Testing for Explosive Behaviour in Relative Inflation Measures: Implications for Monetary Policy

In this paper we test for large deviations in headline measures of the price level relative to core measures using the recently proposed test of Phillips et al. (2011a). We find evidence of explosive behaviour in the headline price index of personal consumption expenditures (PCE) relative to the core PCE (less food and energy prices) on three occasions from 1982-2010. Two of these episodes correspond to energy supply shocks (OPEC price collapse of 1986 and Hurricane Katrina). The third one is during March 2008 through September 2008 which seems to be driven by both food and energy prices as these indices exhibit explosive behaviour. We also find evidence suggesting that inflation expectations behave differently under normal and explosive periods. In particular, unemployment and interest rates also help predict inflation expectations during explosive episodes relative to normal times. Furthermore, explosive episodes in the relative measure between headline and core inflation is found to be more important than the relative volatile periods implied by a Markov-switching model when studying inflation expectations. The findings of this paper suggest that explosive behaviour of headline versus core PCE should be taken into account when conducting monetary policy as it is a key determinant in consumers’ inflation expectations.Explosive behaviour, core inflation, relative measure, inflation expectations

Real Time Monitoring of Asset Markets: Bubbles and Crises

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

Sequential Cauchy Combination Test for Multiple Testing Problems with Financial Applications

We introduce a simple tool to control for false discoveries and identify individual signals in scenarios involving many tests, dependent test statistics, and potentially sparse signals. The tool applies the Cauchy combination test recursively on a sequence of expanding subsets of $p$-values and is referred to as the sequential Cauchy combination test. While the original Cauchy combination test aims to make a global statement about a set of null hypotheses by summing transformed $p$-values, our sequential version determines which $p$-values trigger the rejection of the global null. The sequential test achieves strong familywise error rate control, exhibits less conservatism compared to existing controlling procedures when dealing with dependent test statistics, and provides a power boost. As illustrations, we revisit two well-known large-scale multiple testing problems in finance for which the test statistics have either serial dependence or cross-sectional dependence, namely monitoring drift bursts in asset prices and searching for assets with a nonzero alpha. In both applications, the sequential Cauchy combination test proves to be a preferable alternative. It overcomes many of the drawbacks inherent to inequality-based controlling procedures, extreme value approaches, resampling and screening methods, and it improves the power in simulations, leading to distinct empirical outcomes.Comment: 35 pages, 6 figure

Common Bubble Detection in Large Dimensional Financial Systems

Price bubbles in multiple assets are sometimes nearly coincident in occurrence. Such near-coincidence is strongly suggestive of co-movement in the associated asset prices and likely driven by certain factors that are latent in the financial or economic system with common effects across several markets. Can we detect the presence of such common factors at the early stages of their emergence? To answer this question, we build a factor model that includes I(1), mildly explosive, and stationary factors to capture normal, exuberant, and collapsing phases in such phenomena. The I(1) factor models the primary driving force of market fundamentals. The explosive and stationary factors model latent forces that underlie the formation and destruction of asset price bubbles, which typically exist only for subperiods of the sample. The paper provides an algorithm for testing the presence of and date-stamping the origination and termination of price bubbles determined by latent factors in a large-dimensional system embodying many markets. Asymptotics of the bubble test statistic are given under the null of no common bubbles and the alternative of a common bubble across these markets. We prove consistency of a factor bubble detection process for the origination and termination dates of the common bubble. Simulations show good finite sample performance of the testing algorithm in terms of its successful detection rates. Our methods are applied to real estate markets covering 89 major cities in China over the period January 2003 to March 2013. Results suggest the presence of three common bubble episodes in what are known as China’s Tier 1 and Tier 2 cities over the sample period. There appears to be little evidence of a common bubble in Tier 3 cities

Identifying speculative bubbles with an in finite hidden Markov model

This paper proposes an infinite hidden Markov model (iHMM) to detect, date stamp,and estimate speculative bubbles. Three features make this new approach attractive to practitioners. First, the iHMM is capable of capturing the nonlinear dynamics of different types of bubble behaviors as it allows an infinite number of regimes. Second, the implementation of this procedure is straightforward as the detection, dating, and estimation of bubbles are done simultaneously in a coherent Bayesian framework. Third, the iHMM, by assuming hierarchical structures, is parsimonious and superior in out-of-sample forecast. Two empirical applications are presented: one to the Argentinian money base, exchange rate, and consumer price from January 1983 to November 1989; and the other to the U.S. oil price from April 1983 to December 2010. We find prominent results, which have not been discovered by the existing finite hidden Markov model. Model comparison shows that the iHMM is strongly supported by the predictive likelihood

