GARCH Model and Extreme Value Theory," Global Business Review, International Management Institute, vol. 25(2), pages 468-490, April.
    33. Patrice Abry & Yannick Malevergne & Herwig Wendt & Marc Senneret & Laurent Jaffrès & Blaise Liaustrat, 2019. "Shuffling for understanding multifractality, application to asset price time series," Post-Print hal-02361738, HAL.
    34. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    35. Cajueiro, Daniel O. & Tabak, Benjamin M., 2009. "Multifractality and herding behavior in the Japanese stock market," Chaos, Solitons & Fractals, Elsevier, vol. 40(1), pages 497-504.
    36. Sierra-Porta, D., 2024. "A multifractal approach to understanding Forbush Decrease events: Correlations with geomagnetic storms and space weather phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    37. Chuo Chang, 2020. "Dynamic correlations and distributions of stock returns on China's stock markets," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-6.
    38. Lin, Xiaoqiang & Fei, Fangyu, 2013. "Long memory revisit in Chinese stock markets: Based on GARCH-class models and multiscale analysis," Economic Modelling, Elsevier, vol. 31(C), pages 265-275.
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    163. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2020. "Multifractal Analysis of Market Efficiency across Structural Breaks: Implications for the Adaptive Market Hypothesis," JRFM, MDPI, vol. 13(10), pages 1-18, October.
    164. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    165. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188, arXiv.org.
    166. Ladislav Krištoufek, 2010. "Rescaled Range Analysis and Detrended Fluctuation Analysis: Finite Sample Properties and Confidence Intervals," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(3), pages 315-329, November.
    167. Juan Benjamin Duarte Duarte & Katherine Julieth Sierra Suarez & Juan Manuel Mascarenas Perez-Inigo, 2014. "Evaluation Of Long-Term Memory In Colombian Stock Market By Hurst Coefficient, Evaluacion De La Memoria De Largo Plazo Del Mercado Bursatil Colombiano Mediante El Coeficiente De Hurst," Revista Internacional Administracion & Finanzas, The Institute for Business and Finance Research, vol. 7(4), pages 1-10.
    168. Dias, Rui & da Silva, Jacinto Vidigal & Dionísio, Andreia, 2019. "Financial markets of the LAC region: Does the crisis influence the financial integration?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 160-173.
    169. Gu, Gao-Feng & Xiong, Xiong & Zhang, Yong-Jie & Chen, Wei & Zhang, Wei & Zhou, Wei-Xing, 2016. "Stylized facts of price gaps in limit order books," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 48-58.
    170. Cristescu, Constantin P. & Stan, Cristina & Scarlat, Eugen I. & Minea, Teofil & Cristescu, Cristina M., 2012. "Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2623-2635.
    171. Aloui, Chaker & Shahzad, Syed Jawad Hussain & Jammazi, Rania, 2018. "Dynamic efficiency of European credit sectors: A rolling-window multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 337-349.
    172. Gurjeet Dhesi & Bilal Shakeel & Marcel Ausloos, 2021. "Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach," Annals of Operations Research, Springer, vol. 299(1), pages 1397-1410, April.
    173. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "Efficiency of Thai stock markets: Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 204-209.
    174. Jaksic, Vesna & Mandic, Danilo P. & Karoumi, Raid & Basu, Bidroha & Pakrashi, Vikram, 2016. "Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 100-120.
    175. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    176. Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2014. "Stylized facts of price gaps in limit order books: Evidence from Chinese stocks," Papers 1405.1247, arXiv.org.
    177. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    178. Siokis, Fotios M., 2018. "Credit market Jitters in the course of the financial crisis: A permutation entropy approach in measuring informational efficiency in financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 266-275.
    179. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    180. Liu, Chang & Chang, Chuo, 2021. "Combination of transition probability distribution and stable Lorentz distribution in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    181. Paulo Ferreira & Marcus Fernandes da Silva & Idaraí Santos de Santana, 2019. "Detrended Correlation Coefficients Between Exchange Rate (in Dollars) and Stock Markets in the World’s Largest Economies," Economies, MDPI, vol. 7(1), pages 1-11, February.
    182. Noemi Nava & Tiziana Di Matteo & Tomaso Aste, 2015. "Time-dependent scaling patterns in high frequency financial data," Papers 1508.07428, arXiv.org, revised Dec 2015.
    183. Ferreira, Paulo, 2018. "Efficiency or speculation? A time-varying analysis of European sovereign debt," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1295-1308.
    184. Mahjoub, Amal & Attia, Najmeddine, 2022. "A relative vectorial multifractal formalism," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    185. Anton Golub & Gregor Chliamovitch & Alexandre Dupuis & Bastien Chopard, 2014. "Multi-scale Representation of High Frequency Market Liquidity," Papers 1402.2198, arXiv.org.
    186. Fonseca, Carla L.G. & de Resende, Charlene C. & Fernandes, Danilo H.C. & Cardoso, Rodrigo T.N. & de Magalhães, A.R. Bosco, 2021. "Is the choice of the candlestick dimension relevant in econophysics?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    187. Pan, Zhiyuan & Wang, Yudong & Liu, Li, 2016. "The relationships between petroleum and stock returns: An asymmetric dynamic equi-correlation approach," Energy Economics, Elsevier, vol. 56(C), pages 453-463.
    188. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.
    189. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    190. Ning, Ye & Wang, Yiming & Su, Chi-wei, 2017. "How did China’s foreign exchange reform affect the efficiency of foreign exchange market?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 219-226.

  13. T. Di Matteo & T. Aste & M. M. Dacorogna, 2003. "Using the Scaling Analysis to Characterize Financial Markets," Papers cond-mat/0302434, arXiv.org.

    Cited by:

    1. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    2. Ioan Roxana, 2020. "Capital Market Correlations Structure During The Covid-19 Crisis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 67-79, December.
    3. Selçuk, Faruk, 2004. "Financial earthquakes, aftershocks and scaling in emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 306-316.

  14. Michel Dacorogna & Peter Blum, 2003. "Extreme Moves in Foreign Exchange Rates and Risk Limit Setting," Risk and Insurance 0306004, University Library of Munich, Germany.

    Cited by:

    1. Ana-Maria Gavril, 2009. "Exchange Rate Risk: Heads or Tails," Advances in Economic and Financial Research - DOFIN Working Paper Series 35, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.

  15. Peter Blum & Michel Dacorogna & Lars Jaeger, 2003. "Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations," Risk and Insurance 0311001, University Library of Munich, Germany.

    Cited by:

    1. Roumpis, Efthymios & Syriopoulos, Theodore, 2014. "Dynamics and risk factors in hedge funds returns: Implications for portfolio construction and performance evaluation," The Journal of Economic Asymmetries, Elsevier, vol. 11(C), pages 58-77.

  16. Michel Dacorogna & Gianluca Oderda & Tobias Jung, 2003. "Credit Risk Models - Do They Deliver Their Promises? A Quantitative Assessment," Risk and Insurance 0306003, University Library of Munich, Germany.

