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

32 Pages Posted: 5 Feb 2016

See all articles by Qunzhi Zhang

Qunzhi Zhang

ETH Zürich

Didier Sornette

ETH Zürich - Department of Management, Technology, and Economics (D-MTEC); Swiss Finance Institute

Mehmet Balcilar

Eastern Mediterranean University

Rangan Gupta

University of Pretoria - Department of Economics

Zeynel Abidin Ozdemir

IZA Institute of Labor Economics; Economic Research Forum (ERF)

Hakan Yetkiner

Izmir University of Economics

Date Written: February 2, 2016

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.

Keywords: S&P 500, LPPL method, stock market bubble, forecast, bubble indicators

JEL Classification: J16, O47, C32

Suggested Citation

Zhang, Qunzhi and Sornette, Didier and Balcilar, Mehmet and Gupta, Rangan and Ozdemir, Zeynel Abidin and Yetkiner, I. Hakan, LPPLS Bubble Indicators over Two Centuries of the S&P 500 Index (February 2, 2016). Swiss Finance Institute Research Paper No. 16-05, Available at SSRN: https://ssrn.com/abstract=2727755 or http://dx.doi.org/10.2139/ssrn.2727755

Qunzhi Zhang

ETH Zürich ( email )

Rämistrasse 101
ZUE F7
Zürich, 8092
Switzerland

Didier Sornette (Contact Author)

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

Scheuchzerstrasse 7
Zurich, ZURICH CH-8092
Switzerland
41446328917 (Phone)
41446321914 (Fax)

HOME PAGE: http://www.er.ethz.ch/

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Mehmet Balcilar

Eastern Mediterranean University ( email )

Gazimagusa
Turkey

HOME PAGE: http://www.mbalcilar.net

Rangan Gupta

University of Pretoria - Department of Economics ( email )

Lynnwood Road
Hillcrest
Pretoria, 0002
South Africa

Zeynel Abidin Ozdemir

IZA Institute of Labor Economics ( email )

P.O. Box 7240
Bonn, D-53072
Germany

Economic Research Forum (ERF) ( email )

21 Al-Sad Al-Aaly St.
(P.O. Box: 12311)
Dokki, Cairo
Egypt

I. Hakan Yetkiner

Izmir University of Economics ( email )

Sakarya Cad. No. 156
Balcova
Izmir, 35350
Turkey

HOME PAGE: http://www.hakanyetkiner.com/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
547
Abstract Views
2,178
rank
54,197
PlumX Metrics