A key determinant of commodity price Co-movement: The role of daily market liquidity

Daily price co-movement across different commodity classes and its key determinant are investigated in this paper. Using co-integration and Granger causality analysis, we identify a common liquidity factor which drives prices of five commodities (oil, silver, gold, corn, live cattle) to move along a common trend. When the market becomes more (less) liquid, all commodity prices tend to move up (down) in the same direction. As a result, such liquidity-driven price co-movement across different commodity classes is likely to generate aggregate price shocks and amplify inflation volatility. As a practical implication of our findings, policy makers ought to be able to draw valuable lessons from monitoring daily commodity liquidity dynamics as a timely bellwether for incipient inflation and to more effectively control inflation risk.     

Time–frequency relationship between US output with commodity and asset prices

Commodity and asset prices have a well-documented effect on economic growth as manifested through various channels. At the same time, the business cycle influences the commodity and asset prices. Whereas empirical evidence on the effect of commodity and asset prices on the long-run economic growth is ambiguous, most of the previous researches highlight a positive correlation in the short run. The aim of this article is to disentangle the short- and long-run co-movements between US historical business cycles and commodity and asset prices over the period 1859–2013. For this purpose, we use a time–frequency approach and we test the historical influence of oil, gold, housing and stock prices over the output growth. In contrast to other studies, we control for the effect of other prices and monetary conditions, using the wavelet partial coherency. In line with the previous works, we discover that co-movements between economic growth and commodity and assets prices manifest especially in the short run. We also find that stock returns and housing prices have a more powerful effect on the US economic growth rate than the oil and gold prices. The long-run co-movements are documented especially around the World War II. Finally, when controlling for the influence of the interest rate, inflation and other commodity and asset prices, co-movements become weaker in the short run. In general, the oil and housing prices lead the GDP growth, the US output leads the gold prices, while there is no clear causality direction between business cycle and stock prices.     

Bad volatility is not always bad: evidence from the commodity markets

ABSTRACT

Using exchange-traded fund (ETF) options data, we examine the predictive power of variance risk premium on returns of four commodities: crude oil, natural gas, gold and silver. We also analyze the predictive power of upside and downside variance risk premiums using a decomposition model conditional on the direction of the underlying market movement. We find that both the undecomposed and decomposed variance risk premiums are able to predict commodity prices. The decomposed variance risk premiums, however, outperform the undecomposed premium. The importance of upside and downside variance risk premiums differs across markets, related to hedging demand. In energy markets, both upside and downside premiums have strong predictive power, while in precious metal markets, only the upside premium is predictive.     

Global Liquidity and Commodity Prices

While monetary easing and increasing participation of financial institutions in commodity trading have enhanced the financialization of commodity markets, this paper investigates empirically whether the impact of global liquidity on commodity prices has grown since the crisis. For each commodity group, this paper uses a structural vector autoregression (SVAR) model to address the short‐run relationship between global liquidity and commodity prices. The key finding is that the effect of global liquidity on commodity prices becomes more salient since the global financial crisis. This paper also suggests a price‐based liquidity indicator has a greater explanatory power for the commodity price dynamics than monetary aggregates.     

Long-run waves or short-run fluctuations – what establishes the correlation between oil and food prices?

The strong correlation between food prices and energy prices has gained much attention in the public debate. In this article, we focus on the so-called excess co-movement, which is the correlation between crude oil price and the prices of food commodities after controlling for economic activity. We use a frequency domain Granger causality test to analyse short-run and long-run relationships between crude oil prices and prices of food commodities. For important biofuel inputs like maize, soybeans, rapeseed and EU sugar, we find evidence for long-run Granger causality in particular for the period after 2007. This supports the hypothesis that the increasing biofuel production creates the link between the prices of crude oil and food commodities. However, we also find short-run Granger causality for various food commodities. This result is more in line with herd behaviour or speculation in commodity markets.     

Global Determinants of the Gold Price: A Multivariate Cointegration Analysis

The present paper follows publications which have investigated the influence of global liquidity developments on commodity prices and asset price indices. It contributes to the literature by analyzing how global developments in money, output, and inflation can be related to developments in gold prices in a long‐run perspective. Applying a multivariate cointegration (CVAR) analysis, this study investigates long‐run relationships between these variables. The results suggest a significant influence of excess global liquidity on real gold prices and a co‐movement of real gold prices and global inflation.     

Are Commodity Prices Driven by Fundamentals?

Physical scarcity is hardly sufficient to explain commodity price swings. However, despite of clues of commodity market inefficiency in the last decade, excess volatility in commodity markets emerges only under strong assumptions. When we allow for non‐stationarity in commodity prices and time variation in commodity‐specific risk premia, evidence of commodity market inefficiency becomes significantly weaker. Moreover, there is some evidence of commodity‐specific regime changes in commodity markets, with negligible or even positive correlation between efficiency and market liquidity.     