    Cited by:

    1. Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006. "From default probabilities to credit spreads: Credit risk models do explain market prices," Finance Research Letters, Elsevier, vol. 3(2), pages 79-95, June.
    2. Marta Gómez-Puig & Simón Sosvilla-Rivero & Manish K. Singh, 2015. "Sovereigns and banks in the euro area: A tale of two crises," Working Papers 15-01, Asociación Española de Economía y Finanzas Internacionales.
    3. Li, Ming-Yuan Leon & Miu, Peter, 2010. "A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 818-833, September.
    4. Nidhi Aggarwal & Manish K. Singh & Susan Thomas, 2022. "Do decreases in Distance-to-Default predict rating downgrades?," Working Papers 14, xKDR.
    5. Manish K. Singh & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2014. "“Forward Looking Banking Stress in EMU Countries”," IREA Working Papers 201421, University of Barcelona, Research Institute of Applied Economics, revised Oct 2014.
    6. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    7. Jayasekera, Ranadeva, 2018. "Prediction of company failure: Past, present and promising directions for the future," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 196-208.
    8. Manish K. Singh & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "“Bank risk behavior and connectedness in EMU countries”," IREA Working Papers 201517, University of Barcelona, Research Institute of Applied Economics, revised Jun 2015.
    9. Wei Ting & Sin‐Hui Yen & Chien‐Liang Chiu, 2008. "The Influence of Qualified Foreign Institutional Investors on the Association between Default Risk and Audit Opinions: Evidence from the Chinese Stock Market," Corporate Governance: An International Review, Wiley Blackwell, vol. 16(5), pages 400-415, September.
    10. Li-Su Huang, 2022. "Directors and officers liability insurance and default risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 375-408, April.
    11. Marta Gómez-Puig & Simón Sosvilla-Rivero & Manish K. Singh, 2018. "“Incorporating creditors' seniority into contingent claim models:Application to peripheral euro area countries”," IREA Working Papers 201803, University of Barcelona, Research Institute of Applied Economics, revised Feb 2018.
    12. Nidhi Aggarwal & Manish Singh & Susan Thomas, 2012. "Do changes in distance-to-default anticipate changes in the credit rating?," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2012-010, Indira Gandhi Institute of Development Research, Mumbai, India.
    13. Wei Ting & Sin-Hui Yen & Sheng-Shih Huang, 2009. "Top Management Compensation, Earnings Management And Default Risk: Insights From The Chinese Stock Market," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 3(1), pages 31-46.

  17. Peter Blum & Michel Dacorogna, 2003. "Dynamic Financial Analysis - Understanding Risk and Value Creation in Insurance," Risk and Insurance 0306002, University Library of Munich, Germany.

    Cited by:

    1. Peter Blum & Michel Dacorogna & Lars Jaeger, 2003. "Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations," Risk and Insurance 0311001, University Library of Munich, Germany.

  18. Michel Dacorogna & Höskuldur Ari Hauksson & Thomas Domenig & Ulrich Müller & Gennady Samorodnitsky, 2001. "Multivariate extremes, aggregation and risk estimation," CeNDEF Workshop Papers, January 2001 P2, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Suzanne Emmer & Marie Kratz & Dirk Tasche, 2013. "What Is the Best Risk Measure in Practice? A Comparison of Standard Measures," Working Papers hal-00921283, HAL.
    2. Georg Mainik & Ludger Rüschendorf, 2010. "On optimal portfolio diversification with respect to extreme risks," Finance and Stochastics, Springer, vol. 14(4), pages 593-623, December.
    3. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    4. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    5. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    6. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    7. Einmahl, J.H.J. & de Haan, L.F.M. & Piterbarg, V.I., 2001. "Nonparametric estimation of the spectral measure of an extreme value distribution," Other publications TiSEM c3485b9b-a0bd-456f-9baa-0, Tilburg University, School of Economics and Management.
    8. Gilles Zumbach, 2011. "Characterizing heteroskedasticity," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1357-1369, October.
    9. Arnold Polanski & Evarist Stoja, 2013. "Co-dependence of Extreme Events in High Frequency FX Returns," University of East Anglia Applied and Financial Economics Working Paper Series 040, School of Economics, University of East Anglia, Norwich, UK..
    10. Falk, Michael, 2005. "On the generation of a multivariate extreme value distribution with prescribed tail dependence parameter matrix," Statistics & Probability Letters, Elsevier, vol. 75(4), pages 307-314, December.
    11. Härdle, Wolfgang Karl & Spokoiny, Vladimir & Wang, Weining, 2010. "Local quantile regression," SFB 649 Discussion Papers 2011-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Schmidt, Rafael & Hrycej, Tomas & Stutzle, Eric, 2006. "Multivariate distribution models with generalized hyperbolic margins," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2065-2096, April.
    13. Susanne Emmer & Marie Kratz & Dirk Tasche, 2013. "What is the best risk measure in practice? A comparison of standard measures," Papers 1312.1645, arXiv.org, revised Apr 2015.
    14. Jing Ai & Patrick L. Brockett & Tianyang Wang, 2017. "Optimal Enterprise Risk Management and Decision Making With Shared and Dependent Risks," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(4), pages 1127-1169, December.
    15. Gencay, Ramazan & Selcuk, Faruk & Ulugulyagci, Abdurrahman, 2003. "High volatility, thick tails and extreme value theory in value-at-risk estimation," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 337-356, October.
    16. Richards, Jordan & Tawn, Jonathan A., 2022. "On the tail behaviour of aggregated random variables," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    17. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.
    18. Aleksy Leeuwenkamp & Wentao Hu, 2023. "New general dependence measures: construction, estimation and application to high-frequency stock returns," Papers 2309.00025, arXiv.org.
    19. Peter Blum & Michel Dacorogna & Lars Jaeger, 2003. "Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations," Risk and Insurance 0311001, University Library of Munich, Germany.

  19. Olivier V. Pictet & Michel M. Dacorogna & Ulrich A. Muller, 1996. "Heavy tails in high-frequency financial data," Working Papers 1996-12-11, Olsen and Associates.

    Cited by:

    1. Onour, Ibrahim, 2009. "Extreme Risk and Fat-tails Distribution Model:Empirical Analysis," MPRA Paper 17736, University Library of Munich, Germany, revised 20 Sep 2009.
    2. J. Doyne Farmer, 2000. "Physicists Attempt To Scale The Ivory Towers Of Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 311-333.
    3. Pierre Giot, 2005. "Market risk models for intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 11(4), pages 309-324.
    4. Sayantan Ghosh & P. Manimaran & Prasanta K. Panigrahi, 2010. "Characterizing Multi-Scale Self-Similar Behavior and Non-Statistical Properties of Financial Time Series," Papers 1003.2539, arXiv.org, revised Dec 2010.
    5. Weshah Razzak, 2009. "On the GCC Currency Union," EERI Research Paper Series EERI_RP_2009_29, Economics and Econometrics Research Institute (EERI), Brussels.
    6. Nuyts, Jean & Platten, Isabelle, 2001. "Phenomenology of the term structure of interest rates with Padé Approximants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 528-546.
    7. Collins, A. & Hand, C. & Snell, M.C., 2001. "What Makes a Blockbuster? Economic Analysis of Film Success in the United Kingdom," Papers 137, Portsmouth University - Department of Economics.
    8. Dr. Ibrahim Onour, "undated". "The Global Financial Crisis and Equity Markets in Middle East Oil Exporting Countries," API-Working Paper Series 1009, Arab Planning Institute - Kuwait, Information Center.
    9. Martina Nardon & Paolo Pianca, 2006. "Simulation techniques for generalized Gaussian densities," Working Papers 145, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    10. Mora Galán, Alberto & Pérez, Ana, 2004. "Stochastic volatility models and the Taylor effect," DES - Working Papers. Statistics and Econometrics. WS ws046315, Universidad Carlos III de Madrid. Departamento de Estadística.

  20. Olivier V. Pictet & Michel M. Dacorogna & Ulrich A. Muller, 1996. "Hill, Bootstrap and Jackknife Estimators for Heavy Tails," Working Papers 1996-12-10, Olsen and Associates.

