scholarly journals Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach

Risks ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 144
Author(s):  
Mila Andreani ◽  
Vincenzo Candila ◽  
Giacomo Morelli ◽  
Lea Petrella
Keyword(s):  
Low Frequency ◽  
The United States ◽  
Energy Markets ◽  
Data Sampling ◽  
Conditional Correlation ◽  
Policy Makers ◽  
Dynamic Conditional Correlation ◽  
Mixed Frequency ◽  
Asymmetric Garch ◽  
Risk Managers

This paper shows the effects of the COVID-19 pandemic on energy markets. We estimate daily volatilities and correlations among energy commodities relying on a mixed-frequency approach that exploits information from the number of weekly deaths related to COVID-19 in the United States. The mixed-frequency approach takes advantage of the MIxing-Data Sampling (MIDAS) methods. We compare our results to those obtained by employing two well-known models that do not account for the COVID-19 low-frequency variable, namely the Dynamic EquiCorrelation (DECO) and corrected Dynamic Conditional Correlation (cDCC). Moreover, we consider four possible specifications of the volatility: GARCH, GJR, GARCH-MIDAS, and Double-Asymmetric GARCH-MIDAS. The empirical results show that our approach is statistically superior to other models and represents a valuable methodology that can be used for risk managers, investors, and policy makers to assess the effects of the pandemic on spillovers effects in energy markets.

scholarly journals Multivariate Analysis of Cryptocurrencies

Econometrics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 28
Author(s):  
Vincenzo Candila
Keyword(s):  
Great Recession ◽  
Market Value ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Mixed Frequency ◽  
The Great Recession ◽  
The World ◽  
Asymmetric Garch ◽  
Portfolio Managers ◽  
Points Of View

Recently, the world of cryptocurrencies has experienced an undoubted increase in interest. Since the first cryptocurrency appeared in 2009 in the aftermath of the Great Recession, the popularity of digital currencies has, year by year, risen continuously. As of February 2021, there are more than 8525 cryptocurrencies with a market value of approximately USD 1676 billion. These particular assets can be used to diversify the portfolio as well as for speculative actions. For this reason, investigating the daily volatility and co-volatility of cryptocurrencies is crucial for investors and portfolio managers. In this work, the interdependencies among a panel of the most traded digital currencies are explored and evaluated from statistical and economic points of view. Taking advantage of the monthly Google queries (which appear to be the factors driving the price dynamics) on cryptocurrencies, we adopted a mixed-frequency approach within the Dynamic Conditional Correlation (DCC) model. In particular, we introduced the Double Asymmetric GARCH–MIDAS model in the DCC framework.

scholarly journals SINCRONIZACIÓN DE LOS CICLOS ECONÓMICOS DE MÉXICO Y ESTADOS UNIDOS: UN ENFOQUE DE CORRELACIÓN DINÁMICA

2021 ◽  
Vol 81 (319) ◽  
pp. 37
Author(s):  
Dulce Albarrán Macías ◽  
Pablo Mejía Reyes ◽  
Francisco López Herrera
Keyword(s):  
United States ◽  
Business Cycles ◽  
Great Recession ◽  
The United States ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Dynamic Correlation ◽  
Time Period ◽  
The Common ◽  
The Business Cycle

<p>El objetivo de este documento es analizar la sincronización de los ciclos económicos de México y Estados Unidos durante el periodo 1981-2017 mediante la estimación de un coeficiente de correlación condicional dinámica que permite tener una estimación para cada periodo de tiempo. Los resultados, obtenidos a partir de distintos indicadores de producción y métodos de eliminación de tendencia, muestran un aumento desde la apertura de la economía mexicana a mediados de la década de 1980, especialmente durante las recesiones de 2001-2002 y 2008-2009 y también una serie de descensos aislados, explicados por diferencias en los ritmos de crecimiento de ambas economías, y una declinación sostenida en la fase pos-Gran Recesión que se explica principalmente por reducciones en el comercio exterior.</p><p> </p><p align="center">SYNCHRONIZATION OF THE BUSINESS CYCLES OF MEXICO AND THE UNITED STATES: A DYNAMIC CORRELATION APPROACH</p><p align="center"><strong>ABSTRACT</strong></p><p>The objective of this paper is to analyze the business cycle synchronization of Mexico and the United States over the period 1981-2017 by estimating a dynamic conditional correlation coefficient that allows us to have an estimate for each time period. The results, obtained from different production indicators and different de-trending methods, show an increase in this synchronization after the opening of the Mexican economy in the mid-eighties, especially during the common recessions of 2001-2002 and 2008-2009, and some isolated drops explained by differences in the growth rates of both economies as well as a sustained decline in the post-Great Recession phase resulting from the decline of international trade.</p>

scholarly journals The Conflicting Developments of RMB Internationalization: Contagion Effect and Dynamic Conditional Correlation

