Brexit or Bremain? Evidence from Bubble Analysis

A version of this paper was published in Risk, 23 June 2016,

and in Proceedings of the 1st Workshop on MIning DAta for financial applicationS (MIDAS 2016), September 19-23, 2016, edited by I. Bordino, G. Caldarelli, F. Fumarola, F. Gullo, T. Squartin

10 Pages Posted: 23 Jun 2016 Last revised: 10 Sep 2018

See all articles by Marco Bianchetti

Marco Bianchetti

Intesa Sanpaolo - Financial and Market Risk Management; University of Bologna; AIFIRM - Associazione Italiana Financial Industry Risk Manager

Davide Galli

Dipartimento di Fisica, Università degli Studi di Milano

Camilla Ricci

Intesa Sanpaolo-Financial and Market Risk Management

Angelo Salvatori

Dipartimento di Fisica, Università degli Studi di Milano

Marco Scaringi

Intesa Sanpaolo - Financial and Market Risk Management

Date Written: June 20, 2016

Abstract

We applied the Johansen-Ledoit-Sornette (JLS) model to detect possible bubbles and crashes related to the Brexit/Bremain referendum scheduled for 23rd June 2016. Our implementation includes an enhanced model calibration using Genetic Algorithms. We selected a few historical financial series sensitive to the Brexit/Bremain scenario, representative of multiple asset classes.

We found that equity and currency asset classes show no bubble signals, while rates, credit and real estate show super-exponential behaviour and instabilities typical of bubble regime. Our study suggests that, under the JLS model, equity and currency markets do not expect crashes or sharp rises following the referendum results. Instead, rates and credit markets consider the referendum a risky event, expecting either a Bremain scenario or a Brexit scenario edulcorated by central banks intervention. In the case of real estate, a crash is expected, but its relationship with the referendum results is unclear.

Keywords: JLS, Johansen-Ledoit-Sornette, Bubble, Crash, Crisis, Brexit, Bremain, UK, UE, Referendum, Forecast, Polls, Odds, Historical Series, Super-Exponential, Log-Periodic Power Law, LPPL, Calibration, Genetic Algorithm, Fit

JEL Classification: C13, C32, C53, G1

Suggested Citation

Bianchetti, Marco and Galli, Davide and Ricci, Camilla and Salvatori, Angelo and Scaringi, Marco, Brexit or Bremain? Evidence from Bubble Analysis (June 20, 2016). A version of this paper was published in Risk, 23 June 2016, , and in Proceedings of the 1st Workshop on MIning DAta for financial applicationS (MIDAS 2016), September 19-23, 2016, edited by I. Bordino, G. Caldarelli, F. Fumarola, F. Gullo, T. Squartin, Available at SSRN: https://ssrn.com/abstract=2798434 or http://dx.doi.org/10.2139/ssrn.2798434

Marco Bianchetti (Contact Author)

Intesa Sanpaolo - Financial and Market Risk Management ( email )

Piazza P. Ferrari 10
Milan, 20121
Italy

University of Bologna ( email )

Piazza Scaravilli 2
Bologna, 40100
Italy

AIFIRM - Associazione Italiana Financial Industry Risk Manager ( email )

www.aifirm.it
Italy

Davide Galli

Dipartimento di Fisica, Università degli Studi di Milano ( email )

Via Celoria, 16
Milano, 20133
Italy

Camilla Ricci

Intesa Sanpaolo-Financial and Market Risk Management ( email )

Piazza P. Ferrari 10
P.O. BOX 8319
Milan, 20121
Italy

Angelo Salvatori

Dipartimento di Fisica, Università degli Studi di Milano ( email )

Via Celoria, 16
Milano, 20133
Italy

Marco Scaringi

Intesa Sanpaolo - Financial and Market Risk Management ( email )

Piazza P. Ferrari 10
Milan, 20121
Italy

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