    Cited by:

    1. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    2. David Edelman & Thomas Gillespie, 2000. "The Stochastically Subordinated Poisson Normal Process for Modelling Financial Assets," Annals of Operations Research, Springer, vol. 100(1), pages 133-164, December.
    3. Onour, Ibrahim, 2009. "Extreme Risk and Fat-tails Distribution Model:Empirical Analysis," MPRA Paper 17736, University Library of Munich, Germany, revised 20 Sep 2009.
    4. Michel Dacorogna & Peter Blum, 2003. "Extreme Moves in Foreign Exchange Rates and Risk Limit Setting," Risk and Insurance 0306004, University Library of Munich, Germany.
    5. Kratz , Marie, 2013. "There is a VaR Beyond Usual Approximations," ESSEC Working Papers WP1317, ESSEC Research Center, ESSEC Business School.
    6. Tsourti, Zoi & Panaretos, John, 2003. "Extreme Value Index Estimators and Smoothing Alternatives: A Critical Review," MPRA Paper 6390, University Library of Munich, Germany.
    7. F. Clementi & T. Di Matteo & M. Gallegati, 2006. "The Power-law Tail Exponent of Income Distributions," Papers physics/0603061, arXiv.org.
    8. Wolfgang Breymann & Leah Kelly & Eckhard Platen, 2004. "Intraday Empirical Analysis and Modeling of Diversified World Stock Indices," Research Paper Series 125, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Céline Azizieh & Wolfgang Breymann, 2005. "Estimation of the Stylized Facts of a Stochastic Cascade Model," Working Papers CEB 05-009.RS, ULB -- Universite Libre de Bruxelles.
    10. Sayantan Ghosh & P. Manimaran & Prasanta K. Panigrahi, 2010. "Characterizing Multi-Scale Self-Similar Behavior and Non-Statistical Properties of Financial Time Series," Papers 1003.2539, arXiv.org, revised Dec 2010.
    11. Weshah Razzak, 2009. "On the GCC Currency Union," EERI Research Paper Series EERI_RP_2009_29, Economics and Econometrics Research Institute (EERI), Brussels.
    12. Dr. Ibrahim Onour, "undated". "The Global Financial Crisis and Equity Markets in Middle East Oil Exporting Countries," API-Working Paper Series 1009, Arab Planning Institute - Kuwait, Information Center.
    13. Marie Kratz, 2013. "There is a VaR beyond usual approximations," Papers 1311.0270, arXiv.org.
    14. Raymond Knott & Marco Polenghi, 2006. "Assessing central counterparty margin coverage on futures contracts using GARCH models," Bank of England working papers 287, Bank of England.

  21. Richard B. Olsen & Michel M. Dacorogna & Ulrich A. Muller, & Olivier V. Pictet, "undated". "Going Back to the Basics - Rethinking Market Efficiency," Working Papers 1992-09-07., Olsen and Associates.

    Cited by:

    1. R. Vilela Mendes & Tanya Ara'ujo & Francisco Louc{c}~a, 2002. "Reconstructing an economic space from a market metric," Papers cond-mat/0211108, arXiv.org.
    2. Eric Ringhut & Stefan Kooths, 2003. "Modeling Expectations with GENEFER -- an Artificial Intelligence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 21(1_2), pages 173-194, February.
    3. Spyros Skouras, 1998. "Financial Returns and Efficiency as seen by an Artificial Technical Analyst," Finance 9808001, University Library of Munich, Germany, revised 24 Aug 1998.

  22. Dominique M. Guillaume & Olivier V. Pictet & Michel M. Dacorogna, "undated". "On the intra-daily performance of GARCH processes," Working Papers 1994-07-31, Olsen and Associates.

    Cited by:

    1. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    2. GIOT, Pierre, 2000. "Intraday value-at-risk," LIDAM Discussion Papers CORE 2000045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Dominguez, Kathryn M. E., 2003. "The market microstructure of central bank intervention," Journal of International Economics, Elsevier, vol. 59(1), pages 25-45, January.
    4. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
    5. GIOT, Pierre, 1999. "Time transformations, intraday data and volatility models," LIDAM Discussion Papers CORE 1999044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    7. Gilles O. Zumbach & Michel M. Dacorogna & Jorgen L. Olsen & Richard B. Olsen, 2004. "Introducing a scale of market shocks," Finance 0407004, University Library of Munich, Germany.
    8. David McMillan & Alan Speight, 2002. "Temporal aggregation, volatility components and volume in high frequency UK bond futures," The European Journal of Finance, Taylor & Francis Journals, vol. 8(1), pages 70-92.
    9. Neil Beattie & Jean-François Fillion, 1999. "An Intraday Analysis of the Effectiveness of Foreign Exchange Intervention," Staff Working Papers 99-4, Bank of Canada.

  23. Michel M. Dacorogna, & Ulrich A. Muller & Olivier V. Pictet & Casper De Vries,, "undated". "The Distribution of Extremal Foreign Exchange Rate Returns in Extremely Large Data Sets," Working Papers 1992-10-22, Olsen and Associates.

    Cited by:

    1. Kaizoji, Taisei, 2010. "Stock volatility in the periods of booms and stagnations," MPRA Paper 23727, University Library of Munich, Germany.
    2. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
    3. Taisei Kaizoji, 2005. "Comparison of volatility distributions in the periods of booms and stagnations: an empirical study on stock price indices," Papers physics/0506114, arXiv.org.
    4. Vêlayoudom Marimoutou & Bechir Raggad & Abdelwahed Trabelsi, 2006. "Extreme Value Theory and Value at Risk : Application to Oil Market," Working Papers halshs-00410746, HAL.
    5. Manfred Gilli & Evis këllezi, 2006. "An Application of Extreme Value Theory for Measuring Financial Risk," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 207-228, May.
    6. Y. Malevergne & V. F. Pisarenko & D. Sornette, 2003. "Empirical Distributions of Log-Returns: between the Stretched Exponential and the Power Law?," Papers physics/0305089, arXiv.org.
    7. Jean-Philippe Bouchaud & Marc Potters, 1999. "Worst fluctuation method for fast value-at-risk estimates," Science & Finance (CFM) working paper archive 9909245, Science & Finance, Capital Fund Management.
    8. Charles Goodhart & Takatoshi Ito & Richard Payne, 1995. "One Day in June, 1994: A Study of the Working of Reuters 2000-2 Electronic Foreign Exchange Trading System," NBER Technical Working Papers 0179, National Bureau of Economic Research, Inc.
    9. Neil Beattie & Jean-François Fillion, 1999. "An Intraday Analysis of the Effectiveness of Foreign Exchange Intervention," Staff Working Papers 99-4, Bank of Canada.
    10. Groenendijk, Patrick A. & Lucas, Andre & de Vries, Casper G., 1995. "A note on the relationship between GARCH and symmetric stable processes," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 253-264, September.
    11. Jean-Philippe Bouchaud & Didier Sornette & Christian Walter & Jean-Pierre Aguilar, 1998. "Taming large events: portfolio selection for strongly fluctuating assets," Science & Finance (CFM) working paper archive 500044, Science & Finance, Capital Fund Management.
    12. Peter Blum & Michel Dacorogna & Lars Jaeger, 2003. "Performance and Risk Measurement Challenges For Hedge Funds: Empirical Considerations," Risk and Insurance 0311001, University Library of Munich, Germany.

  24. U. A. Muller & M. M. Dacorogna & R. D. Dave & O. V. Pictet & R. B. Olsen & J.R. Ward, "undated". "Fractals and Intrinsic Time - a Challenge to Econometricians," Working Papers 1993-08-16, Olsen and Associates.

    Cited by:

    1. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    2. Eric Ghysels & Christian Gouriéroux & Joann Jasiak, 1995. "Trading Patterns, Time Deformation and Stochastic Volatility in Foreign Exchange Markets," CIRANO Working Papers 95s-42, CIRANO.
    3. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    4. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    5. Bianchi, Sergio, 2004. "A new distribution-based test of self-similarity," MPRA Paper 16640, University Library of Munich, Germany.
    6. Wang, Jianxin & Yang, Minxian, 2009. "Asymmetric volatility in the foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 597-615, October.
    7. Danilo Delpini & Giacomo Bormetti, 2012. "Stochastic Volatility with Heterogeneous Time Scales," Papers 1206.0026, arXiv.org, revised Apr 2013.
    8. Emanuel Derman, 2002. "The Perception of Time, Risk and Return During Periods of Speculation," Papers cond-mat/0201345, arXiv.org.