2021 ◽  
Vol 5 (1) ◽  
pp. 54
Author(s):  
Xiangqing Lu ◽  
Roengchai Tansuchat
Keyword(s):  
Exchange Rate ◽  
The United States ◽  
Contagion Effect ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
The Us ◽  
Before And After ◽  
Us Dollar ◽  
The Cost ◽  
Rmb Internationalization

As the world’s largest exporter and second-largest importer, China has made exchange rate stability a top priority for its economic growth. With development over decades, however, China now holds excess dollar reserves that have suffered a huge paper loss because of quantitative easing in the United States. In this reality, China has been provoked into speeding RMB internationalization as a strategy to reduce the cost and get rid of the excessive dependence on the US dollar. Thus, this study attempts to investigate the volatility contagion effect and dynamic conditional correlation among four assets, namely China’s onshore exchange rate (CNY), China’s offshore exchange rate (CNH), China’s foreign exchange reserves (FER), and RMB internationalization level (RGI). Considering the huge changes before and after China’s “8.11” exchange rate reform in 2015, we separate the period of study into two sub-periods. The Diagonal BEKK-GARCH model is employed for this analysis. The results exhibit large GARCH effects and relatively low ARCH effects among all periods and evidence that, before August 2015, there was a weak contagion effect among them. However, after September 2015, the model validates a strengthened volatility contagion within CNY and CNH, CNY and RGI, and CNH and RGI. However, the contagion effect is weakened between FER and CNY, FER and CNH, and FER and RGI.

Water Resources Management in the Semi-Arid Central Valley of California

1987 ◽  
Vol 19 (9) ◽  
pp. 97-106
Author(s):  
J. J. Vasconcelos
Keyword(s):  
Resource Management ◽  
Ground Water ◽  
Water Resource ◽  
Water Resource Management ◽  
Arid Regions ◽  
Central Valley ◽  
The United States ◽  
Policy Makers ◽  
Ground Water Resource ◽  
Semi Arid

Hater resource managers in semi-arid regions are faced with some unique problems. The wide variations in precipitation and stream flows in semi-arid regions increase man's dependence on the ground water resource for an ample and reliable supply of water. Proper management of the ground water resource is absolutely essential to the economic well being of semi-arid regions. Historians have discovered the remains of vanished advanced civilizations based on irrigated agriculture which were ignorant of the importance of proper ground water resource management. In the United States a great deal of effort is presently being expended in the study and control of toxic discharges to the ground water resource. What many public policy makers fail to understand is that the potential loss to society resulting from the mineralization of the ground water resource is potentially much greater than the loss caused by toxic wastes discharges, particularly in developing countries. Appropriations for ground water resource management studies in developed countries such as the United States are presently much less than those for toxic wastes management and should be increased. It is the reponsibility of the water resource professional to emphasize to public policy makers the importance of ground water resource management. Applications of ground water resource management models in the semi-arid Central Valley of California are presented. The results demonstrate the need for proper ground water resource management practices in semi-arid regions and the use of ground water management models as a valuable tool for the water resource manager.

Detection by real-time quaking-induced conversion (RT-QuIC), ELISA, and IHC of chronic wasting disease prion in lymph nodes from Pennsylvania white-tailed deer with specific PRNP genotypes

2021 ◽  
pp. 104063872110214
Author(s):  
Deepanker Tewari ◽  
David Steward ◽  
Melinda Fasnacht ◽  
Julia Livengood
Keyword(s):  
Real Time ◽  
Disease Susceptibility ◽  
Chronic Wasting Disease ◽  
Low Frequency ◽  
The United States ◽  
Detection Methods ◽  
Spongiform Encephalopathy ◽  
Wasting Disease ◽  
Diagnostic Laboratory ◽  
Highly Sensitive

Chronic wasting disease (CWD) is a prion-mediated, transmissible disease of cervids, including deer ( Odocoileus spp.), which is characterized by spongiform encephalopathy and death of the prion-infected animals. Official surveillance in the United States using immunohistochemistry (IHC) and ELISA entails the laborious collection of lymphoid and/or brainstem tissue after death. New, highly sensitive prion detection methods, such as real-time quaking-induced conversion (RT-QuIC), have shown promise in detecting abnormal prions from both antemortem and postmortem specimens. We compared RT-QuIC with ELISA and IHC for CWD detection utilizing deer retropharyngeal lymph node (RLN) tissues in a diagnostic laboratory setting. The RLNs were collected postmortem from hunter-harvested animals. RT-QuIC showed 100% sensitivity and specificity for 50 deer RLN (35 positive by both IHC and ELISA, 15 negative) included in our study. All deer were also genotyped for PRNP polymorphism. Most deer were homozygous at codons 95, 96, 116, and 226 (QQ/GG/AA/QQ genotype, with frequency 0.86), which are the codons implicated in disease susceptibility. Heterozygosity was noticed in Pennsylvania deer, albeit at a very low frequency, for codons 95GS (0.06) and 96QH (0.08), but deer with these genotypes were still found to be CWD prion-infected.

