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Sergio Bianchi

Personal Details

First Name:Sergio
Middle Name:
Last Name:Bianchi
Suffix:
RePEc Short-ID:pbi426
[This author has chosen not to make the email address public]
https://web.uniroma1.it/memotef/en/users/bianchi-sergio
Terminal Degree:1991 Facoltà di Economia; "Sapienza" Università di Roma (from RePEc Genealogy)

Affiliation

Dipartimento di Metodi e modelli per l'economia, il territorio e la finanza (MEMOTEF)
Facoltà di Economia
"Sapienza" Università di Roma

Roma, Italy
https://web.uniroma1.it/memotef/
RePEc:edi:dmrosit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Pierre Raphaël Bertrand & Jean-Louis Combes & Marie-Eliette Dury & Doha Hadouni & Sergio Bianchi, 2018. "Overfitting of Hurst estimators for multifractional Brownian motion: A fitting test advocating simple models," Post-Print hal-01816206, HAL.
  2. Bianchi, Sergio & Pantanella, Alexandre & Pianese, Augusto, 2009. "Financial Portfolio Selection in a Nonstationary Gaussian Framework," Papers 2009/49, Osterreichish-Rumanischer Akademischer Verein.
  3. Sergio, Bianchi & Alessandro, Trudda, 2008. "Global Asset Return in Pension Funds: a dynamical risk analysis," MPRA Paper 12011, University Library of Munich, Germany, revised 14 Jun 2008.
  4. Bianchi, Sergio, 2004. "A new distribution-based test of self-similarity," MPRA Paper 16640, University Library of Munich, Germany.
  5. Sergio Bianchi, 2001. "A Distribution-Based Method For Evaluating Multiscaling In Finance," CeNDEF Workshop Papers, January 2001 4A.3, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

Articles

  1. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
  2. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.
  3. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
  4. Pianese, Augusto & Attias, Anna & Bianchi, Sergio & Varga, Zoltàn, 2020. "On the asymptotic equilibrium of a population system with migration," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 115-127.
  5. Sergio Bianchi & Augusto Pianese & Massimiliano Frezza, 2020. "A distribution‐based method to gauge market liquidity through scale invariance between investment horizons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(5), pages 809-824, September.
  6. Bianchi, Sergio & Pianese, Augusto, 2018. "Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 64-75.
  7. Sergio Bianchi & Massimiliano Frezza, 2018. "Liquidity, Efficiency and the 2007-2008 Global Financial Crisis," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 375-404, November.
  8. Sergio Bianchi & Alexandre Pantanella & Augusto Pianese, 2015. "Efficient Markets And Behavioral Finance: A Comprehensive Multifractional Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 18(01n02), pages 1-29.
  9. Bianchi, Sergio & Pianese, Augusto, 2014. "Multifractional processes in finance," Risk and Decision Analysis, IOS Press, issue 5, pages 1-22.
  10. S. Bianchi & A. Pantanella & A. Pianese, 2013. "Modeling stock prices by multifractional Brownian motion: an improved estimation of the pointwise regularity," Quantitative Finance, Taylor & Francis Journals, vol. 13(8), pages 1317-1330, July.
  11. Sergio Bianchi & Iva De Bellis & Augusto Pianese, 2010. "Fractal properties of some European electricity markets," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 1(4), pages 395-421.
  12. S. Bianchi & A. Pianese, 2008. "Multifractional Properties Of Stock Indices Decomposed By Filtering Their Pointwise Hölder Regularity," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 567-595.
  13. Sergio Bianchi & Augusto Pianese, 2007. "Modelling stock price movements: multifractality or multifractionality?," Quantitative Finance, Taylor & Francis Journals, vol. 7(3), pages 301-319.
  14. Sergio Bianchi, 2005. "A cautionary note on the detection of multifractal scaling in finance and economics," Applied Economics Letters, Taylor & Francis Journals, vol. 12(12), pages 775-780.
  15. Sergio Bianchi, 2005. "Pathwise Identification Of The Memory Function Of Multifractional Brownian Motion With Application To Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 255-281.