  25. Olivier V. Pictet & Michel M. Dacorogna & Rakhal D. Dave & Bastien Chopard & Roberto Schirru & Marco Tomassini, "undated". "Genetic Algorithms with collective sharing for Robust Optimization in Financial Applications," Working Papers 1995-02-06., Olsen and Associates.

    Cited by:

    1. Spyros Skouras, 1998. "Financial Returns and Efficiency as seen by an Artificial Technical Analyst," Finance 9808001, University Library of Munich, Germany, revised 24 Aug 1998.

Articles

  1. Dacorogna, Michel & Debbabi, Nehla & Kratz, Marie, 2023. "Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data," European Journal of Operational Research, Elsevier, vol. 311(2), pages 708-729.

    Cited by:

    1. Matteo Malavasi & Gareth W. Peters & Stefan Treuck & Pavel V. Shevchenko & Jiwook Jang & Georgy Sofronov, 2024. "Cyber Risk Taxonomies: Statistical Analysis of Cybersecurity Risk Classifications," Papers 2410.05297, arXiv.org.
    2. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation In Extreme Value Regression Models Of Hedge Fund Tail Risks," Working Papers hal-04090916, HAL.
    3. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation in Extreme Value Regression Models of Hedge Fund Tail Risks," Papers 2304.06950, arXiv.org.
    4. Wing Fung Chong & Daniel Linders & Zhiyu Quan & Linfeng Zhang, 2023. "Incident-Specific Cyber Insurance," Papers 2308.00921, arXiv.org.

  2. Michel Dacorogna, 2023. "How to Gain Confidence in the Results of Internal Risk Models? Approaches and Techniques for Validation," Risks, MDPI, vol. 11(5), pages 1-20, May.

    Cited by:

    1. Borgonovo, Emanuele & Clemente, Gian Paolo & Rabitti, Giovanni, 2024. "Why insurance regulators need to require sensitivity settings of internal models for their approval," Finance Research Letters, Elsevier, vol. 60(C).

  3. Michel Dacorogna & Marie Kratz, 2023. "Managing cyber risk, a science in the making," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2023(10), pages 1000-1021, November.

    Cited by:

    1. Matteo Malavasi & Gareth W. Peters & Stefan Treuck & Pavel V. Shevchenko & Jiwook Jang & Georgy Sofronov, 2024. "Cyber Risk Taxonomies: Statistical Analysis of Cybersecurity Risk Classifications," Papers 2410.05297, arXiv.org.
    2. Antonello Calabrò & Enrico Cambiaso & Manuel Cheminod & Ivan Cibrario Bertolotti & Luca Durante & Agostino Forestiero & Flavio Lombardi & Giuseppe Manco & Eda Marchetti & Albina Orlando & Giuseppe Pap, 2024. "A Methodological Approach to Securing Cyber-Physical Systems for Critical Infrastructures," Future Internet, MDPI, vol. 16(11), pages 1-19, November.
    3. Dacorogna, Michel & Debbabi, Nehla & Kratz, Marie, 2023. "Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data," European Journal of Operational Research, Elsevier, vol. 311(2), pages 708-729.

  4. Michel Dacorogna & Marie Kratz, 2022. "Special Issue “Cyber Risk and Security”," Risks, MDPI, vol. 10(6), pages 1-4, May.

    Cited by:

    1. Dacorogna, Michel & Debbabi, Nehla & Kratz, Marie, 2023. "Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data," European Journal of Operational Research, Elsevier, vol. 311(2), pages 708-729.

  5. Giovanna Apicella & Michel Dacorogna & Emilia Di Lorenzo & Marilena Sibillo, 2019. "Improving the Forecast of Longevity by Combining Models," North American Actuarial Journal, Taylor & Francis Journals, vol. 23(2), pages 298-319, April.

    Cited by:

    1. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.

  6. Dacorogna, Michel, 2018. "A change of paradigm for the insurance industry," Annals of Actuarial Science, Cambridge University Press, vol. 12(2), pages 211-232, September.

    Cited by:

    1. Ettlin, Nicolas & Farkas, Walter & Kull, Andreas & Smirnow, Alexander, 2020. "Optimal risk-sharing across a network of insurance companies," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 39-47.
    2. Albrecher, Hansjörg & Dacorogna, Michel M, 2024. "Allocating Capital to Time: Introducing Credit Migration for Measuring Time-Related Risks," MPRA Paper 122323, University Library of Munich, Germany.

  7. Dacorogna, Michel & Elbahtouri, Laila & Kratz, Marie, 2018. "Validation of aggregated risks models," Annals of Actuarial Science, Cambridge University Press, vol. 12(2), pages 433-454, September.

    Cited by:

    1. Michel Dacorogna, 2023. "How to Gain Confidence in the Results of Internal Risk Models? Approaches and Techniques for Validation," Risks, MDPI, vol. 11(5), pages 1-20, May.
    2. Bingzhen Geng & Yang Liu & Yimiao Zhao, 2024. "Value-at-Risk- and Expectile-based Systemic Risk Measures and Second-order Asymptotics: With Applications to Diversification," Papers 2404.18029, arXiv.org.

  8. Michel Dacorogna & Alessandro Ferriero & David Krief, 2018. "One-Year Change Methodologies for Fixed-Sum Insurance Contracts," Risks, MDPI, vol. 6(3), pages 1-29, July.

    Cited by:

    1. Carnevale Giulio Ercole & Clemente Gian Paolo, 2020. "A Bayesian Internal Model for Reserve Risk: An Extension of the Correlated Chain Ladder," Risks, MDPI, vol. 8(4), pages 1-20, November.
    2. Michel Dacorogna, 2023. "How to Gain Confidence in the Results of Internal Risk Models? Approaches and Techniques for Validation," Risks, MDPI, vol. 11(5), pages 1-20, May.

  9. Michel Dacorogna & Marc Busse, 2017. "The Price of Being a Systemically Important Financial Institution (SIFI)," International Review of Finance, International Review of Finance Ltd., vol. 17(4), pages 611-616, December.
    See citations under working paper version above.
  10. Marc Busse & Michel Dacorogna & Marie Kratz, 2014. "The Impact of Systemic Risk on the Diversification Benefits of a Risk Portfolio," Risks, MDPI, vol. 2(3), pages 1-17, July.
    See citations under working paper version above.
  11. Busse, Marc & Müller, Ulrich & Dacorogna, Michel, 2010. "Robust Estimation of Reserve Risk," ASTIN Bulletin, Cambridge University Press, vol. 40(2), pages 453-489, November.

    Cited by:

    1. Michel Dacorogna & Alessandro Ferriero & David Krief, 2018. "One-Year Change Methodologies for Fixed-Sum Insurance Contracts," Risks, MDPI, vol. 6(3), pages 1-29, July.
    2. Michel Dacorogna, 2023. "How to Gain Confidence in the Results of Internal Risk Models? Approaches and Techniques for Validation," Risks, MDPI, vol. 11(5), pages 1-20, May.
    3. Dacorogna, Michel M, 2017. "Approaches and Techniques to Validate Internal Model Results," MPRA Paper 79632, University Library of Munich, Germany.
    4. Pitselis, Georgios & Grigoriadou, Vasiliki & Badounas, Ioannis, 2015. "Robust loss reserving in a log-linear model," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 14-27.
    5. Rüdiger Kiesel & Robin Rühlicke & Gerhard Stahl & Jinsong Zheng, 2016. "The Wasserstein Metric and Robustness in Risk Management," Risks, MDPI, vol. 4(3), pages 1-14, August.

