Identifying Speculative Bubbles: A Two-Pillar Surveillance Framework

Abstract

In the aftermath of the global financial crisis, the issue of how best to identify speculative asset bubbles (in real-time) remains in flux. This owes to the difficulty of disentangling irrational investor exuberance from the rational response to lower risk based on price behavior alone. In response, I introduce a two-pillar (price and quantity) approach for financial market surveillance. The intuition is straightforward: while asset pricing models comprise a valuable component of the surveillance toolkit, risk taking behavior, and financial vulnerabilities more generally, can also be reflected in subtler, non-price terms. The framework appears to capture stylized facts of asset booms and busts-some of the largest in history have been associated with below average risk premia (captured by the 'pricing pillar') and unusually elevated patterns of issuance, trading volumes, fund flows, and survey-based return projections (reflected in the 'quantities pillar'). Based on a comparison to past boom-bust episodes, the approach is signaling mounting vulnerabilities in risky U.S. credit markets. Policy makers and regulators should be attune to any further deterioration in issuance quality, and where possible, take steps to ensure the post-crisis financial infrastructure is braced to accommodate a re-pricing in credit risk.

The efficacy of macroeconomic policies in resolving financial market disequilibria: A cross‐country analysis

“…10 This was primarily due to the fact that a common facet of the mandate of monetary authorities is to ensure price stability, which was thought to facilitate financial stability (Bernanke et al, 1999). 14 These results are consistent with the propositions of Jones (2014). Based on this premise, Hayford and Malliaris (2008) suggested that it is unlikely that monetary authorities will be able to increase interest rates only to prevent financial market dislocations.…”

“…In order to identify financial market disequilibria, credit spreads will be used as a proxy based on the propositions of Jones (2014) and Krishnamurthy and Muir (2015) as they capture the general equilibrium of multiple financial markets. Although credit spreads reflect the general equilibrium of financial markets, other proxies are also identified in literature.…”

“…A one-way ANOVA test will also be used to evaluate the notion of policy convergence, which is in line with Samuels and Shugart (2011). In order to create the dependent dummy variables, changes in credit spreads that are above or equal to 0.01 will be assigned the value of 1, and all others will be assigned the value of 0, as suggested by Jones (2014). Finally, a logit regression analyses will be conducted to elucidate the macroeconomic policies chosen by governments with various political orientations to redress financial market imbalances, which is in line with Song (2010).…”

“…To ensure that credit spreads are an appropriate proxy for imbalances in financial markets, a VAR analysis was conducted to examine the short-term relationship between credit spreads and the returns of key financial markets: stock, bond, foreign exchange, and oil markets (in line with Gilchrist & Zakrajšek, 2012). Furthermore, two lag lengths will be used on the basis of the suggestions of Jones (2014). A condition for this study is that there must be a relationship between credit spreads and the returns of at least one key market for each country in order for credit spreads to be used as a proxy.…”

“…The dependent dummy variables represent macroeconomic policies implemented during periods of financial market disequilibria. In order to create the dependent dummy variables, changes in credit spreads that are above or equal to 0.01 will be assigned the value of 1, and all others will be assigned the value of 0, as suggested by Jones (2014). This index will then be multiplied by government spending, liquidity provision, and central bank interest rates.…”