Capital account liberalization and dynamic price discovery: evidence from Chinese cross-listed stocks

We analyse the effects of a recent financial reform (Shanghai-Hong Kong Stock Connect) that enables cross-market investment between Hong Kong and Shanghai stock exchanges. Using a VECM, we find that the reform announcement considerably narrows the equilibrium level of price disparity and strengthens the price comovement of shares that are cross-listed in both markets. The estimated equilibrium relationship is in support of the relative law of one price. We find that both markets adjust in response to a disequilibrium in price disparity, leading to a sizeable error correction activity. The Shanghai market contributes to approximately two-thirds of the price discovery process. Competition and informativeness of trading affect the relative role of price discovery in each market. Finally, the reform implementation reinforces the long-run cointegration relationship and strengthens the short-run price comovements of cross-listed stocks despite the widening price disparity during the period.     

The multi-market analysis of a housing price transmission model

In this article, we examine dynamic relationships among housing prices from four first-tier cities in China from December 2000 to May 2010 and present an equilibrium model of housing price in multi-markets. By explicitly incorporating and modelling endogenous price series in competing housing markets, our empirical model is able to capture the existence of long-run equilibrium relationships and important short-run dynamics and price structures such as price leadership, price transmission lag and asymmetric price responses. Such multi-market analysis has generalized implications and can easily be applied to analyse the pricing dynamics among other real estate markets in the world. Our major contribution lies in two aspects. First, we employ an Error-Correction Model (ECM) with Directed Acyclic Graphs (DAG) to study the price dynamics in the four largest and key housing markets in China. Second, we uncover a price transmission among these housing markets in China and provide an insightful understanding of price adjustment across markets. The revealed effective price transmission and high correlation among these different markets actually is not a good thing for a stable financial system and for the defence against price bubbles in the housing market.     

An investigation into the dynamic relationship between international and China’s crude oil prices

This article studies the dynamic relationship between international (WTI, Brent and Dubai) and domestic (Da Qing) crude oil prices in China using threshold cointegration method. We find evidence of a long-run equilibrium relationship between each pair of international and Da Qing oil prices, favouring the market integration hypothesis. We also estimate asymmetric adjustments under the momentum threshold autoregressive (M-TAR) specification in a TVECM, and the results show that adjustments to eliminate disequilibrium happen faster when oil price spread increases than when it decreases. The long-run and short-run Granger causality tests support the notion that China has influence on the international oil markets. The results imply that China should open up its domestic and imported oil markets, and also establish a well-functioning crude oil futures market, as they are essential for arbitrage and hedging strategies.     

Financial contagion and volatility spillover: An exploration into Indian commodity derivative market

This study measures the extent of financial contagion in the Indian asset markets. In specific it shows the contagion in Indian commodity derivative market vis-à-vis bond, foreign exchange, gold, and stock markets. Subsequently, directional volatility spillover among these asset markets, have been examined. Applying DCC-MGARCH method on daily return of commodity future price index and other asset markets for the period 2006–16, time varying correlation between commodity and other assets are estimated. The degree of financial contagion in commodity derivative market is found to be the largest with stock market and least with the gold market. A generalized VAR based volatility spillover estimation shows that commodity and stock markets are net transmitters of volatility while bond, foreign exchange and gold markets are the net receivers of volatility. Volatility is transmitted to commodity market only from the stock market. Such volatility spillover is found to have time varying nature, showing higher volatility spillover during the Global Financial Crisis and during the period of large rupee depreciation in 2013–14. These results have significant implication for optimal portfolio choice.     

Correlations and volatility spillovers across commodity and stock markets: Linking energies,food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets.     

国内外铜期货市场的价格联系

The purpose of this paper is to investigate the time varying relationships between the Chinese copper futures market and its London counterparts. Rolling correlation and rolling Granger causality test show that with the development of the Shanghai copper futures markets, it has stronger connections with its London counterpart and it plays more and more important role in the price discovery process. There is a long run relationship between the Shanghai futures exchanges (SHFE) and London Metals exchanges (LME) copper futures prices. The influence of LME on SHFE is greater than that of SHFE on LME. The research will shed light on the openness of the Chinese copper commodity markets and on the nature of cross-market information transmission.      

Are crude oil spot and futures prices cointegrated? Not always!

In previous studies, the cointegration relationships between crude oil spot and futures prices are confirmed based on Johansen (1988) test and vector error correction model (VECM). These conventional methods assume that the process of long-run equilibrium adjustment is linear. This paper revisits this topic employing nonlinear threshold VECM to take into account the nonlinear dynamics of equilibrium adjustment. Our results show that crude oil spot and futures prices are cointegrated only when the price differentials are larger than the threshold value. Moreover, we use a multi-frequency analysis based on low-pass filtering with different cut-off frequencies. The main findings indicate that the relationships between spot and futures prices are different between in the short-term and in the long-term. In the short-term, futures price plays the major role in the formation of long-run equilibrium (error correction mechanism). In the long-term, both spot and futures prices contribute to the dynamics of long-run equilibrium.     

