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 Financial speculation impact on agricultural commodity price volatility: TGARCH approach

2020 ◽  
Author(s):  
Algirdas Justinas Staugaitis ◽  
Keyword(s):  
Commodity Prices ◽  
Price Volatility ◽  
Commodity Price ◽  
Agricultural Commodity ◽  
Exogenous Factor ◽  
Market Participants ◽  
Financial Speculation ◽  
Commercial Market ◽  
Commodity Price Volatility ◽  
The Impact

Motivated by agricultural commodity price fluctuations and spikes in the last decade, we investigate whether financial speculation destabilizes the price of agricultural commodities. The aim of this research is to assess the impact of financial speculation on agricultural commodity price volatility. In our study we use weekly returns on wheat, soybean and corn futures from Chicago Mercantile of Exchange. To measure this impact, we apply autoregressive conditional heteroskedasticity (ARCH) technique. We also propose a model with seasonal dummy variables to measure if financial speculation impact on price volatility differs among seasons. The results of our research indicate that financial speculation as an exogenous factor has either no effect or reduces the volatility of the underlying futures prices. Therefore, we conclude that the increase of non-commercial market participants does not make the agricultural commodity prices more volatile or this link is at least questionable.

scholarly journals COMMODITY PRICE AND INFLATION DYNAMICS: EVIDENCE FROM BRIICS

2021 ◽  
Vol 23 (4) ◽  
pp. 485-500
Author(s):  
Syed Aun R. Rizvi ◽  
Sahminan Sahminan
Keyword(s):  
South Africa ◽  
Inflation Targeting ◽  
Phillips Curve ◽  
Commodity Prices ◽  
Price Volatility ◽  
Commodity Price ◽  
Food Prices ◽  
Energy Prices ◽  
Commodity Price Volatility ◽  
The Impact

In this study, we use a commodity augmented Phillips curve to investigate the impact of global commodity prices on domestic inflation in Brazil, Russia, India, Indonesia, China, and South Africa. Oil and energy prices cause inflationary pressures in all countries, except Russia, where they cause deflationary pressures. In Indiaand Indonesia, global food prices are highly significant and positively related to inflation, while in South Africa precious metal prices impact inflation negatively. For policymakers, this study provides insights on the domestic adjustments required for inflation targeting in response to global commodity price volatility.

The impact of macroeconomic uncertainty on international commodity prices

2017 ◽  
Vol 7 (2) ◽  
pp. 163-184 ◽  
Author(s):  
Xiaofen Tan ◽  
Yongjiao Ma
Keyword(s):  
Raw Materials ◽  
Commodity Prices ◽  
Precious Metals ◽  
Commodity Price ◽  
Content Type ◽  
Vector Autoregressive ◽  
Macroeconomic Uncertainty ◽  
Wide Range ◽  
The Impact ◽  
Low Uncertainty

Purpose The purpose of this paper is to empirically analyze the impact of macroeconomic uncertainty on a large sample of 19 commodity markets. Design/methodology/approach The authors rely on Jurado et al.’s (2015) measure of macroeconomic uncertainty based on a wide range of monthly macroeconomic and financial indicators and estimate a threshold VAR model to assess whether the impact of macroeconomic uncertainty on commodity prices differs under the high- or low-uncertainty state. Findings The findings show that positive macroeconomic uncertainty shocks affect commodity prices returns negatively on average and the impact of macroeconomic uncertainty is generally higher in high-uncertainty states compared with low-uncertainty states. Besides, although the safe-haven role of precious metals is confirmed, energy and industrial markets are more sensitive to short-run and long-run macroeconomic uncertainty, respectively. Research limitations/implications The findings in this study suggest that commodity prices reflect not only the level of economic fundamental but also the volatility of economic fundamental. Originality/value This study empirically analyzes and verifies the influence of macroeconomic uncertainty not only on oil prices but also on four groups of 19 raw materials. As for the methodological issues, the authors rely on a structural threshold vector autoregressive specification for modeling commodity price returns to account for potentially different effects depending on the macroeconomic uncertainty states.

scholarly journals Discussion: Commodity Price Discovery: Problems That Have Solutions or Solutions That Are Problems

2009 ◽  
Vol 41 (2) ◽  
pp. 393-402 ◽  
Author(s):  
T. Randall Fortenbery
Keyword(s):  
Futures Markets ◽  
Market Failure ◽  
Commodity Prices ◽  
Price Volatility ◽  
Commodity Price ◽  
Price Risk ◽  
Futures Trading ◽  
Unacceptable Behavior ◽  
Commodity Price Volatility ◽  
Negative Impacts

This paper examines three invited papers focused on commodity prices. Public responses to high nominal commodity prices and perceived increases in price risk have ranged from attempts to assign blame, attempts to change contracting arrangements, and development of public policy that “protects“ the market from future occurrences of unacceptable behavior. Interestingly, a result of increased commodity price volatility has suggested that futures markets no longer “work.“ This is ironic given that futures markets initially came into existence as tools for managing the negative impacts of commodity price risk. In response to perceptions of market failure some are looking for strategies to regulate the who and how of futures trading.

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 Measuring the financial effects of mitigating commodity price volatility in supply chains

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Barbara Gaudenzi ◽  
George A. Zsidisin ◽  
Roberta Pellegrino
Keyword(s):  
Supply Chain ◽  
Risk Mitigation ◽  
Price Volatility ◽  
Commodity Price ◽  
Price Risk ◽  
Costs And Benefits ◽  
Content Type ◽  
Advantages And Disadvantages ◽  
Commodity Price Volatility ◽  
The Impact

Purpose Firms can choose from an array of approaches for reducing the detrimental financial effects caused by unfavorable fluctuations in commodity prices. The purpose of this paper is to provide guidance for effectively estimating the financial effects of mitigating commodity price risk volatility (CPV) in supply chain management decisions. Design/methodology/approach This paper adopts two prominent and complementary methodologies, namely, total cost of ownership (TCO and real options valuation (ROV), to illustrate how commodity price risk mitigation strategies can be analyzed with respect to their effect on costs and performance. The paper provides insights through a case study to demonstrate the application of these methods together and establish the benefits and challenges associated with their implementation. Findings The paper illustrates advantages and disadvantages of TCO and ROV and how these approaches can be adopted together to contribute to effective purchasing decisions. Supply chain flexibility is a key capability but requires investments. Holistically measuring the financial effects of flexibility investments is imperative for gaining executive management support in mitigating commodity price volatility. Research limitations/implications This study can provide supply chain professionals with useful guidance for measuring the costs and benefits related to developing strategies for mitigating commodity price volatility. TCO provides a focus on the costs associated with the commodity purchasing process, and ROV enables the aggregation of all the costs and benefits associated with the use of the strategy and synthesizes them into the net value estimate. Originality/value The paper provides a comparison of different but complementary approaches, specifically TCO and ROV, for analyzing the effectiveness of CPV risk mitigation decisions. In addition, these two methods allow supply chain professionals to evaluate and control the financial effects of CPV risk, particularly the impact of mitigation on firm’s cash flows.

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