Facts and Fantasies about Commodity Futures Ten Years Later

Bhardwaj, Geetesh; Gorton, Gary; Rouwenhorst, Geert

doi:10.3386/w21243

Cited by 88 publications

(59 citation statements)

References 22 publications

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“…After sorting and ranking commodity futures using basis levels, Bhardwaj et al . () show that market returns are greater for those markets with a more positive (inverted) basis structure. Here we directly incorporate this sorting process into the following cross‐sectional regression:

R_{i, t} = α + {italicβ}_{1} {Position}_{i, t} + {italicβ}_{2} Basis {Rank}_{i, t - 1} + {italicε}_{t}

where R i,t is the return in commodity futures market i and period t , Position i , t is the percent change in the net long index position in market i during period t , and

Basis {Rank}_{i, t - 1}

is the basis rank at the start of period t for market i .…”

Section: Cross‐sectional Analysismentioning

confidence: 96%

“…Few such measures exist across commodity markets. However, recent research (Gorton et al ., ; Bhardwaj et al ., ) indicates that the ‘basis’ or term structure of the futures markets, an indicator of ‘scarcity’ or inventory levels across markets, is related to risk premiums. Put simply, futures markets that have more of an inverted market structure – nearby futures higher than deferred futures – will tend to have higher returns.…”

Section: Cross‐sectional Analysismentioning

confidence: 99%

“…() and Bhardwaj et al . (), the basis at time t is defined as:

{Basis}_{t} = (\frac{p_{t}^{1} - p_{t}^{2}}{p_{t}^{1}}) \times (\frac{T^{2} - T^{1}}{365}) \times 100

where

p_{t}^{1}

is the futures price of the first listed or nearest‐to‐expiration contract expiring at time T 1 and

p_{t}^{2}

is the futures price of the second listed contract expiring at T 2 , such that equation represents the basis as a percent per year. A positive basis in equation represents a futures market that is inverted and a negative basis is a normal carry or contango market.…”

Section: Cross‐sectional Analysismentioning

confidence: 99%

See 2 more Smart Citations

Bubbles, Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

Sanders¹,

Irwin²

2016

J Agricultural Economics

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The Masters Hypothesis suggests that long‐only index funds were the main cause of a massive increase in commodity prices in 2007–2008 and 2011–2012. Central to the Masters Hypothesis are three basic tenets: (i) long‐only commodity index funds were directly responsible for driving futures prices higher; (ii) the deviations from fundamental value were economically very large; (iii) the impact was pervasive across commodity futures markets. There has been a great deal of empirical research on the Masters Hypothesis and commodity market bubbles. However, surprisingly few studies have found evidence that directly support the main tenets of the Masters Hypothesis. Some have attributed the lack of supporting evidence to the low‐power of time‐series tests, market efficiency issues and a lack of conditioning variables within models. In this paper, we address each of these issues using updated data and new empirical approaches. Still, price behaviour consistent with the Masters Hypothesis is surprisingly difficult to find in the data. This is an important finding given the on‐going policy debate and regulations proposed or being implemented to limit speculative positions in these markets.

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R_{i, t} = α + {italicβ}_{1} {Position}_{i, t} + {italicβ}_{2} Basis {Rank}_{i, t - 1} + {italicε}_{t}

where R i,t is the return in commodity futures market i and period t , Position i , t is the percent change in the net long index position in market i during period t , and

Basis {Rank}_{i, t - 1}

is the basis rank at the start of period t for market i .…”

Section: Cross‐sectional Analysismentioning

confidence: 96%

Section: Cross‐sectional Analysismentioning

confidence: 99%

“…() and Bhardwaj et al . (), the basis at time t is defined as:

{Basis}_{t} = (\frac{p_{t}^{1} - p_{t}^{2}}{p_{t}^{1}}) \times (\frac{T^{2} - T^{1}}{365}) \times 100

where

p_{t}^{1}

is the futures price of the first listed or nearest‐to‐expiration contract expiring at time T 1 and

p_{t}^{2}

Section: Cross‐sectional Analysismentioning

confidence: 99%

See 1 more Smart Citation

Bubbles, Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

Sanders¹,

Irwin²

2016

J Agricultural Economics

View full text Add to dashboard Cite

show abstract

“…Several studies investigate the possible reasons behind the success or failure of exchange traded derivatives and in particular futures contracts (see Białkowski & Jakubowski, ; Garcia, Irwin, & Smith, ; Johnston & McConnell, ; Till, ; Webb, ). Although past studies point out several features of futures and related cash markets that increase the chance of success, the topic is the subject of debate, and Bhardwaj, Gorton and Rouwenhorst () argue that more research into the success and failure of futures contracts is needed. In this paper, we provide evidence that a previously unstudied aspect of futures markets—the underlying spot market index design—is a strong determinant of the hedging effectiveness of futures contracts and hedge ratio persistence over short to long hedging horizons.…”

Section: Introductionmentioning

confidence: 99%

Does the design of spot markets matter for the success of futures markets? Evidence from dairy futures

Białkowski

Koeman

2017

Journal of Futures Markets

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This study provides evidence of the importance of a well‐defined and functioning spot market for the success of the associated futures market. Our analysis of hedging effectiveness and hedge ratio persistence shows that none of the United States (US) spot market indices may be hedged effectively with the Chicago Mercantile Exchange nonfat dry milk futures at short hedging horizons, whereas the New Zealand (NZ) Stock Exchange whole milk powder futures contract is an effective hedge for the Global Dairy Trade spot pricing benchmark. Four important dimensions of spot market design are identified—timeliness, market‐based measurement, forward‐spot separation, and inclusiveness.

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“…http://www.ft.com/cms/s/0/a6ff2818-094c-11e5-8534-00144feabdc0.html, also the source for the second opening quote. Also see Bhardwaj, Gorton, and Rouwenhorst ().…”

mentioning

confidence: 99%

Benchmarking commodity investments

Blocher

Cooper

Molyboga

2017

Journal of Futures Markets

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While much is known about the financialization of commodities, less is known about how to profitably invest in commodities. We develop a four‐factor asset pricing model of commodity returns. Our four‐factor model prices both commodity spot and term risk premia in an intuitive manner related to investable portfolios. The straightforward construction of our factors is an improvement over previous models. Furthermore, our four‐factor model prices commodity risk premia using both sorted portfolios and risk adjusted alphas as benchmarks. Thus, we feel it is an appropriate benchmark to evaluate commodity investment vehicles.

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Facts and Fantasies about Commodity Futures Ten Years Later

Cited by 88 publications

References 22 publications

Bubbles, Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

Bubbles, Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

Does the design of spot markets matter for the success of futures markets? Evidence from dairy futures

Benchmarking commodity investments

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