Chapters

  1. Sergio Bianchi & Augusto Pianese & Massimiliano Frezza & Anna Maria Palazzo, 2021. "Stochastic Dominance in the Outer Distributions of the $$\alpha $$ α -Efficiency Domain," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 95-101, Springer.
  2. Sergio Bianchi & Augusto Pianese, 2015. "Asset Price Modeling: From Fractional to Multifractional Processes," International Series in Operations Research & Management Science, in: Alain Bensoussan & Dominique Guegan & Charles S. Tapiero (ed.), Future Perspectives in Risk Models and Finance, edition 127, pages 247-285, Springer.
  3. Sergio Bianchi & Augusto Pianese, 2008. "Scaling Laws in Stock Markets. An Analysis of Prices and Volumes," Springer Books, in: Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods in Insurance and Finance, pages 35-42, Springer.

Citations

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

Working papers

  1. Pierre Raphaël Bertrand & Jean-Louis Combes & Marie-Eliette Dury & Doha Hadouni & Sergio Bianchi, 2018. "Overfitting of Hurst estimators for multifractional Brownian motion: A fitting test advocating simple models," Post-Print hal-01816206, HAL.

    Cited by:

    1. Matthieu Garcin, 2019. "Fractal analysis of the multifractality of foreign exchange rates [Analyse fractale de la multifractalité des taux de change]," Working Papers hal-02283915, HAL.
    2. Pierre R. Bertrand & Marie-Eliette Dury & Bing Xiao, 2020. "A study of Chinese market efficiency, Shanghai versus Shenzhen: Evidence based on multifractional models," Post-Print hal-03031766, HAL.
    3. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.

  2. Sergio, Bianchi & Alessandro, Trudda, 2008. "Global Asset Return in Pension Funds: a dynamical risk analysis," MPRA Paper 12011, University Library of Munich, Germany, revised 14 Jun 2008.

    Cited by:

    1. Cadoni, Marinella & Melis, Roberta & Trudda, Alessandro, 2017. "Pension funds rules: Paradoxes in risk control," Finance Research Letters, Elsevier, vol. 22(C), pages 20-29.
    2. Marinella Cadoni & Roberta Melis & Alessandro Trudda, 2015. "Financial Crisis: A New Measure for Risk of Pension Fund Portfolios," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-12, June.
    3. M. Cadoni & R. Melis & A. Trudda, 2012. "Financial crisis: a new measure for risk of pension funds assets," Working Paper CRENoS 201231, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

  3. Bianchi, Sergio, 2004. "A new distribution-based test of self-similarity," MPRA Paper 16640, University Library of Munich, Germany.

    Cited by:

    1. Myoungji Lee & Marc G. Genton & Mikyoung Jun, 2016. "Testing Self-Similarity Through Lamperti Transformations," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 426-447, September.
    2. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.
    3. Sergio Bianchi & Augusto Pianese & Massimiliano Frezza, 2020. "A distribution‐based method to gauge market liquidity through scale invariance between investment horizons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(5), pages 809-824, September.
    4. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

Articles

  1. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

    Cited by:

    1. Daniele Angelini & Matthieu Garcin, 2024. "Market information of the fractional stochastic regularity model," Papers 2409.07159, arXiv.org.
    2. Li, Yicun & Teng, Yuanyang, 2023. "Statistical inference in discretely observed fractional Ornstein–Uhlenbeck processes," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

  2. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).