  12. Jean-Luc Besson & Michel M Dacorogna & Paolo de Martin & Michael Kastenholz & Michael Moller, 2009. "How Much Capital Does a Reinsurance Need?," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 34(2), pages 159-174, April.

    Cited by:

    1. Das, Shubhabrata & Kratz, Marie, 2010. "On Devising Various Alarm Systems for Insurance Companies," ESSEC Working Papers DR 10008, ESSEC Research Center, ESSEC Business School.
    2. Burnecki, Krzysztof & Giuricich, Mario Nicoló & Palmowski, Zbigniew, 2019. "Valuation of contingent convertible catastrophe bonds — The case for equity conversion," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 238-254.
    3. Das, S. & Kratz, M., 2012. "Alarm system for insurance companies: A strategy for capital allocation," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 53-65.
    4. Marie Kratz & Shubhabrata Das, 2010. "On Devising Various Alarm Systems for Insurance Companies," Post-Print hal-00572546, HAL.
    5. Shubhabrata Das & Marie Kratz, 2010. "Alarm System for Insurance Companies: A Strategy for Capital Allocation," Papers 1006.5473, arXiv.org.

  13. Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006. "From default probabilities to credit spreads: Credit risk models do explain market prices," Finance Research Letters, Elsevier, vol. 3(2), pages 79-95, June.
    See citations under working paper version above.
  14. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    See citations under working paper version above.
  15. Di Matteo, T. & Aste, T. & Dacorogna, M.M., 2003. "Scaling behaviors in differently developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 183-188.

    Cited by:

    1. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    3. Wang, Yuanyuan & Shang, Pengjian, 2018. "A new measurement of financial time irreversibility based on information measures method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 221-230.
    4. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
    5. Siew Ann Cheong, 2013. "Econophysics: An Experimental Course for Advanced Undergraduates in the Nanyang Technological University," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 79-99, July.
    6. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    7. Marina Resta, 2004. "Multifractal analysis of Power Markets. Some empirical evidence," Econometrics 0410002, University Library of Munich, Germany.
    8. Stanisław Drożdż & Ludovico Minati & Paweł Oświȩcimka & Marek Stanuszek & Marcin Wa̧torek, 2019. "Signatures of the Crypto-Currency Market Decoupling from the Forex," Future Internet, MDPI, vol. 11(7), pages 1-18, July.
    9. Zunino, Luciano & Tabak, Benjamin M. & Serinaldi, Francesco & Zanin, Massimiliano & Pérez, Darío G. & Rosso, Osvaldo A., 2011. "Commodity predictability analysis with a permutation information theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 876-890.
    10. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    11. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    12. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    13. Kristoufek, Ladislav, 2010. "On spurious anti-persistence in the US stock indices," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 68-78.
    14. Chiarucci, Riccardo & Loffredo, Maria I. & Ruzzenenti, Franco, 2017. "Evidences for a structural change in the oil market before a financial crisis: The flat horizon effect," Research in International Business and Finance, Elsevier, vol. 42(C), pages 912-921.
    15. Stavroyiannis, Stavros & Babalos, Vassilios & Bekiros, Stelios & Lahmiri, Salim & Uddin, Gazi Salah, 2019. "The high frequency multifractal properties of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 62-71.
    16. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    17. Hasan, Rashid & Mohammad, Salim M., 2015. "Multifractal analysis of Asian markets during 2007–2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 746-761.
    18. Peng Liu & Yanyan Zheng, 2022. "Precision measurement of the return distribution property of the Chinese stock market index," Papers 2209.08521, arXiv.org, revised Nov 2023.
    19. Conte, Elio & Khrennikov, Andrei & Federici, Antonio & Zbilut, Joseph P., 2009. "Fractal fluctuations and quantum-like chaos in the brain by analysis of variability of brain waves: A new method based on a fractal variance function and random matrix theory: A link with El Naschie f," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2790-2800.
    20. Ladislav KRISTOUFEK & Petra LUNACKOVA, 2013. "Long-term Memory in Electricity Prices: Czech Market Evidence," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 407-424, November.
    21. Sierra-Porta, D., 2024. "A multifractal approach to understanding Forbush Decrease events: Correlations with geomagnetic storms and space weather phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    22. Kumar, A. & Wyłomańska, A. & Połoczański, R. & Sundar, S., 2017. "Fractional Brownian motion time-changed by gamma and inverse gamma process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 648-667.
    23. Ramos-Requena, J.P. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A., 2017. "Introducing Hurst exponent in pair trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 39-45.
    24. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.
    25. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    26. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    27. Selçuk BAYRACI, 2017. "Long-memory, self-similarity and scaling of the long-term government bond yields: Evidence from Turkey and the USA," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(612), A), pages 71-82, Autumn.
    28. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    29. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    30. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2017. "A multifractal detrended fluctuation analysis of financial market efficiency: Comparison using Dow Jones sector ETF indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 182-192.
    31. Mateos, Diego M. & Zozor, Steeve & Olivares, Felipe, 2020. "Contrasting stochasticity with chaos in a permutation Lempel–Ziv complexity — Shannon entropy plane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    32. Khondekar, Mofazzal Hossain & Ghosh, Koushik & Bhattacharjee, Anup Kumar, 2016. "Scaling and nonlinear behaviour of daily mean temperature time series across IndiaAuthor-Name: Ray, Rajdeep," Chaos, Solitons & Fractals, Elsevier, vol. 84(C), pages 9-14.
    33. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "The stylized facts of prediction markets: Analysis of price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 159-170.
    34. Morales, Raffaello & Di Matteo, T. & Aste, Tomaso, 2013. "Non-stationary multifractality in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6470-6483.
    35. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    36. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    37. Antoniades, I.P. & Karakatsanis, L.P. & Pavlos, E.G., 2021. "Dynamical characteristics of global stock markets based on time dependent Tsallis non-extensive statistics and generalized Hurst exponents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    38. Brandi, Giuseppe & Di Matteo, T., 2022. "Multiscaling and rough volatility: An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 84(C).
    39. Domino, Krzysztof, 2012. "The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 156-169.
    40. Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Naveed & Al-Yahyaee, Khamis Hamed, 2018. "Stock market efficiency: A comparative analysis of Islamic and conventional stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 139-153.
    41. Chen, Xuehui & Zhu, Hongli & Zhang, Xinru & Zhao, Lutao, 2022. "A novel time-varying FIGARCH model for improving volatility predictions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    42. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    43. Darko Stosic & Dusan Stosic & Irena Vodenska & H. Eugene Stanley & Tatijana Stosic, 2021. "A new look at calendar anomalies: Multifractality and day of the week effect," Papers 2106.06164, arXiv.org.
    44. Lotfalinezhad, Hamze & Maleki, Ali, 2020. "TTA, a new approach to estimate Hurst exponent with less estimation error and computational time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    45. Stavroyiannis, S. & Makris, I. & Nikolaidis, V., 2010. "Non-extensive properties, multifractality, and inefficiency degree of the Athens Stock Exchange General Index," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 19-24, January.
    46. Mulligan, Robert F., 2017. "The multifractal character of capacity utilization over the business cycle: An application of Hurst signature analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 147-152.
    47. Li, Daye & Kou, Zhun & Sun, Qiankun, 2015. "The scale-dependent market trend: Empirical evidences using the lagged DFA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 26-35.
    48. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Papers 2105.09140, arXiv.org, revised Sep 2021.
    49. Siokis, Fotios M., 2014. "European economies in crisis: A multifractal analysis of disruptive economic events and the effects of financial assistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 283-292.
    50. Noemi Nava & T. Di Matteo & Tomaso Aste, 2015. "Anomalous volatility scaling in high frequency financial data," Papers 1503.08465, arXiv.org, revised Dec 2015.
    51. Wang, Jian & Yan, Yan & Chen, Wenbing & Shao, Wei & Wang, Jian & Tang, Weiwei, 2021. "Equity-linked securities option pricing by fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    52. Vidal-Tomás, David, 2022. "Which cryptocurrency data sources should scholars use?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    53. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    54. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    55. Kostanjcar, Zvonko & Jeren, Branko & Juretic, Zeljan, 2012. "Impact of uncertainty in expected return estimation on stock price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5563-5571.
    56. Raza, Syed Ali & Shah, Nida & Suleman, Muhammed Tahir, 2024. "A multifractal detrended fluctuation analysis of Islamic and conventional financial markets efficiency during the COVID-19 pandemic," International Economics, Elsevier, vol. 177(C).
    57. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    58. Wu, Zhenyu & Shang, Pengjian & Xiong, Hui, 2018. "An improvement of the measurement of time series irreversibility with visibility graph approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 370-378.
    59. Jozef Barunik & Ladislav Kristoufek, 2012. "On Hurst exponent estimation under heavy-tailed distributions," Papers 1201.4786, arXiv.org.
    60. Bariviera, Aurelio F., 2021. "One model is not enough: Heterogeneity in cryptocurrencies’ multifractal profiles," Finance Research Letters, Elsevier, vol. 39(C).
    61. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Trinidad Segovia, J.E., 2013. "Measuring the self-similarity exponent in Lévy stable processes of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5330-5345.
    62. Giuseppe Brandi & T. Di Matteo, 2022. "Multiscaling and rough volatility: an empirical investigation," Papers 2201.10466, arXiv.org.
    63. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    64. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    65. Wang, Fang & Yang, Zhaohui & Wang, Lin, 2016. "Detecting and quantifying cross-correlations by analogous multifractal height cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 954-962.
    66. Zhang, H.S. & Shen, X.Y. & Huang, J.P., 2016. "Pattern of trends in stock markets as revealed by the renormalization method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 340-346.
    67. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    68. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    69. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Mensi, Walid & Kumar, Ronald Ravinesh, 2017. "Examining the efficiency and interdependence of US credit and stock markets through MF-DFA and MF-DXA approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 351-363.
    70. Rizvi, Syed Aun R. & Dewandaru, Ginanjar & Bacha, Obiyathulla I. & Masih, Mansur, 2014. "An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 86-99.
    71. 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.
    72. Stanis{l}aw Dro.zd.z & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek & Marcin Wk{a}torek, 2019. "Signatures of crypto-currency market decoupling from the Forex," Papers 1906.07834, arXiv.org, revised Jul 2019.
    73. Tzouras, Spilios & Anagnostopoulos, Christoforos & McCoy, Emma, 2015. "Financial time series modeling using the Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 50-68.
    74. Corzo Santamaría, Teresa & Martin-Bujack, Karin & Portela, Jose & Sáenz-Diez, Rocio, 2022. "Early market efficiency testing among hydrogen players," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 723-742.
    75. Ioannis P. Antoniades & Giuseppe Brandi & L. G. Magafas & T. Di Matteo, 2020. "The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool," Papers 2010.08890, arXiv.org, revised Dec 2020.
    76. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
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    78. Bariviera, Aurelio F. & Fabregat-Aibar, Laura & Sorrosal-Forradellas, Maria-Teresa, 2023. "Disentangling the impact of economic and health crises on financial markets," Research in International Business and Finance, Elsevier, vol. 65(C).
    79. Pakrashi, Vikram & Kelly, Joe & Harkin, Julie & Farrell, Aidan, 2013. "Hurst exponent footprints from activities on a large structural system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1803-1817.
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    84. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
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    97. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
    98. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
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    106. Antoniades, I.P. & Brandi, Giuseppe & Magafas, L. & Di Matteo, T., 2021. "The use of scaling properties to detect relevant changes in financial time series: A new visual warning tool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    107. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2020. "Multifractal Analysis of Market Efficiency across Structural Breaks: Implications for the Adaptive Market Hypothesis," JRFM, MDPI, vol. 13(10), pages 1-18, October.
    108. Cristescu, Constantin P. & Stan, Cristina & Scarlat, Eugen I. & Minea, Teofil & Cristescu, Cristina M., 2012. "Parameter motivated mutual correlation analysis: Application to the study of currency exchange rates based on intermittency parameter and Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2623-2635.
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    112. Hernández-Pérez, R., 2012. "Allan deviation analysis of financial return series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2883-2888.
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    114. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
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    123. Mulligan, Robert F., 2014. "Multifractality of sectoral price indices: Hurst signature analysis of Cantillon effects in disequilibrium factor markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 252-264.
    124. Jonathan Haynes & Daniel Schmitt & Lukas Grimm, 2019. "Estimating stochastic volatility: the rough side to equity returns," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 449-469, December.
    125. Miśkiewicz, Janusz, 2012. "Economy with the time delay of information flow—The stock market case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1388-1394.

