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The impact of long-range dependence in the capital stock on interest rate and wealth distribution

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  • Calisse, Frank

Abstract

Macroeconomic modeling in the context of a stochastic continuous-time environment has become more popular in recent years. Most of these models are based on stochastic differential equations to describe macroeconomic dynamics and stochastic uncertainty is mostly modeled by Brownian motions or Poisson processes. However, these assumptions neglect the statistical evidence of long-range dependence in macroeconomic time series such as inflation rates, GDP, unemployment rates and interest rates. Based on Brunnermeier and Sannikov's contribution to the Handbook of Macroeconomics 2016, we present a small and quite simple model where the uncertainty is modeled by an approximated Liouville fractional Brownian motion. With this approach we are able to consider the effects of correlated shocks as well as the impact of long-range dependence in capital stock on the rate of interest and the distribution of wealth.

Suggested Citation

  • Calisse, Frank, 2019. "The impact of long-range dependence in the capital stock on interest rate and wealth distribution," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203591, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc19:203591
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    1. Sottinen Tommi & Valkeila Esko, 2003. "On arbitrage and replication in the fractional Black–Scholes pricing model," Statistics & Risk Modeling, De Gruyter, vol. 21(2), pages 93-108, February.
    2. Basak, Suleyman & Cuoco, Domenico, 1998. "An Equilibrium Model with Restricted Stock Market Participation," The Review of Financial Studies, Society for Financial Studies, vol. 11(2), pages 309-341.
    3. Tarasov, Vasily E. & Tarasova, Valentina V., 2018. "Macroeconomic models with long dynamic memory: Fractional calculus approach," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 466-486.
    4. Wang, Xiao-Tian, 2010. "Scaling and long-range dependence in option pricing I: Pricing European option with transaction costs under the fractional Black–Scholes model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 438-444.
    5. Brunnermeier, M.K. & Sannikov, Y., 2016. "Macro, Money, and Finance," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1497-1545, Elsevier.
    6. Nataliya Klimenko & Sebastian Pfeil & Jean-Charles Rochet & Gianni De Nicolo, 2016. "Aggregate Bank Capital and Credit Dynamics," Swiss Finance Institute Research Paper Series 16-42, Swiss Finance Institute.
    7. Guglielmo Caporale & Luis Gil-Alana, 2013. "Long memory in US real output per capita," Empirical Economics, Springer, vol. 44(2), pages 591-611, April.
    8. Tomas Björk & Henrik Hult, 2005. "A note on Wick products and the fractional Black-Scholes model," Finance and Stochastics, Springer, vol. 9(2), pages 197-209, April.
    9. Guglielmo Maria Caporale & Marinko Skare, 2014. "Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis," Discussion Papers of DIW Berlin 1395, DIW Berlin, German Institute for Economic Research.
    10. Xiao, Wei-Lin & Zhang, Wei-Guo & Zhang, Xi-Li & Wang, Ying-Luo, 2010. "Pricing currency options in a fractional Brownian motion with jumps," Economic Modelling, Elsevier, vol. 27(5), pages 935-942, September.
    11. L. C. G. Rogers, 1997. "Arbitrage with Fractional Brownian Motion," Mathematical Finance, Wiley Blackwell, vol. 7(1), pages 95-105, January.
    12. Cipian Necula, 2008. "Option Pricing in a Fractional Brownian Motion Environment," Advances in Economic and Financial Research - DOFIN Working Paper Series 2, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    13. Paolo Guasoni, 2006. "No Arbitrage Under Transaction Costs, With Fractional Brownian Motion And Beyond," Mathematical Finance, Wiley Blackwell, vol. 16(3), pages 569-582, July.
    14. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    15. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    16. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    17. Emmanuel Haven & Philip Molyneux & John O. S. Wilson & Sergei Fedotov & Meryem Duygun (ed.), 2016. "The Handbook of Post Crisis Financial Modeling," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-49449-8.
    18. Rostek, S. & Schöbel, R., 2013. "A note on the use of fractional Brownian motion for financial modeling," Economic Modelling, Elsevier, vol. 30(C), pages 30-35.
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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G00 - Financial Economics - - General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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