Identifying speculative bubbles with an in finite hidden Markov model

This paper proposes an infinite hidden Markov model (iHMM) to detect, date stamp,and estimate speculative bubbles. Three features make this new approach attractive to practitioners. First, the iHMM is capable of capturing the nonlinear dynamics of different types of bubble behaviors as it allows an infinite number of regimes. Second, the implementation of this procedure is straightforward as the detection, dating, and estimation of bubbles are done simultaneously in a coherent Bayesian framework. Third, the iHMM, by assuming hierarchical structures, is parsimonious and superior in out-of-sample forecast. Two empirical applications are presented: one to the Argentinian money base, exchange rate, and consumer price from January 1983 to November 1989; and the other to the U.S. oil price from April 1983 to December 2010. We find prominent results, which have not been discovered by the existing finite hidden Markov model. Model comparison shows that the iHMM is strongly supported by the predictive likelihood

Salvianolic acid B Relieves Oxidative Stress in Glucose Absorption and Utilization of Mice Fed High-Sugar Diet

Purpose: To evaluate the influence of Salvianolic acid B (Sal B) on  oxidative stress in mice administrated with glucose, sucrose and high-sugar diet.Methods: 40 Kunming mice were divided into four groups of 10. After a fast of 12 h, mice were treated by oral infusion respectively with physiological saline, 20 % glucose, 20 % sucrose, and 20 % glucose + 0.002 % Sal B. Blood glucose and levels of reactive oxygen species (ROS) were  determined at 0, 0.5, 1.0, 1.5, and 2.0 h after administration. Another 3 groups of 10 Kunming mice each were fed with normal diet, high-sugar diet (20 % sucrose, HSD) and HSD + 0.002 % Sal B. Four weeks later, the levels of ROS as well as antioxidant enzyme activity were determined.Results: Blood ROS showed the first peak at 0.5 h and a higher peak at 1.5 h after high glucose administration. ROS were mainly produced in liver and pancreas with the utilization of glucose. Sal B administration prevented increase in blood glucose and significantly (p < 0.05) reduced ROS produced in the process of glucose absorption and utilization, especially the latter. Sal B decrease oxidative stress induced by HSD through scavenging ROS associated with increased activity of antioxidant enzymes.Conclusion: This study demonstrates that Sal B can decrease oxidative stress in glucose absorption and utilization in HSD mice. Thus, the findings provide a basis for a potential interventional strategy for protecting against oxidative damage induced by HSD.Keywords: Salvianolic acid B, Blood glucose, Reactive oxygen species, Oxidative stress, Sugar di

Gold as a Financial Instrument

In this paper, we explore the effectiveness of gold as a hedging and safe haven instrument for a variety of market risks. Rather than confining the analysis to specific countries, we treat gold as a global asset and apply the novel Phillips, Shi and Yu (2015a,b) methodology to identify extreme price movements. This method accounts for both the level and speed of changes in price dynamics that better characterises periods of abnormally high risks. We find that gold is a strong safe haven for stock, European sovereign, and oil inflation market risks. We also show that gold is a strong hedge to inflationary and currency risks. We demonstrate that gold had exhibited safe haven properties during the 2020 Covid-19 crisis, and highlight the importance of considering explosive behaviour in identifying periods of risk

Combustion synthesis of Ce2LuO5.5:Eu phosphor nanopowders: structure, surface and luminescence investigations

The spherical shape, uniform size and small degree of agglomeration of the particles play crucial roles in promoting the practical applications of the phosphor powders. In this paper, the novel Eu3+ -doped cerium lutetium Ce2LuO5.5 composite nanopowders with a cubic fluorite structure were prepared via a typical solution combustion route, and their internal structure, surface morphology as well as luminescence properties were investigated. The Eu3+ could substitute in either Lu3+ or Ce4+ sites and the existence of oxygen vacancy was confirmed in the composite by X-ray diffraction and Raman spectra techniques. Without the addition of surfactant, most of the as-prepared particles were bound together, and the luminescence was very weak even after a sintering process. Assisted with appropriate polyvinyl alcohol (PVA) surfactant in the combustion reaction and a subsequent heat-treatment process, the bound-particles were evidently separated and seemed to be nearly spherical shape. The particle size could be controlled to 30–120 nm and the luminescence was enhanced by adjusting the subsequent sintering temperature. Excited with 466 nm blue light, the nanopowders exhibited characteristic 5D0 → 7FJ (J  =  0–4) emission transition of Eu3+ and showed enhanced red luminescence as Eu3+ occupied Ce4+ site rather than Lu3+ site. The maximum emission was obtained as 40 mol% Eu substitutes Ce in the composite. Due to the coincidence of 466 nm excitation light with the emission of InGaN chips in white light-emitting diodes, the surface-morphology improved Eu-doped Ce2LuO5.5 phosphor nanopowders have a potential application in solid state lighting fields.publishe