scholarly journals Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices

Econometrics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 40
Author(s):  
Kjartan Kloster Osmundsen ◽  
Tore Selland Kleppe ◽  
Roman Liesenfeld ◽  
Atle Oglend
Keyword(s):  
Structural Parameters ◽  
State Space Model ◽  
Commodity Prices ◽  
Commodity Markets ◽  
Monte Carlo Algorithm ◽  
Economic Rationality ◽  
Storage Model ◽  
Stochastic Trend ◽  
Stochastic Trends ◽  
Deterministic Trend

We propose a State-Space Model (SSM) for commodity prices that combines the competitive storage model with a stochastic trend. This approach fits into the economic rationality of storage decisions and adds to previous deterministic trend specifications of the storage model. For a Bayesian posterior analysis of the SSM, which is nonlinear in the latent states, we used a Markov chain Monte Carlo algorithm based on the particle marginal Metropolis–Hastings approach. An empirical application to four commodity markets showed that the stochastic trend SSM is favored over deterministic trend specifications. The stochastic trend SSM identifies structural parameters that differ from those for deterministic trend specifications. In particular, the estimated price elasticities of demand are typically larger under the stochastic trend SSM.

scholarly journals Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices

2020 ◽  
Author(s):  
Kjartan Kloster Osmundsen ◽  
Tore Selland Kleppe ◽  
Roman Liesenfeld ◽  
Atle Oglend
Keyword(s):  
Commodity Prices ◽  
Storage Model ◽  
Stochastic Trends

The Economics of Commodities and Commodity Markets

2018 ◽  
Author(s):  
Florian Ielpo
Keyword(s):  
Raw Materials ◽  
Commodity Prices ◽  
Essential Element ◽  
Commodity Markets ◽  
Production Costs ◽  
Demand And Supply ◽  
Spot Prices ◽  
Supply Shocks ◽  
The Business Cycle

This chapter covers the economic fundamentals of commodity markets (i.e., what shapes the evolution of the price of raw materials) in three steps. First, it covers the theories explaining why the futures curve can be upward or downward sloping, an essential element for commodity producing companies. The evolution of inventories and hedging pressures are the two dominant sources of explanation. Second, the chapter reviews the fundamentals of commodity spot prices: technologies, supply, demand, and speculation. Production costs draw the long-term evolution of prices, but demand and supply shocks can trigger substantial variations in commodity prices. Third, the chapter presents how commodity prices interact with the business cycle. Commodities are influenced by the world activity but can also have a material impact on it.

scholarly journals Volatility Spillovers Arising from the Financialization of Commodities

2018 ◽  
Vol 11 (4) ◽  
pp. 72 ◽  
Author(s):  
Wing Chan ◽  
Bryce Shelton ◽  
Yan Wu
Keyword(s):  
Commodity Prices ◽  
Spillover Effects ◽  
Realized Volatility ◽  
Commodity Markets ◽  
Exchange Traded Funds ◽  
Volatility Transmission ◽  
Volatility Spillovers ◽  
The Difference ◽  
Index Investment ◽  
The Impact

This paper examines whether the proliferation of new index products, such as commodity-tracking exchange-traded funds (ETFs), amplified the volatility transmission channel introduced by financialization. This paper focuses on the volatility spillover effects among crude oil, metals, agriculture, and non-energy commodity markets. The results show financialization has an impact on the volatility of commodity prices, predominantly for non-energy commodities. However, the impact on volatility is not symmetric across all commodities. The analysis of index investment and investors’ positions in futures markets shows that, when a relationship exists, it is generally negatively correlated with the realized volatility of non-energy commodities. Using realized volatility in the difference-in-difference model provides estimates that are inconsistent with other findings that non-energy commodities, traded as a part of indices, have experienced higher volatility. The results are similar to the index investment and futures market analysis, where increased participation by investors through new investment products has put download pressure on realized 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.