scholarly journals The relationship between Google search interest for pulmonary symptoms and COVID-19 cases using dynamic conditional correlation analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Halit Cinarka ◽  
Mehmet Atilla Uysal ◽  
Atilla Cifter ◽  
Elif Yelda Niksarlioglu ◽  
Aslı Çarkoğlu
Keyword(s):  
Case Reports ◽  
Time Varying ◽  
Conditional Correlation ◽  
Web Based ◽  
Specific Symptom ◽  
Sliding Windows ◽  
Dynamic Conditional Correlation ◽  
The United Kingdom ◽  
Correlation Models ◽  
Google Search

AbstractThis study aims to evaluate the monitoring and predictive value of web-based symptoms (fever, cough, dyspnea) searches for COVID-19 spread. Daily search interests from Turkey, Italy, Spain, France, and the United Kingdom were obtained from Google Trends (GT) between January 1, 2020, and August 31, 2020. In addition to conventional correlational models, we studied the time-varying correlation between GT search and new case reports; we used dynamic conditional correlation (DCC) and sliding windows correlation models. We found time-varying correlations between pulmonary symptoms on GT and new cases to be significant. The DCC model proved more powerful than the sliding windows correlation model. This model also provided better at time-varying correlations (r ≥ 0.90) during the first wave of the pandemic. We used a root means square error (RMSE) approach to attain symptom-specific shift days and showed that pulmonary symptom searches on GT should be shifted separately. Web-based search interest for pulmonary symptoms of COVID-19 is a reliable predictor of later reported cases for the first wave of the COVID-19 pandemic. Illness-specific symptom search interest on GT can be used to alert the healthcare system to prepare and allocate resources needed ahead of time.

Universality, Quality & Economics: Finding a Balance in Ontario and British Columbia

1994 ◽  
Vol 20 (1-2) ◽  
pp. 203-229
Author(s):  
John D. Blum
Keyword(s):  
Health Reform ◽  
New Ventures ◽  
The United States ◽  
High Price ◽  
Social Programs ◽  
Policy Makers ◽  
High Expectations ◽  
The Us ◽  
Acceptable Model ◽  
National Economies

National economies worldwide are in disarray, evidenced by escalating debts and growing deficits. As countries struggle with their faltering economies they are hard pressed to fulfill commitments of social programs made in more prosperous times, much less take on new government initiatives. The current experiences in health reform in the United States present an interesting example of the dilemmas governments now face when they embark on new ventures. While great political pressures have been launched and high expectations abound, the reality of American health reform quickly reveals that expanded access will come at a high price that won't be offset easily by conventional cost containment or market forces.In the search for an acceptable model for health reform, it was popular for policy makers and academics to turn their attentions to the health systems of other nations. Recommendations were made that the US should adopt a German or Canadian solution for our health problems.

Predicting risk in energy markets: Low-frequency data still matter

2021 ◽  
Vol 282 ◽  
pp. 116146
Author(s):  
Štefan Lyócsa ◽  
Neda Todorova ◽  
Tomáš Výrost
Keyword(s):  
Low Frequency ◽  
Energy Markets ◽  
Frequency Data

scholarly journals COVID-TRACK: world and USA SARS-COV-2 testing and COVID-19 tracking

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ye Emma Zohner ◽  
Jeffrey S. Morris
Keyword(s):  
Web Application ◽  
The United States ◽  
Mitigation Strategies ◽  
Time Lags ◽  
Policy Makers ◽  
Major Health ◽  
Dynamic Representation ◽  
Graphical Displays ◽  
The Usa ◽  
User Friendly

Abstract Background The COVID-19 pandemic has caused major health and socio-economic disruptions worldwide. Accurate investigation of emerging data is crucial to inform policy makers as they construct viral mitigation strategies. Complications such as variable testing rates and time lags in counting cases, hospitalizations and deaths make it challenging to accurately track and identify true infectious surges from available data, and requires a multi-modal approach that simultaneously considers testing, incidence, hospitalizations, and deaths. Although many websites and applications report a subset of these data, none of them provide graphical displays capable of comparing different states or countries on all these measures as well as various useful quantities derived from them. Here we introduce a freely available dynamic representation tool, COVID-TRACK, that allows the user to simultaneously assess time trends in these measures and compare various states or countries, equipping them with a tool to investigate the potential effects of the different mitigation strategies and timelines used by various jurisdictions. Findings COVID-TRACK is a Python based web-application that provides a platform for tracking testing, incidence, hospitalizations, and deaths related to COVID-19 along with various derived quantities. Our application makes the comparison across states in the USA and countries in the world easy to explore, with useful transformation options including per capita, log scale, and/or moving averages. We illustrate its use by assessing various viral trends in the USA and Europe. Conclusion The COVID-TRACK web-application is a user-friendly analytical tool to compare data and trends related to the COVID-19 pandemic across areas in the United States and worldwide. Our tracking tool provides a unique platform where trends can be monitored across geographical areas in the coming months to watch how the pandemic waxes and wanes over time at different locations around the USA and the globe.

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