Document Type

Discussion Paper

Publication Date

11-1-2018

CFDP Number

2152

CFDP Pages

24

Journal of Economic Literature (JEL) Code(s)

C12, C14

Abstract

While each financial crisis has its own characteristics, there is now widespread recognition that crises arising from sources such as financial speculation and excessive credit creation do inflict harm on the real economy. Detecting speculative market conditions and ballooning credit risk in real time is therefore of prime importance in the complex exercises of market surveillance, risk management, and policy action. This chapter provides an R implementation of the popular real-time monitoring strategy proposed by Phillips, Shi and Yu in the International Economic Review (2015), along with a new bootstrap procedure designed to mitigate the potential impact of heteroskedasticity and to effect family-wise size control in recursive testing algorithms. This methodology has been shown effective for bubble and crisis detection and is now widely used by academic researchers, central bank economists, and fiscal regulators. We illustrate the effectiveness of this procedure with applications to the S&P financial market and the European sovereign debt sector using the psymonitor R package developed in conjunction with this chapter.

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