Determinants of commodity prices

Arango, Luis E.; Arias, Fernando; Flórez, Adriana

doi:10.1080/00036846.2010.500273

Cited by 35 publications

(16 citation statements)

References 11 publications

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“…and p t is the world price for an internationally traded commodity. Moreover, a complimentary supply function (see Arango et al, 2012) can be stated:…”

Section: Introductionmentioning

confidence: 99%

Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day

et al. 2017

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A significant proportion of the trade basket of many developing countries is comprised of primary commodities. This implies relative price movements in commodities may have important consequences for economic growth and poverty reduction. Taking a long-run perspective, we examine the historical relation between a new aggregate index of commodity prices, economic activity and interest rates. Initial empirical tests show that commodity prices present a downward trend with breaks over the entire industrial age, providing clear support for the Prebisch-Singer hypothesis. It would also appear that this trend has declined at a faster rate since the 1870s. Conversely, several GDP series such as World, Chile, China, UK and US, trend upwards with breaks. Such trending behaviour in both commodity prices and economic activity suggests a latent common factor like technological innovation.To assess the relationships between economic series, we apply a stationary VAR (Vector Autoregression) to model movements around trends. Strikingly, there is evidence that commodity prices Granger cause income and interest rates, whilst interest rates Granger cause commodity prices. From these results and the related impulse response function analysis, the historical perspective provides some useful information for contemporary policy makers. For example, loose monetary policy has tended to support higher commodity prices. More-1 over, commodity price movements have an asymmetric country effect on economic activity; periods of falling commodity prices will support GDP growth for commodity importers like the US but depress growth for commodity exporters such as Chile.

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“…and p t is the world price for an internationally traded commodity. Moreover, a complimentary supply function (see Arango et al, 2012) can be stated:…”

Section: Introductionmentioning

confidence: 99%

Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day

et al. 2017

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“…Menurut GAPKI (2014), terjadi peningkatan produksi olein sebesar 107,5 persen dari tahun 2002 sampai dengan 2013 dan terjadi perubahan pola konsumsi dimana konsumsi olein untuk kebutuhan dalam negeri sekitar 61 persen dan konsumsi olein untuk ekspor sekitar 39 persen pada tahun 2002 sedangkan pada tahun 2013, 65 persen konsumsi ditujukan untuk ekspor dan 35 persen ditujukan untuk konsumsi dalam negeri. 2009 2010 2011 2012 2013 2014 CPOTR -193 563 771 979 817 143 795 296 605 279 OLEINTR --1 542 4 374 1 963 588 GOLDGR 3 831 23 285 12 873 6 443 84 477 66 707 GOLDID --7 063 4 867 605 949 GOLDUD --79 366 113 904 48 686 3 402 PAMPGRID -----3 Helbling et al (2008), Arango et al (2012), Frankel dan Rose (2010), Arshad dan Hameed (2012). Sedangkan penggunaan metode VECM dalam analisis faktor yang mempengaruhi harga berdasarkan pada penelitian Nugraheni (2014).…”

Section: Pendahuluanunclassified

Analisis Faktor Yang Mempengaruhi Harga Dan Integrasi Harga Olein

Paramita

Nuryartono

Achsani

2018

JEKP

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Olein production increased by 107.5 percent from 2002 to 2013. There was a change in consumption patterns where the consumption of olein intended for export has risen from only 39 percent in 2002 to 65 percent in 2013. In the beginning of 2008, olein prices increased due to the global financial crisis. In the end of 2008, olein prices decreased but since then olein prices fluctuations until the end of 2014. Many factors affecting the price fluctuations such as macroeconomic and microeconomic variables. Commodity market participants need to take action in response to price fluctuations by participating in commodity futures trading. Olein futures trading commodity in Indonesia is not well developed. This is indicated by small volumes of the transaction of olein futures contracts in Indonesia Commodity and Derivatives Exchange (ICDX) causing market participants to not using ICDX futures prices as a reference. The participants actually use the price of the Rotterdam exchange for their transactions of buying and selling. Therefore, this study aims to analyze factors influencing olein prices and analyze olein prices integration by using Vector Error Correction Model (VECM) method. Results showed that exchange rates, interest rates, money supply, CPO prices, and Indonesia's GDP affect olein prices. In addition, there is an integration between the physical prices, futures prices, and world reference prices in the long term. Key words : Factors Affecting Price, Olein, Price Integration, VECM

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“…For yearly data (Panel A), besides the original type of a characteristic, the central transformations are the ztransformation, logarithmic growth, and the ratio to total production, according to e.g. Arango et al (2012), Coleman (2012), or Frankel (2008. In contrast to fundamental data, which are only available on a yearly basis, we obtain monthly data for financial figures in Panel B.…”

Section: Variables and Transformationsmentioning

confidence: 99%

Metals: resources or financial assets? A multivariate cross-sectional analysis

et al. 2016

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Metals are very important resources for industrial production, but recently they have attracted more and more attention from investors. While certainly industrial producers, consumers, and financial investors do have some influence on metal price development, the role of relevant price factors is not yet quite clear. Therefore, in this paper we examine the explanatory power of various fundamental factors and characteristics known from financial markets, specifically on the expected returns in a unique data sample of 30 metals. We applyto our knowledge for the first time in this contextthe widely accepted method of characteristicsorted portfolios, extended by the very recent method of two-way portfolio sorts as an alternative to classical multivariate regressions. This mostly non-parametric approach, combined with portfolio aggregation, provides very robust results. Our major finding is that the financial characteristics value and momentum have a very high predictive power for monthly returns of metal portfolios. Metal-specific fundamental factors like stocks, secondary production, apparent consumption, country concentration, mine production, or reserves perform depending on the interpretation moderately well or rather poorly, regarding some economically interpretable transformations and when using multivariate two-way sorts. Hence, from the perspective of expected returns, metals are predominantly assets, while fundamental metal-specific factors still play a non-negligible role. Thus, to a much lesser extent, metals can still be regarded as resources. Overall, the combination of financial characteristics and metal-specific fundamental factors yields the best results. With these robust results, we hope to contribute to a better understanding of metal prices and their underlying factors.

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Determinants of commodity prices

Cited by 35 publications

References 11 publications

Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day

Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day

Analisis Faktor Yang Mempengaruhi Harga Dan Integrasi Harga Olein

Metals: resources or financial assets? A multivariate cross-sectional analysis

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