    Cited by:

    1. Gaio, Luiz Eduardo & Stefanelli, Nelson Oliveira & Pimenta, Tabajara & Bonacim, Carlos Alberto Grespan & Gatsios, Rafael Confetti, 2022. "The impact of the Russia-Ukraine conflict on market efficiency: Evidence for the developed stock market," Finance Research Letters, Elsevier, vol. 50(C).
    2. Kakinaka, Shinji & Umeno, Ken, 2022. "Cryptocurrency market efficiency in short- and long-term horizons during COVID-19: An asymmetric multifractal analysis approach," Finance Research Letters, Elsevier, vol. 46(PA).
    3. Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    4. Papathanasiou, Spyros & Dokas, Ioannis & Koutsokostas, Drosos, 2022. "Value investing versus other investment strategies: A volatility spillover approach and portfolio hedging strategies for investors," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    5. Long, Shaobo & Zhang, Rui & Hao, Jing, 2022. "Asymmetric impact of Sino-US interest rate differentials and economic policy uncertainty ratio on RMB exchange rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    6. Vuong, Giang Thi Huong & Nguyen, Manh Huu & Huynh, Anh Ngoc Quang, 2022. "Volatility spillovers from the Chinese stock market to the U.S. stock market: The role of the COVID-19 pandemic," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    7. Mohsen Soltanifar, 2022. "The Second Generalization of the Hausdorff Dimension Theorem for Random Fractals," Mathematics, MDPI, vol. 10(5), pages 1-11, February.
    8. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Alam, Masud & Abedin, Mohammad Zoynul & Shi, Baofeng, 2023. "NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis," International Review of Financial Analysis, Elsevier, vol. 87(C).
    9. Xie, Jun & Fang, Yuying & Gao, Bin & Tan, Chunzhi, 2023. "Availability heuristic and expected returns," Finance Research Letters, Elsevier, vol. 51(C).
    10. Navratil, Robert & Taylor, Stephen & Vecer, Jan, 2021. "On equity market inefficiency during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 77(C).
    11. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).

  3. Sergio Bianchi & Augusto Pianese & Massimiliano Frezza, 2020. "A distribution‐based method to gauge market liquidity through scale invariance between investment horizons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(5), pages 809-824, September.

    Cited by:

    1. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).

  4. Bianchi, Sergio & Pianese, Augusto, 2018. "Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 64-75.

    Cited by:

    1. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Working Papers hal-03230167, HAL.
    2. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Papers 2105.09140, arXiv.org, revised Sep 2021.
    3. Brouty, Xavier & Garcin, Matthieu, 2024. "Fractal properties, information theory, and market efficiency," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).

  5. Sergio Bianchi & Alexandre Pantanella & Augusto Pianese, 2015. "Efficient Markets And Behavioral Finance: A Comprehensive Multifractional Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 18(01n02), pages 1-29.

    Cited by:

    1. Sergio Bianchi & Massimiliano Frezza, 2018. "Liquidity, Efficiency and the 2007-2008 Global Financial Crisis," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 375-404, November.
    2. Matthieu Garcin, 2019. "Fractal analysis of the multifractality of foreign exchange rates [Analyse fractale de la multifractalité des taux de change]," Working Papers hal-02283915, HAL.
    3. Pierre R. Bertrand & Marie-Eliette Dury & Bing Xiao, 2020. "A study of Chinese market efficiency, Shanghai versus Shenzhen: Evidence based on multifractional models," Post-Print hal-03031766, HAL.
    4. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    5. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.

  6. Bianchi, Sergio & Pianese, Augusto, 2014. "Multifractional processes in finance," Risk and Decision Analysis, IOS Press, issue 5, pages 1-22.

    Cited by:

    1. Sergio Bianchi & Massimiliano Frezza, 2018. "Liquidity, Efficiency and the 2007-2008 Global Financial Crisis," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 375-404, November.
    2. Sergio Bianchi & Augusto Pianese & Massimiliano Frezza, 2020. "A distribution‐based method to gauge market liquidity through scale invariance between investment horizons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(5), pages 809-824, September.
    3. Paolo Angelis & Roberto Marchis & Mario Marino & Antonio Luciano Martire & Immacolata Oliva, 2021. "Betting on bitcoin: a profitable trading between directional and shielding strategies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 883-903, December.
    4. Ayache, Antoine & Bouly, Florent, 2022. "Moving average Multifractional Processes with Random Exponent: Lower bounds for local oscillations," Stochastic Processes and their Applications, Elsevier, vol. 146(C), pages 143-163.
    5. Marinella Cadoni & Roberta Melis & Alessandro Trudda, 2015. "Financial Crisis: A New Measure for Risk of Pension Fund Portfolios," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-12, June.
    6. 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.
    7. Bianchi, Sergio & Pianese, Augusto, 2018. "Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 64-75.
    8. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.

