Forecasting Commodity Market Synchronization with Commodity Currencies: A Network-Based Approach.

This paper shows that some commodity currencies (from Chile, Iceland, Norway, South Africa, Australia, Canada, and New Zealand) predict the synchronization of metals and energy commodities. This relationship links the present-value theory for exchange rates and its connection with commodity export economies' fundamentals, where prospective commodity price fluctuations affect exchange rates. Predicting commodity market return synchronization is critical for dealing with systemic risk, market efficiency, and financial stability since synchronization reduces the benefits of diversification and increases the probability of contagion in financial markets during economic and financial crises. Using network methods coupled with in-sample and out-of-sample econometrics models, we find evidence that a fall in the return of commodity-currencies (dollar appreciation) predicts an increase in commodity market synchronization and, consequently, in commodity market systemic risk. This discovery is consistent with a transitive capacity phenomenon, suggesting that commodity currencies have a predictive ability over commodities that extend beyond the commodity bundle that a country produces. The latter behavior would be exacerbated by the high financialization of commodities and strong co-movement of commodity markets. Our paper is part of a vigorously growing literature that has recently measured and predicted systemic risk caused by synchronization, combining a complex systems perspective and financial network analysis.

Making Cardiopulmonary Exercise Testing Interpretable for Clinicians.

ABSTRACT: Cardiopulmonary exercise testing (CPET) is a dynamic clinical tool for determining the cause for a person's exercise limitation. CPET provides clinicians with fundamental knowledge of the coupling of external to internal respiration (oxygen and carbon dioxide) during exercise. Subtle perturbations in CPET parameters can differentiate exercise responses among individual patients and disease states. However, perhaps because of the challenges in interpretation given the amount and complexity of data obtained, CPET is underused. In this article, we review fundamental concepts in CPET data interpretation and visualization. We also discuss future directions for how to best use CPET results to guide clinical care. Finally, we share a novel three-dimensional graphical platform for CPET data that simplifies conceptualization of organ system-specific (cardiac, pulmonary, and skeletal muscle) exercise limitations. Our goal is to make CPET testing more accessible to the general medical provider and make the test of greater use in the medical toolbox.

The predictive power of stock market's expectations volatility: A financial synchronization phenomenon.

We explore the use of implied volatility indices as a tool for estimate changes in the synchronization of stock markets. Specifically, we assess the implied stock market's volatility indices' predictive power on synchronizing global equity indices returns. We built the correlation network of 26 stock indices and implemented in-sample and out-of-sample tests to evaluate the predictive power of VIX, VSTOXX, and VXJ implied volatility indices. To measure markets' synchronization, we use the Minimum Spanning Tree length and the length of the Planar Maximally Filtered Graph. Our results indicate a high predictive power of all the volatility indices, both individually and together, though the VIX predominates over the evaluated options. We find that an increase in the markets' volatility expectations, captured by the implied volatility indices, is a good Granger predictor of an increase in the synchronization of returns in the following month. Estimating, monitoring, and predicting returns' synchronization is essential for investment decision-making, especially for diversification strategies and regulating financial systems.

Image Analysis Method for the Characterization of Trichoderma reesei During Fermentations.

This chapter describes the use of a specific image analysis method with the plug im! software for the characterization of filamentous fungus morphology. It details an application of this method with samples obtained from a fermentation process of a Trichoderma reesei strain. This fully automated and accurate image analysis method provides quantitative and representative data for morphological and topological analyses.