scholarly journals A Time-Varying Gerber Statistic: Application of a Novel Correlation Metric to Commodity Price Co-Movements

Forecasting ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 339-354
Author(s):  
Bernardina Algieri ◽  
Arturo Leccadito ◽  
Pietro Toscano
Keyword(s):  
Commodity Prices ◽  
Commodity Price ◽  
Time Varying ◽  
Conditional Correlation ◽  
Forecasting Accuracy ◽  
Novel Approach ◽  
Correlation Models ◽  
Rolling Window ◽  
Auto Regressive ◽  
Energy Products

This study investigates the daily co-movements in commodity prices over the period 2006–2020 using a novel approach based on a time-varying Gerber correlation. The statistic is computed considering a set of probabilities estimated via non-traditional models that give a time-varying structure to the measure. The results indicate that there are several co-movements across commodities, that these co-movements change over time, and that they are tendentially positive. Conditional auto-regressive multithreshold logit models show higher forecasting accuracy for agricultural returns, while dynamic conditional correlation models are more accurate for energy products and metals. The proposed models are shown to be superior in terms of forecasting power to the benchmark method which is based on estimating the Gerber correlation moving a rolling window.

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.

scholarly journals Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach

2021 ◽  
Vol 14 (1) ◽  
pp. 21
Author(s):  
Mariagrazia Fallanca ◽  
Antonio Fabio Forgione ◽  
Edoardo Otranto
Keyword(s):  
Correlation Coefficients ◽  
Bank Loan ◽  
Time Varying ◽  
Conditional Correlation ◽  
Subprime Mortgage ◽  
Macroeconomic Variables ◽  
Correlation Models ◽  
Mortgage Crisis ◽  
The Us ◽  
Macroeconomic Indicators

Several studies have explored the linkage between non-performing loans and major macroeconomic indicators, using a wide variety of methodologies, sometimes with different results. This occurs, we argue, because these relationships are generally derived in terms of correlation coefficients evaluated in certain time spans, which represent a sort of average level of correlations. However, such correlations are necessarily time-varying, because the relationships between bank loan indicators and macroeconomic variables could be stronger during particular periods or in correspondence with important economic events. We propose an empirical exercise using dynamic conditional correlation models, with constant and time-varying parameters. Applying these models to quarterly delinquency rates and an array of macroeconomic variables for the US, for the period 1985–2019, we find that the correlation is often negligible in this period except during periods of economic crises, in particular the early 1990 crisis and the subprime mortgage crisis.

scholarly journals Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jianqin Hang ◽  
Xu Zhang
Keyword(s):  
Time Domain ◽  
Time Varying ◽  
Investor Attention ◽  
Causality Test ◽  
Novel Approach ◽  
Rolling Window ◽  
Causality Tests ◽  
High Volatility ◽  
The Time Domain ◽  
Quantile Causality

This study proposes a novel approach that incorporates rolling-window estimation and a quantile causality test. Using this approach, Google Trends and Bitcoin price data are used to empirically investigate the time-varying quantile causality between investor attention and Bitcoin returns. The results show that the parameters of the causality tests are unstable during the sample period. The results also show strong evidence of quantile- and time-varying causality between investor attention and Bitcoin returns. Specifically, our results show that causality appears only in high volatility periods within the time domain, and causality presents various patterns across quantiles within the quantile domain.

scholarly journals Exploring the Dynamic Links between GCC Sukuk and Commodity Market Volatility

2018 ◽  
Vol 6 (3) ◽  
pp. 72 ◽  
Author(s):  
Nader Naifar
Keyword(s):  
Management Practices ◽  
Commodity Prices ◽  
Precious Metals ◽  
Price Volatility ◽  
Commodity Price ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Commodity Price Volatility ◽  
The Impact ◽  
Risk Ratios

This study investigates the impact of commodity price volatility (including soft commodities, precious metals, industrial metals, and energy) on the dynamics of corporate sukuk returns. Using a sample of sukuk indices from Gulf Cooperation Council (GCC) countries, we study the dynamic conditional correlation using a multivariate generalized autoregressive conditional heteroskedasticity dynamic conditional correlation (GARCH-DCC) process. Empirical results show a time-varying negative correlation between GCC sukuk returns and commodity prices. In fact, a negative conditional correlation among assets of a given portfolio implies higher gain-to-risk ratios. An understanding of volatility and dynamic co-movements in financial and commodity markets is important for portfolio allocation and risk management practices.

scholarly journals Commodity Price Correlation And Time Varying Hedge Ratios

2014 ◽  
Vol 30 (4) ◽  
pp. 1053
Author(s):  
Amine Lahiani ◽  
Khaled Guesmi
Keyword(s):  
Stock Market ◽  
Value At Risk ◽  
Price Volatility ◽  
Commodity Price ◽  
Conditional Value At Risk ◽  
Time Varying ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Hedging Strategies ◽  
Hedge Ratios