Applications of Bayesian corrections for systematic errors in Rietveld refinements

2016 ◽  
Vol 49 (3) ◽  
pp. 814-822 ◽  
Author(s):  
Anton Gagin ◽  
Igor Levin
Keyword(s):  
Monte Carlo ◽  
Structural Parameters ◽  
Systematic Errors ◽  
Monte Carlo Algorithm ◽  
Data Sets ◽  
Correction Procedure ◽  
Bayesian Procedure ◽  
Rietveld Refinements ◽  
X Ray ◽  
Least Squares Minimization

Recently, a Bayesian statistics approach for correction of systematic errors in Rietveld refinements has been developed and implemented as a patch toGSAS-II. This paper demonstrates the benefits of the proposed method in a series of structural refinements from diffraction data collected for one sample using four different powder diffractometers,i.e.synchrotron and laboratory X-ray and two time-of-flight neutron instruments. Differences between the parameters estimated while fitting these four data sets provided magnitudes of the systematic errors while also highlighting the efficacy of the Bayesian procedure for their correction. Structural parameters estimated from the standard Rietveld refinements using the four data sets differed significantly. In all cases, the agreement improved markedly after applying the Bayesian error-correction procedure. The Bayesian refinements were paired with a Markov chain Monte Carlo algorithm, which was implemented as part of the same patch toGSAS-II, to confirm that uncertainties in the refined parameters obtained using the much faster least-squares minimization were realistic.

scholarly journals Agricultural Policy: High Commodity and Input Prices

2009 ◽  
Vol 38 (1) ◽  
pp. 18-35 ◽  
Author(s):  
Andrew Schmitz ◽  
Hartley Furtan ◽  
Troy G. Schmitz
Keyword(s):  
Commodity Prices ◽  
The United States ◽  
Food Prices ◽  
Commodity Markets ◽  
The European Union ◽  
Agricultural Commodity ◽  
Commodity Trade ◽  
Country Of Origin Labeling ◽  
Input Prices ◽  
Meat Sector

Because of high commodity prices, beginning in 2006, subsidies to farmers in the United States, the European Union, and Canada have been reduced significantly. However, significant losses have been experienced by the red meat sector, along with escalating food prices. Because of rising input costs, the “farm boom” may not be as great as first thought. Ethanol made from corn and country-of-origin labeling cloud the U.S. policy scene. Higher commodity prices have caused some countries to lower tariff and non-tariff barriers, resulting in freer commodity trade worldwide. Policymakers should attempt to make these trade-barrier cuts permanent and should rethink current policy legislation to deal with the possibility of a collapse of world commodity markets. Agricultural commodity prices have dropped significantly since early 2008.

scholarly journals Global vs Sectoral Factors and the Impact of the Financialization in Commodity Price Changes

2020 ◽  
Vol 31 (4) ◽  
pp. 859-879
Author(s):  
Pilar Poncela ◽  
Eva Senra ◽  
Lya Paola Sierra
Keyword(s):  
Developing Economies ◽  
Commodity Prices ◽  
Commodity Price ◽  
Commodity Markets ◽  
Small Scale ◽  
Policy Makers ◽  
Economic Agents ◽  
Short Run ◽  
The Impact ◽  
Predictive Content

Abstract Commodity prices influence price levels of a broad range of goods and, in the case of some developing economies, production and export activity. Therefore, information about future commodity inflation is useful for central banks, forward-looking policy-makers, and economic agents whose decisions depend on their expectations about it. After 2004, we have witnessed the so-called financialization of the commodity markets, which might induce greater communalities among commodity prices. This paper reports evidence on the relevance of the forecasting content of co-movement after 2004. With the use of large and small scale factor models we find that for the short run, in addition to dynamics, sectoral communality has relevant predictive content. For 12 months ahead, dynamics lose relevance while communality remains relevant.