  7. S. Bianchi & A. Pantanella & A. Pianese, 2013. "Modeling stock prices by multifractional Brownian motion: an improved estimation of the pointwise regularity," Quantitative Finance, Taylor & Francis Journals, vol. 13(8), pages 1317-1330, July.

    Cited by:

    1. Axel A. Araneda, 2023. "A multifractional option pricing formula," Papers 2303.16314, arXiv.org, revised Jun 2024.
    2. 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.
    3. Sergio Bianchi & Massimiliano Frezza, 2018. "Liquidity, Efficiency and the 2007-2008 Global Financial Crisis," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 375-404, November.
    4. Bernd Hayo & Britta Niehof, 2014. "Monetary and Fiscal Policy in Times of Crises: A New Keynesian Perspective in Continuous Time," MAGKS Papers on Economics 201455, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.
    6. Rosella Castellano & Roy Cerqueti & Giulia Rotundo, 2020. "Exploring the financial risk of a temperature index: a fractional integrated approach," Annals of Operations Research, Springer, vol. 284(1), pages 225-242, January.
    7. Sergio Bianchi & Augusto Pianese & Massimiliano Frezza, 2020. "A distribution‐based method to gauge market liquidity through scale invariance between investment horizons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(5), pages 809-824, September.
    8. Villena, Marcelo J. & Araneda, Axel A., 2024. "On sectoral market efficiency," Finance Research Letters, Elsevier, vol. 61(C).
    9. Ayache, Antoine & Bouly, Florent, 2022. "Moving average Multifractional Processes with Random Exponent: Lower bounds for local oscillations," Stochastic Processes and their Applications, Elsevier, vol. 146(C), pages 143-163.
    10. Sixian Jin & Qidi Peng & Henry Schellhorn, 2018. "Estimation of the pointwise Hölder exponent of hidden multifractional Brownian motion using wavelet coefficients," Statistical Inference for Stochastic Processes, Springer, vol. 21(1), pages 113-140, April.
    11. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    12. Tsai, Yi-Cheng & Lei, Chin-Laung & Cheung, William & Wu, Chung-Shu & Ho, Jan-Ming & Wang, Chuan-Ju, 2018. "Exploring the Persistent Behavior of Financial Markets," Finance Research Letters, Elsevier, vol. 24(C), pages 199-220.
    13. Peng, Qidi & Zhao, Ran, 2018. "A general class of multifractional processes and stock price informativeness," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 248-267.
    14. 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.
    15. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
    16. Gerlich, Nikolas & Rostek, Stefan, 2015. "Estimating serial correlation and self-similarity in financial time series—A diversification approach with applications to high frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 84-98.
    17. Bianchi, Sergio & Pianese, Augusto, 2018. "Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 64-75.
    18. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.

  8. S. Bianchi & A. Pianese, 2008. "Multifractional Properties Of Stock Indices Decomposed By Filtering Their Pointwise Hölder Regularity," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 567-595.

    Cited by:

    1. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    2. Peng, Qidi & Zhao, Ran, 2018. "A general class of multifractional processes and stock price informativeness," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 248-267.
    3. Bianchi, Sergio & Pianese, Augusto, 2018. "Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 64-75.

  9. Sergio Bianchi & Augusto Pianese, 2007. "Modelling stock price movements: multifractality or multifractionality?," Quantitative Finance, Taylor & Francis Journals, vol. 7(3), pages 301-319.

