Investing in Commodities in Times of Uncertainty and Lax Monetary Policy

2020 ◽  
pp. 1-36
Author(s):  
Athanasios Triantafyllou
Keyword(s):  
Monetary Policy ◽  
Positive Impact ◽  
Relevant Literature ◽  
Commodity Prices ◽  
Price Volatility ◽  
Commodity Markets ◽  
Macroeconomic Fluctuations ◽  
Economic Uncertainty ◽  
Commodity Price Volatility ◽  
Policy Shocks

This chapter presents empirical evidence showing the impact of economic uncertainty and monetary policy on the volatility of commodity futures markets. The findings are in line with those of the relevant literature according to which rising uncertainty predicts rising volatility in commodity markets. The author shows that the unobservable economic uncertainty measures of Jurado et al. (2015) have a significant and long-lasting positive impact on the volatility of commodity prices. Hence, the OLS regression results show that commodity markets are significantly affected by the rising degree of unpredictability in the macroeconomy, while they are relatively immune to observable macroeconomic fluctuations. The expansionary monetary policy is followed by rising volatility in agricultural and energy markets, while it has much smaller effect on the volatility of metals markets. Financialization in commodity markets has increased the dynamic linkages between monetary policy shocks and commodity price volatility.

scholarly journals U.S. Monetary Policy, Commodity Prices and the Financialization Hypothesis

2017 ◽  
Vol 10 (2) ◽  
pp. 53-77 ◽  
Author(s):  
Papa Gueye Fam ◽  
Rachida Hennani ◽  
Nicolas Huchet
Keyword(s):  
Monetary Policy ◽  
Commodity Prices ◽  
Spillover Effects ◽  
Commodity Markets ◽  
Bond Markets ◽  
Financial Assets ◽  
Market Prices ◽  
Agricultural Prices ◽  
Policy Measures ◽  
The U.S

AbstractMany studies point out the growing correlations within financial markets, while others highlight the financialization of commodity markets. The purpose of this article is to revisit the relationships between various financial assets and commodity markets by taking into account the U.S. monetary policy and therefore the implementation of non-standard measures. In addition to oil, stock and bond markets, U.S. policy rates and a great deal of agricultural prices have been over time considered through a DCC-GARCH model, between 1995-2015. We find that agricultural markets uphold the financialization hypothesis, implying an increase in market-prices’ correlations and so raises the question of agricultural prices’ drivers. Interestingly, conditional correlations between the U.S. monetary policy and agricultural prices have decreased since 2010, which indicates that the implementation of non-standard monetary policy measures reduces spillover effects on asset prices, especially raw commodities. Such a result in turn highlights changing relationships between monetary, financial and physical markets, in a context of very weak policy rates over a long period.

Monetary policy shocks and real commodity prices

2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Christopher Phillip Reicher ◽  
Johannes Friederich Utlaut
Keyword(s):  
Monetary Policy ◽  
Commodity Prices ◽  
Monetary Policy Shocks ◽  
Policy Shocks

scholarly journals Macroeconomic Impact of Agricultural Commodity Price Volatility in Nigeria

2019 ◽  
Vol 13 (1) ◽  
pp. 162-174
Author(s):  
Adeyemi A. Ogundipe ◽  
Omobola Adu ◽  
Oluwatomisin M. Ogundipe ◽  
Abiola J. Asaleye
Keyword(s):  
Impulse Response Function ◽  
Price Volatility ◽  
Commodity Price ◽  
Macroeconomic Fluctuations ◽  
Agricultural Commodity ◽  
Agricultural Prices ◽  
Commodity Price Volatility ◽  
Macroeconomic Impact ◽  
Food Imports ◽  
Macroeconomic Aggregates