<p>This paper examines the price volatility and hedging behavior of commodity futures indices and stock market indices. We investigate the weekly hedging strategies generated by return-based and range-based asymmetric dynamic conditional correlation (DCC) processes. The hedging performances of short and long hedgers are estimated with a semi-variance, low partial moment and conditional value-at-risk. The empirical results show that range-based DCC model outperforms return-based DCC model for most cases.</p>

scholarly journals Sustainability of Global Economic Policy and Stock Market Returns in Indonesia

2021 ◽  
Vol 13 (10) ◽  
pp. 5422
Author(s):  
Shabir Mohsin Hashmi ◽  
Muhammad Akram Gilal ◽  
Wing-Keung Wong
Keyword(s):  
Economic Policy ◽  
Stock Market ◽  
Crude Oil ◽  
Oil Prices ◽  
Time Varying ◽  
Conditional Correlation ◽  
Developed Markets ◽  
Crude Oil Prices ◽  
Rolling Window ◽  
Crude Oil Production

Interdependence in trade and financial globalization has increased the vulnerability of developed and developing countries to external shocks alike, whereas emerging markets are more vulnerable to the shocks originating from the world’s leading economies. This paper investigates the impact of the uncertainty from the global economic policy on the return of the Indonesian stock market by using the time-varying correlation based on the rolling window method and time-varying built dynamic conditional correlation method. Both the rolling window and condition correlation estimates indicate that the correlation between global policy uncertainty and Indonesian stock returns is time-varying. The results of the autoregressive distributed lag-based regression indicate that inflation, global crude oil prices, gross domestic product, and world crude oil production have significant impacts on the dynamic conditional correlation. The average negative estimate of time-varying correlation suggests that investors when faced with liquidity constraints in one country may sell off their assets in another country to raise funds in order to meet their future financial needs. This also indicates that the rise in the uncertainty of economic policy in developed markets has a negative impact on the shocks faced by the Indonesian stock market. Based on our empirical findings, it is recommended that Indonesian policymakers should place more focus on the sustainability of the economic growth, pay close attention to volatile crude oil prices, world crude oil production, and inflation so as to avoid dynamic interaction between the uncertainty of economic policy in the developed markets and the return of the Indonesian stock market.

Economic Institutions and Growth Nexus: The Role of Governance and Democratic Institutions—Evidence from Time Varying Parameters’ (TVPs) Models

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 675-688
Author(s):  
Ghulam Murtaza ◽  
Muhammad Zahir Faridi
Keyword(s):  
Structural Changes ◽  
Jel Classification ◽  
Economic Institutions ◽  
Time Varying ◽  
Democratic Institutions ◽  
Main Hypothesis ◽  
Dynamic Relationship ◽  
Rolling Window

The present study has investigated the channels through which the linkage between economic institutions and growth is gauged, by addressing the main hypothesis of the study that whether quality of governance and democratic institutions set a stage for economic institutions to promote the long-term growth process in Pakistan. To test the hypothesis empirically, our study models the dynamic relationship between growth and economic institutions in a time varying framework in order to capture institutional developments and structural changes occurred in the economy of Pakistan over the years. Study articulates that, along with some customary specifics, the quality of government and democracy are the substantial factors that affect institutional quality and ultimately cause to promote growth in Pakistan. JEL Classification: O40; P16; C14; H10 Keywords: Economic Institutions, Growth, Governance and Democracy, Rolling Window Two-stage Least Squares, Pakistan

scholarly journals Commodity price pass-through along the pricing chain

2021 ◽  
Author(s):  
Rebeca Jiménez-Rodríguez ◽  
Amalia Morales-Zumaquero
Keyword(s):  
Emerging Economies ◽  
Raw Materials ◽  
Commodity Prices ◽  
Commodity Price ◽  
Emerging Countries ◽  
Consumer Prices ◽  
Advanced Economies ◽  
The World ◽  
Producer Prices ◽  
Pass Through

AbstractThis paper analyses the commodity price pass-through along the pricing chain for the global commodity price index and the indices of its main categories (i.e., agricultural raw materials, food and beverages, energy and metals) in the world, advanced and emerging economies. To do so, the study considers country-by-country vector autoregression models and pool the results by taking weighted means for 18 advanced economies and 19 emerging countries, as well as for the world (defined as the sum of advanced and emerging economies). The results show the following: (i) there is evidence in favour of partial pass-through from commodity prices to producer prices, although the evidence for the pass-through to consumer prices is less evident; (ii) the pass-through in the world seems to be led by both advanced and emerging countries for producer prices and only by advanced economies for consumer prices; (iii) higher prices in the four categories (agricultural raw materials only in the short-run) induce significant higher producer prices in almost all cases, with shocks in the prices of energy and metals showing the largest effects; and (iv) energy prices explain the highest variability of producer and consumer prices.

Sign in / Sign up

Export Citation Format

Share Document