  16. Gencay, Ramazan & Dacorogna, Michel & Olsen, Richard & Pictet, Olivier, 2003. "Foreign exchange trading models and market behavior," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 909-935, April.

    Cited by:

    1. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    2. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    3. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    4. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    5. Gencay, Ramazan & Selcuk, Faruk & Whitcher, Brandon, 2004. "Information flow between volatilities across time scales," MPRA Paper 10355, University Library of Munich, Germany.
    6. Michael D. McKenzie, 2007. "Technical Trading Rules in Emerging Markets and the 1997 Asian Currency Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(4), pages 46-73, August.
    7. Jiali Fang & Ben Jacobsen & Yafeng Qin, 2014. "Predictability of the simple technical trading rules: An out‐of‐sample test," Review of Financial Economics, John Wiley & Sons, vol. 23(1), pages 30-45, January.
    8. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    9. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    10. 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.
    11. Simone Cirillo & Stefan Lloyd & Peter Nordin, 2014. "Evolving intraday foreign exchange trading strategies utilizing multiple instruments price series," Papers 1411.2153, arXiv.org.
    12. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    13. Menkhoff, Lukas & Taylor, Mark P., 2006. "The Obstinate Passion of Foreign Exchange Professionals : Technical Analysis," The Warwick Economics Research Paper Series (TWERPS) 769, University of Warwick, Department of Economics.
    14. Sayo Ayodeji, 2015. "Modeling Asymmetric Effect in African Currency Markets: Evidence from Kenya," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 4(3), pages 1-2.
    15. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
    16. Cecilia Maya & Karoll Gómez, 2008. "What Exactly is "Bad News" in Foreign Exchange Markets? Evidence from Latin American Markets," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 45(132), pages 161-183.
    17. Narayan, Paresh Kumar & Mishra, Sagarika & Narayan, Seema & Thuraisamy, Kannan, 2015. "Is Exchange Rate Trading Profitable?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 217-229.
    18. Stephan Schulmeister, 2007. "Performance of Technical Trading Systems in the Yen/Dollar Market," WIFO Working Papers 291, WIFO.
    19. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.

  17. Ramazan GenÁay & Giuseppe Ballocchi & Michel Dacorogna & Richard Olsen & Olivier Pictet, 2002. "Real-Time Trading Models and the Statistical Properties of Foreign Exchange Rates," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(2), pages 463-492, May.