Introduction: The Nigerian economy has remained consistently heavily dependent on earnings from commodity exports which constitute over 95% external earning and 85% of budgetary and fiscal financing. Agricultural commodity exports have witnessed a significant price swings in the international market in the past few decades resulting in food price hike and macroeconomic distortions in economies heavily dependent on food imports. Methods and Materials: The study assesses the macreoconomic impact of agricultural commodity price volatility in Nigeria from 1970-2017 using Autoregressive Distributive Lag (ARDL) cointegration and Impulse-Response Function (IRF) analysis. The study adopted an atheoretical statistics to ascertain the evidence of swings in macroeconomic aggregates. Results: There was evidence of persistent fluctuations in the macroeconomic variables observed, implying that external price shocks exert a significant impact on the macroeconomic management, since bulk of national budgetary and fiscal financing is from commodity exports. Conclusion: The study found that volatile agricultural prices were responsible for a meager 2% of macroeconomic fluctuations. The empirical evidence corroborates the statistics showing that the share of agriculture in primary commodity exports has consistently remained less than 3% since the advent of crude oil. Furthermore, the study found that the swings in agricultural prices impacts foreign reserves and inflation more significantly and earlier in the time horizons than other macroeconomic aggregates.

scholarly journals Business diversification of coal mining companies as a strategy facing coal price volatility

2021 ◽  
Vol 3 (4) ◽  
pp. 38-50
Author(s):  
Gusnawan Adi Putra ◽  
Sri Mulyantini ◽  
Dianwicaksih Arieftiara
Keyword(s):  
Coal Mining ◽  
Stock Prices ◽  
Negative Impact ◽  
Positive Impact ◽  
Stock Exchange ◽  
Commodity Prices ◽  
Price Volatility ◽  
Company Performance ◽  
Coal Price ◽  
Significant Difference

This study aims to determine the effect of business diversification on stock prices by mediating company performance, represented by the variable ROE and EPS in a fluctuating coal price situation. The data used are 16 companies engaged in coal mining in Indonesia and listed on the Indonesia Stock Exchange (IDX) from 2012 to 2019. Using two analysis methods: path analysis to examine direct and indirect relationships between variables and different tests to see differences in the performance of companies that diversify and do not diversify. The results showed that coal commodity prices had a significant positive effect on stock prices and indirectly, through ROE and EPS, had a significant positive impact on stock prices. Business diversification directly has a significant negative impact on stock prices and indirectly through EPS positively affects stock prices. Business diversification provides a substantial difference to EPS and does not provide a significant difference to ROE.

Commodity price volatility and U.S. monetary policy: Commodity price overshooting revisited

Agribusiness ◽  
2018 ◽  
Vol 35 (2) ◽  
pp. 200-218 ◽  
Author(s):  
Sima Siami‐Namini ◽  
Darren Hudson ◽  
Adao Alexandre Trindade ◽  
Conrad Lyford
Keyword(s):  
Monetary Policy ◽  
Price Volatility ◽  
Commodity Price ◽  
Commodity Price Volatility

WHEN DOES MONETARY MEASUREMENT MATTER (MOST)?

2018 ◽  
pp. 1-17
Author(s):  
Makram El-Shagi
Keyword(s):  
Monetary Policy ◽  
Index Number ◽  
Economic Uncertainty ◽  
Monetary Policy Shocks ◽  
Interaction Terms ◽  
Index Number Theory ◽  
Policy Shocks ◽  
Local Projections ◽  
Relevant Interaction ◽  
Selection Of

It has repeatedly been shown that properly constructed monetary aggregates based on index number theory (such as Divisia money) vastly outperform traditional measures of money (i.e. simple sum money) in empirical models. However, opponents of Divisia frequently claim that Divisia is “too complex” for little gain. And indeed, at first glance it looks as if simple sum and Divisia sum exhibit similar dynamics. In this paper, we want to build deeper understanding of how and when Divisia and simple sum differ empirically using monthly US data from 1990M1 to 2007M12. In particular, we look at how they respond differently to monetary policy shocks, which seems to be the most essential aspect of those differences from the perspective of the policy maker. We use a very rich, fairly agnostic setup that allows us to identify many potential nonlinearities, building on a smoothed local projections approach with automatic selection of the relevant interaction terms. We find, that—while the direction of change is often similar—the precise dynamics differ sharply. In particular in times of economic uncertainty, when the proper assessment of monetary policy is most relevant, those existing differences are drastically augmented.

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