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LPPLS Bubble Indicators over Two Centuries of the S&P 500 Index

Author

Listed:
  • Qunzhi Zhang

    (ETH Zurich, Department of Management, Technology and Economics (D-MTEC))

  • Didier Sornette

    (ETH Zurich, Department of Management, Technology and Economics ; Swiss Finance Institute, c/o University of Geneva, Switzerland)

  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Turkey ; Department of Economics, University of Pretoria, South Africa ; and IPAG Business School, Paris France)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Zeynel A. Ozdemir

    (Department of Economics, Gazi University, Turkey; and Economic Research Forum (ERF), Cairo)

  • Hakan Yetkiner

    (Department of Economics, Izmir University of Economics, Turkey)

Abstract

The aim of this paper is to present novel tests for the early causal diagnostic of positive and negative bubbles in the S&P 500 index and the detection of End-of-Bubble signals with their corresponding confidence levels. We use monthly S&P 500 data covering the period from August 1791 to August 2014. This study is the first work in the literature showing the possibility to develop reliable ex-ante diagnostics of the frequent regime shifts over two centuries of data. We show that the DS LPPLS (log-periodic power law singularity) approach successfully diagnoses positive and negative bubbles, constructs efficient End-of-Bubble signals for all of the well-documented bubbles, and obtains for the first time new statistical evidence of bubbles for some other events. We also compare the DS LPPLS method to the exponential curve fitting and the generalized sup ADF test approaches and find that DS LPPLS system is more accurate in identifying well-known bubble events, with significantly smaller numbers of false negatives and false positives.

Suggested Citation

  • Qunzhi Zhang & Didier Sornette & Mehmet Balcilar & Rangan Gupta & Zeynel A. Ozdemir & Hakan Yetkiner, 2016. "LPPLS Bubble Indicators over Two Centuries of the S&P 500 Index," Working Papers 201606, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201606
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    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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