    Cited by:

    1. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    2. Mobeen Ur Rehman, 2020. "Dynamic correlation pattern amongst alternative energy market for diversification opportunities," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-24, December.
    3. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    4. Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank.
    5. Stephan Schulmeister, 2005. "The Interaction between Technical Currency Trading and Exchange Rate Fluctuations," Finance 0512033, University Library of Munich, Germany.
    6. Rehman, Mobeen Ur & Kang, Sang Hoon, 2021. "A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    7. Nour Meddahi & Eric Renault, 2000. "Temporal Aggregation of Volatility Models," CIRANO Working Papers 2000s-22, CIRANO.
    8. Jiali Fang & Ben Jacobsen & Yafeng Qin, 2014. "Predictability of the simple technical trading rules: An out‐of‐sample test," Review of Financial Economics, John Wiley & Sons, vol. 23(1), pages 30-45, January.
    9. Zhao, Xin & Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Vasa, László & Shahzad, Umer, 2023. "Interoperability of the revolutionary blockchain architectures and Islamic and conventional technology markets: Case of Metaverse, HPB, and Bloknet," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 112-131.
    10. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    11. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    12. 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.
    13. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    14. Neely, C. J. & Weller, P. A., 2003. "Intraday technical trading in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 22(2), pages 223-237, April.
    15. Ronald J. Balvers & Yangru Wu, 2005. "Optimal Transaction Filters Under Transitory Trading Opportunities: Theory and Empirical Illustration," Working Papers 022005, Hong Kong Institute for Monetary Research.
    16. Wright, Calvin & Swidler, Steve, 2023. "Abnormal trading volume, news and market efficiency: Evidence from the Jamaica Stock Exchange," Research in International Business and Finance, Elsevier, vol. 64(C).
    17. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    18. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    19. Kang, Sang Hoon & Uddin, Gazi Salah & Ahmed, Ali & Yoon, Seong-Min, 2018. "Multi-scale causality and extreme tail inter-dependence among housing prices," Economic Modelling, Elsevier, vol. 70(C), pages 301-309.
    20. Yacine Ait-Sahalia & Jialin Yu, 2009. "High frequency market microstructure noise estimates and liquidity measures," Papers 0906.1444, arXiv.org.
    21. Zhang, Zhanren & Karimi, Mohammad Sharif & Weerasinghe, Naveen Mahasen & Bilan, Yuriy & Shahzad, U., 2024. "Interplay between economic progress, carbon emissions and energy prices on green energy adoption: Evidence from USA and Germany in context of sustainability," Renewable Energy, Elsevier, vol. 232(C).
    22. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
    23. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    24. Narayan, Paresh Kumar & Mishra, Sagarika & Narayan, Seema & Thuraisamy, Kannan, 2015. "Is Exchange Rate Trading Profitable?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 217-229.

  18. Ballocchi Giuseppe & Dacorogna Michael & Gençay Ramazan & Piccinato Barbara, 2001. "Time-to-Expiry Seasonalities in Eurofutures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(4), pages 1-6, January.

    Cited by:

    1. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.

  19. M. Dacorogna & U. Mller & R. Olsen & O. Pictet, 2001. "Defining efficiency in heterogeneous markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 198-201.

    Cited by:

    1. T. Di Matteo & T. Aste & Michel M. Dacorogna, 2004. "Using the Scaling Analysis to Characterize Financial Markets," Finance 0402014, University Library of Munich, Germany.
    2. Chin Wen Cheong, 2010. "Estimating the Hurst parameter in financial time series via heuristic approaches," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(2), pages 201-214.
    3. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    4. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    5. Chin Wen CHEONG & Lee Min CHERNG & Grace Lee Ching YAP, 2016. "Heterogeneous Market Hypothesis Evaluations using Various Jump-Robust Realized Volatility," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 50-64, December.
    6. Cheong, Chin Wen, 2008. "Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 889-898.
    7. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    8. Yang, Ann Shawing & Pangastuti, Airin, 2016. "Stock market efficiency and liquidity: The Indonesia Stock Exchange merger," Research in International Business and Finance, Elsevier, vol. 36(C), pages 28-40.
    9. Jiao, Jing-Wen & Yin, Jun-Ping & Xu, Ping-Feng & Zhang, Juan & Liu, Yuan, 2023. "Transmission mechanisms of geopolitical risks to the crude oil market——A pioneering two-stage geopolitical risk analysis approach," Energy, Elsevier, vol. 283(C).
    10. BEN ABDALLAH Mohamed & TALBI Omar, 2024. "A Wavelet Analysis of Bitcoin Price Volatility Dynamic," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(1), pages 951-964, January.
    11. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does Shariah index hedge against sentiment risk? Evidence from Indian stock market using time–frequency domain approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 20-35.
    12. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
    13. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    14. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).

  20. Fulvio Corsi & Gilles Zumbach & Ulrich A. Muller & Michel M. Dacorogna, 2001. "Consistent High-precision Volatility from High-frequency Data," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 183-204, July.
    See citations under working paper version above.
  21. Dacorogna, Michel M. & Gençay, Ramazan & Müller, Ulrich A. & Pictet, Olivier V., 2001. "Effective return, risk aversion and drawdowns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 229-248.

    Cited by:

    1. GIOT, Pierre & PETITJEAN, Mikael, 2006. "International stock return predictability: statistical evidence and economic significance," LIDAM Discussion Papers CORE 2006088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Tavakoli Baghdadabad, Mohammad Reza, 2014. "Average drawdown risk reduction and risk tolerances," Research in Economics, Elsevier, vol. 68(3), pages 264-276.
    3. Christopher J. Neely, 2001. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," Working Papers 1999-015, Federal Reserve Bank of St. Louis.
    4. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    5. Heidorn, Thomas & Siragusano, Tindaro, 2004. "Die Anwendbarkeit der Behavioral Finance im Devisenmarkt," Frankfurt School - Working Paper Series 52, Frankfurt School of Finance and Management.
    6. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.
    7. 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.
    8. Dong, Yang & Wen, Shu-hui & Hu, Xiao-bing & Li, Jiang-Cheng, 2020. "Stochastic resonance of drawdown risk in energy market prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    9. Andrew Clark, 2005. "The use of Hurst and effective return in investing," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 1-8.
    10. Pierre Giot & Mikael Petitjean, 2011. "On the statistical and economic performance of stock return predictive regression models: an international perspective," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 175-193.
    11. Xufre Casqueiro, Patricia & Rodrigues, Antonio J.L., 2006. "Neuro-dynamic trading methods," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1400-1412, December.

  22. H. A. Hauksson & M. Dacorogna & T. Domenig & U. Mller & G. Samorodnitsky, 2001. "Multivariate extremes, aggregation and risk estimation," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 79-95.
    See citations under working paper version above.
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  24. Ballocchi, Giuseppe & Dacorogna, Michel M. & Hopman, Carl M. & Muller, Ulrich A. & Olsen, Richard B., 1999. "The intraday multivariate structure of the Eurofutures markets," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 479-513, December.