Financialization of Indian agricultural commodities: the case of index investments

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manogna RL ◽  
Aswini Kumar Mishra
Keyword(s):  
Institutional Investors ◽  
Extreme Values ◽  
Commodity Prices ◽  
Equity Markets ◽  
Commodity Markets ◽  
Agricultural Products ◽  
Agricultural Commodities ◽  
Agricultural Commodity ◽  
Content Type ◽  
Index Value

PurposeThe phenomenon known as financialization of commodities, arising from the speculation in commodity derivatives market, has raised serious concerns in the recent past. This has prompted distortion in agricultural commodity prices driving them away from rational levels of supply and demand shocks. In the backdrop of financialized commodities leading to increase in price of agricultural products and their interaction with equity markets, the authors examine the investment of institutional investors in impacting the agricultural returns. The paper aims to focus on the financial mechanism that drives extreme values and the mean of agricultural returns.Design/methodology/approachThe authors employ the Threshold AutoRegressive Quantile (TQAR) methodology to find evidence of linkages between the Indian agricultural and equity markets from January 2010 to May 2020 consistent with the rise in inflows of institutional investors in agricultural markets.FindingsThe results reveal that the investors impact the agricultural commodity markets strongly when the composite commodity index value (COMDEX) is low. Additionally, in the lower extreme quantiles (0.25) of agricultural returns, the integration between the equity index and agricultural returns is found to be highly significant compared to insignificant values in the higher quantiles (0.75 and 0.95) in both the regimes. The results suggest that low values of agricultural commodities are more closely linked to equity indices when composite commodity index value is low. This implies that, at the lower quantiles of COMDEX return (bad day), the investors move to the stock market. In that way, the commodity index returns are seen to be as a strong channel for the financialization of Indian agricultural commodities and suggesting potential involvement of investors during those regime.Research limitations/implicationsRegulators need to anticipate the price fluctuations in spot and futures markets. Investors in commodity markets need to strengthen risk awareness to carry out portfolio strategies.Practical implicationsFrom policy perspective, it is of pivotal importance to enhance the understanding of the financialization of agricultural products. The findings provide reference measures to stabilize the commodity markets, alleviate price distortions and carry out further evidence of price discovery and risk management in Indian commodity markets.Originality/valueTo the best of the authors’ knowledge, this study is the first to highlight the potential influence of financial markets on the financialization of agricultural commodities in an emerging economy like India.

scholarly journals Commodity Prices Revisited

2000 ◽  
Vol 29 (2) ◽  
pp. 125-137 ◽  
Author(s):  
William G. Tomek
Keyword(s):  
Conceptual Models ◽  
Structural Parameters ◽  
Commodity Prices ◽  
Decision Makers ◽  
Model Specification ◽  
Price Expectations ◽  
Empirical Results ◽  
Price Series ◽  
Typical Time ◽  
Random Variability

Empirical models of commodity prices are potentially important aids to decision-makers, especially as the economy has grown more complex. A typical time series of commodity prices exhibits positive autocorrelation, occasional spikes, and random variability, and conceptual models have been developed to explain this behavior. But, the leap from theory to empirical applications is large because of model specification and data quality problems. When modeling price expectations, for example, should a price series be deflated and if so, by what deflator? The choice can have a large effect on empirical results. Nonetheless, it is possible in some applications to obtain relatively stable estimates of structural parameters that are useful for addressing specific problems. This may not happen often, however, because the incentives in academia do not encourage rigorous, in-depth appraisals of empirical results.

Der Zufall und seine Bedeutung für die Entwicklung des deutschen Bruttoinlandsprodukts 1850–1990 / Stochastic Shocks and their Impact on the Development of German Gross Domestic Product from 1850–1990

1998 ◽  
Vol 217 (3) ◽  
Author(s):  
Rainer Metz
Keyword(s):  
Time Series ◽  
Gross Domestic Product ◽  
National Product ◽  
Domestic Product ◽  
Outlier Analysis ◽  
Stochastic Trend ◽  
Trend Model ◽  
Stochastic Trends ◽  
Macroeconomic Time Series

SummaryFollowing the influential work of Nelson and Plosser (1982) stochastic trends in macroeconomic time series are considered to be a stylized fact. However, since the stochastic trend hypothesis can be rejected for many economic series if a segmented trend model is considered as an alternative, there is at present no agreement on the proper modeling of national product. In this paper „Big“-shocks in the series of German Gross Domestic Product from 1850-1990 are modeled by means of an outlier analysis within the ARIMA-approach. Besides the identification and modeling of such outliers their impact on the trend and cycle component and especially on long term growth variations is investigated.

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