Global commodity cycles and linkages: a FAVAR approach

In this article, we examine linkages across non-energy commodity price developments by means of a factor-augmented VAR model (FAVAR). From a set of non-energy commodity price series, we extract two factors, which we identify as common trends in metals and food prices. These factors are included in a FAVAR model together with selected macroeconomic variables, which have been associated with developments in commodity prices. Impulse response functions confirm that exchange rates and economic activity affect individual non-energy commodity prices, but we fail to find strong spillovers from oil to non-oil commodity prices or an impact of the interest rate. In addition, we find that individual commodity prices are affected by common trends captured by the food and metals factors.     

Price Limits, Information Acquisition, and Bid–ask Spreads: Theory and Evidence

A number of futures markets use price limits which, in effect, preclude trade from occurring at prices outside certain exogenous bounds. Noting that such markets are characterized by heterogeneously informed traders, whereas previous work on price limits assumes symmetrically informed traders, we examine the effects of price limits in a setting where market participants are asymmetrically informed. We find that imposing price limits generally lowers the quality of information acquired in equilibrium, but lowers bid–ask spreads as well. Thus, depending on the relative weights placed by society on liquidity versus price efficiency, there may exist a set of price limits that are most efficient in achieving a trade-off between liquidity and informational efficiency. We perform empirical tests of some implications of the model using cross-sectional data on price limits. We find that price limits are strongly negatively related to both price volatility and trading volume. Though other explanations for our empirical findings cannot be ruled out, these results are not inconsistent with the model's implication that price limits should be tighter for contracts which offer greater profit potential for informed traders.     

Equilibrium Effects of Superstition in the Housing Market

We investigate the interaction of product quality differentiation and consumer preference heterogeneity in durable goods markets, focusing on the effects of secondary market liquidity and consumer heterogeneity on equilibrium prices. We build an infinite‐horizon dynamic model of the apartments housing market that captures the above features. Some apartments are considered lucky, and some consumers are superstitious. Lucky apartments are valued more highly than non‐lucky ones only by superstitious consumers. Results show that the difference between the lucky apartment price and the non‐lucky apartment price becomes smaller when the secondary market becomes less liquid and when consumers’ preference heterogeneity becomes more persistent as opposed to time‐varying.     

Determinants of the premium in forward contracts

Whilst the benefits of forward contracting for goods and services have been extensively researched in terms of mitigating market power effects in spot markets, we analyse how the risk in spot price formation induces a counteracting premium in the contract prices. We consider and test a wide-ranging set of propositions, involving fundamental, behavioural, dynamic, market conduct and shock components, on a long data set from the most liquid of European electricity forward markets, the EEX. We show that part of what is conventionally regarded as the market price of risk in electricity is actually that of its underlying fuel commodity, gas; that market power has a double effect on prices, insofar as it increases spot prices and induces a forward premium; that oil price sentiment spills over and that the premium reacts to scarcity and the higher moments of spot price uncertainty. We observe that considerations of the scale and determinants of the forward premium are at least as important as the market power effects in spot market price formation when evaluating the efficiency of wholesale power trading.     

Feedback effects between credit ratings and financial markets

Credit rating agencies often make sharp adjustments in their pronouncements during times of stress in financial markets. These adjustments typically happen with a delay relative to shocks in market prices. Since prices convey information about what market participants are doing and thinking, it is likely that rating agencies take into account market prices when issuing their pronouncements.In order to understand the relationship between credit ratings and financial prices, we develop a model of debt roll-over in which rating agencies incorporate information publicly available in financial markets. We find that (1) rating agencies respond to market prices, i.e. nonfundamental price volatility can shift financing conditions from a low risk spread and high credit rating equilibrium to an equilibrium with high spread and low rating, and (2) rating agencies can anchor expectations about the equilibrium in financial markets, thus serving as an antidote to nonfundamental price volatility.     

Commodity price cycles and heterogeneous speculators: a STAR–GARCH model

We propose an empirical commodity market model with heterogeneous speculators. While the power of trend-extrapolating chartists is constant over time, the symmetric impact of stabilizing fundamentalists adjusts endogenously according to market circumstances: Using monthly data for various commodities such as cotton, sugar or zinc, our STAR–GARCH model indicates that their influence positively depends on the distance between the commodity price and its long-run equilibrium value. Fundamentalists seem to become more and more convinced that mean reversion will set in as the mispricing enlarges. Commodity price cycles may thus emerge due to the nonlinear interplay between different trader types. The paper represents the authors’ personal opinion and does not necessarily reflect the views of the Deutsche Bundesbank.