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    4. Tiziana Di Matteo & Tomaso Aste, 2002. "How Does The Eurodollar Interest Rate Behave?," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 107-122.
    5. Svitlana Vyetrenko & David Byrd & Nick Petosa & Mahmoud Mahfouz & Danial Dervovic & Manuela Veloso & Tucker Hybinette Balch, 2019. "Get Real: Realism Metrics for Robust Limit Order Book Market Simulations," Papers 1912.04941, arXiv.org.
    6. Hamza Bodor & Laurent Carlier, 2024. "Stylized Facts and Market Microstructure: An In-Depth Exploration of German Bond Futures Market," Papers 2401.10722, arXiv.org.
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    1. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
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    3. Xue-Zhong He, 2003. "Asset Pricing, Volatility and Market Behaviour: A Market Fraction Approach," Research Paper Series 95, Quantitative Finance Research Centre, University of Technology, Sydney.
    4. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    5. Xue-Zhong He & Youwei Li, 2005. "Long Memory, Heterogeneity and Trend Chasing," Research Paper Series 148, Quantitative Finance Research Centre, University of Technology, Sydney.
    6. Christian Peretti, 2007. "Long Memory and Hysteresis," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 363-389, Springer.
    7. Sarantis, Nicholas, 2001. "Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence," International Journal of Forecasting, Elsevier, vol. 17(3), pages 459-482.
    8. Nishiwaki, Takashi, 2022. "Impact of different investment horizons in heterogeneous agent models: Do long-term traders bring market stability?," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 393-401.
    9. Xue-Zhong He & Youwei Li, 2008. "Heterogeneity, convergence, and autocorrelations," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 59-79.
    10. Carl Chiarella & Xue-Zhong He & Duo Wang, 2004. "Statistical Properties of a Heterogeneous Asset Price Model with Time-Varying Second Moment," Research Paper Series 142, Quantitative Finance Research Centre, University of Technology, Sydney.
    11. He, Xue-Zhong & Li, Youwei, 2007. "Power-law behaviour, heterogeneity, and trend chasing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3396-3426, October.
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    17. Gencay, Ramazan & Dacorogna, Michel & Olsen, Richard & Pictet, Olivier, 2003. "Foreign exchange trading models and market behavior," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 909-935, April.
    18. Youwei Li & Xue-Zhong (Tony) He, 2005. "Heterogeneity, Profitability and Autocorrelations," Computing in Economics and Finance 2005 244, Society for Computational Economics.
    19. Brock, W.A. & Hommes, C.H., 1997. "Models of Compelxity in Economics and Finance," Working papers 9706, Wisconsin Madison - Social Systems.
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    21. Hommes, C.H., 2005. "Heterogeneous Agents Models: two simple examples, forthcoming In: Lines, M. (ed.) Nonlinear Dynamical Systems in Economics, CISM Courses and Lectures, Springer, 2005, pp.131-164," CeNDEF Working Papers 05-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    22. Takashi Nishiwaki, "undated". "On the Stability of Equilibrium in the Market with Heterogeneous Investment Horizons," Working Papers 2101, Waseda University, Faculty of Political Science and Economics.
    23. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
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    26. Catherine Kyrtsou & Walter C. Labys & Michel Terraza, 2004. "Noisy chaotic dynamics in commodity markets," Empirical Economics, Springer, vol. 29(3), pages 489-502, September.

  28. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.

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    7. Eleftherios Giovanis, 2014. "The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(3), pages 43-61, December.
    8. Torben G. Anderson & Tim Bollerslev & Ashish Das, 1998. "Testing for Market Microstructure Effects in Intraday Volatility: A Reassessment of the Tokyo FX Experiment," NBER Working Papers 6666, National Bureau of Economic Research, Inc.
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Books

  1. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.

    Cited by:

    1. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
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    8. 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.
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    10. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
    11. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does sentiment matter for stock returns? Evidence from Indian stock market using wavelet approach," Finance Research Letters, Elsevier, vol. 26(C), pages 32-39.
    12. Bottazzi, Giulio & Devetag, Giovanna & Pancotto, Francesca, 2011. "Does volatility matter? Expectations of price return and variability in an asset pricing experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 77(2), pages 124-146, February.
    13. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    14. Sarkar, A. & Barat, P., 2006. "Scaling analysis on Indian foreign exchange market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 362-368.
    15. Beine, Michel & Laurent, Sébastien & Palm, Franz C., 2009. "Central bank FOREX interventions assessed using realized moments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 112-127, February.
    16. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
    17. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    18. Marcel Brautigam & Michel Dacorogna & Marie Kratz, 2019. "Pro-Cyclicality of Traditional Risk Measurements: Quantifying and Highlighting Factors at its Source," Papers 1903.03969, arXiv.org, revised Dec 2019.
    19. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    20. Xin Huang & Hao Zhou & Haibin Zhu, 2009. "A Framework for Assessing the Systemic Risk of Major Financial Institutions," BIS Working Papers 281, Bank for International Settlements.
    21. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    22. Juan Carlos Ruilova & Pedro Alberto Morettin, 2020. "Parsimonious Heterogeneous ARCH Models for High Frequency Modeling," JRFM, MDPI, vol. 13(2), pages 1-19, February.
    23. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    24. Sabrina Camargo & Silvio M. Duarte Queiros & Celia Anteneodo, 2013. "Bridging stylized facts in finance and data non-stationarities," Papers 1302.3197, arXiv.org, revised May 2013.
    25. Niels S. Grønborg & Asger Lunde & Kasper V. Olesen & Harry Vander Elst, 2018. "Realizing Correlations Across Asset Classes," CREATES Research Papers 2018-37, Department of Economics and Business Economics, Aarhus University.
    26. Y. Kahiri & A. Shmilovici & S. Hauser, 2006. "Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm," Computing in Economics and Finance 2006 256, Society for Computational Economics.
    27. Dilip Kumar, 2016. "Sudden changes in crude oil price volatility: an application of extreme value volatility estimator," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(3/4), pages 215-234.
    28. Lallouache, Mehdi & Abergel, Frédéric, 2014. "Tick size reduction and price clustering in a FX order book," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 488-498.
    29. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    30. Manfred Gilli & Enrico Schumann, 2012. "Heuristic optimisation in financial modelling," Annals of Operations Research, Springer, vol. 193(1), pages 129-158, March.
    31. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.
    32. Aviral Tiwari & Niyati Bhanja & Arif Dar & Faridul Islam, 2015. "Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets," Empirical Economics, Springer, vol. 48(2), pages 699-714, March.
    33. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    34. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    35. Marc Simpson & Jose Moreno & Teofilo Ozuna, 2012. "The makings of an information leader: the intraday price discovery process for individual stocks in the DJIA," Review of Quantitative Finance and Accounting, Springer, vol. 38(3), pages 347-365, April.
    36. Bottazzi, G. & Sapio, S. & Secchi, A., 2005. "Some statistical investigations on the nature and dynamics of electricity prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 54-61.
    37. David Mcmillan & Alan Speight, 2008. "Long-memory in high-frequency exchange rate volatility under temporal aggregation," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 251-261.
    38. Enrico Scalas & Rudolf Gorenflo & Francesco Mainardi & Maurizio Mantelli & Marco Raberto, 2003. "Anomalous waiting times in high-frequency financial data," Papers cond-mat/0310305, arXiv.org.
    39. Li, Jiang-Cheng & Long, Chao & Chen, Xiao-Dan, 2015. "The returns and risks of investment portfolio in stock market crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 282-288.
    40. Dufour, Jean-Marie & García, René, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    41. Jin, Xiaoye, 2017. "Time-varying return-volatility relation in international stock markets," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 157-173.
    42. Carlo Rosa, 2012. "How "unconventional" are large-scale asset purchases? The impact of monetary policy on asset prices," Staff Reports 560, Federal Reserve Bank of New York.
    43. Yoshiro Tsutsui & Kenjiro Hirayama, 2008. "How Fast Do Tokyo and New York Stock Exchanges Respond to Each Other?: An Analysis with High-Frequency Data," Discussion Papers in Economics and Business 08-32, Osaka University, Graduate School of Economics.
    44. Bertram, William K., 2005. "A threshold model for Australian Stock Exchange equities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 561-576.
    45. Enrico Scalas, 2006. "Five Years of Continuous-time Random Walks in Econophysics," Lecture Notes in Economics and Mathematical Systems, in: Akira Namatame & Taisei Kaizouji & Yuuji Aruka (ed.), The Complex Networks of Economic Interactions, pages 3-16, Springer.
    46. Damien Challet & Robin Stinchcombe, 2003. "Non-constant rates and over-diffusive prices in a simple model of limit order markets," Quantitative Finance, Taylor & Francis Journals, vol. 3(3), pages 155-162.
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