    Cited by:

    1. 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.
    2. Tao, Qizhi & Wei, Yu & Liu, Jiapeng & Zhang, Ting, 2018. "Modeling and forecasting multifractal volatility established upon the heterogeneous market hypothesis," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 143-153.
    3. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey & Peter G. Szilagyi, 2013. "The structure of gold and silver spread returns," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 561-570, March.
    4. Frezza, Massimiliano, 2012. "Modeling the time-changing dependence in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(12), pages 1510-1520.
    5. Frezza, Massimiliano, 2014. "Goodness of fit assessment for a fractal model of stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 41-50.

  10. Sergio Bianchi, 2005. "A cautionary note on the detection of multifractal scaling in finance and economics," Applied Economics Letters, Taylor & Francis Journals, vol. 12(12), pages 775-780.

    Cited by:

    1. Frezza, Massimiliano, 2012. "Modeling the time-changing dependence in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(12), pages 1510-1520.
    2. Crepaldi, Antonio F. & Neto, Camilo Rodrigues & Ferreira, Fernando F. & Francisco, Gerson, 2009. "Multifractal regime transition in a modified minority game model," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1364-1371.

  11. Sergio Bianchi, 2005. "Pathwise Identification Of The Memory Function Of Multifractional Brownian Motion With Application To Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 255-281.

    Cited by:

    1. Axel A. Araneda, 2023. "A multifractional option pricing formula," Papers 2303.16314, arXiv.org, revised Jun 2024.
    2. Sergio Bianchi & Massimiliano Frezza, 2018. "Liquidity, Efficiency and the 2007-2008 Global Financial Crisis," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 375-404, November.
    3. Matthieu Garcin, 2019. "Hurst Exponents And Delampertized Fractional Brownian Motions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-26, August.
    4. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    5. Villena, Marcelo J. & Araneda, Axel A., 2024. "On sectoral market efficiency," Finance Research Letters, Elsevier, vol. 61(C).
    6. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    7. Erhan Bayraktar & Ulrich Horst & Ronnie Sircar, 2007. "Queueing Theoretic Approaches to Financial Price Fluctuations," Papers math/0703832, arXiv.org.
    8. Cadoni, Marinella & Melis, Roberta & Trudda, Alessandro, 2017. "Pension funds rules: Paradoxes in risk control," Finance Research Letters, Elsevier, vol. 22(C), pages 20-29.
    9. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    10. Sergio, Bianchi & Alessandro, Trudda, 2008. "Global Asset Return in Pension Funds: a dynamical risk analysis," MPRA Paper 12011, University Library of Munich, Germany, revised 14 Jun 2008.
    11. Marinella Cadoni & Roberta Melis & Alessandro Trudda, 2015. "Financial Crisis: A New Measure for Risk of Pension Fund Portfolios," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-12, June.
    12. Frezza, Massimiliano, 2012. "Modeling the time-changing dependence in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 45(12), pages 1510-1520.
    13. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    14. Frezza, Massimiliano, 2014. "Goodness of fit assessment for a fractal model of stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 41-50.
    15. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
    16. Bianchi, Sergio & Pianese, Augusto, 2018. "Time-varying Hurst–Hölder exponents and the dynamics of (in)efficiency in stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 64-75.
    17. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.
    18. M. Cadoni & R. Melis & A. Trudda, 2012. "Financial crisis: a new measure for risk of pension funds assets," Working Paper CRENoS 201231, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

Chapters

  1. Sergio Bianchi & Augusto Pianese, 2015. "Asset Price Modeling: From Fractional to Multifractional Processes," International Series in Operations Research & Management Science, in: Alain Bensoussan & Dominique Guegan & Charles S. Tapiero (ed.), Future Perspectives in Risk Models and Finance, edition 127, pages 247-285, Springer.

    Cited by:

    1. Axel A. Araneda, 2023. "A multifractional option pricing formula," Papers 2303.16314, arXiv.org, revised Jun 2024.
    2. Paolo Angelis & Roberto Marchis & Mario Marino & Antonio Luciano Martire & Immacolata Oliva, 2021. "Betting on bitcoin: a profitable trading between directional and shielding strategies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 883-903, December.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-RMG: Risk Management (2) 2009-04-13 2009-07-03

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