The demise of commodity price agreements: the role of exchange rates and special interests

We derive the equilibrium joint distribution of exchange rate and commodity price in a two-country rational expectations model. The correlation between commodity price and exchange rate appears crucial for the stability of commodity markets. This result arises from the common practice to quote commodity prices in consuming countries' currency, which subjects producing countries to the currency risk. Welfare results of commodity price stabilization are obtained and facilitate the interpretation of the position taken by industrialized countries long opposed to international commodity agreements. We apply our model to the Philippines and investigate the potential effects of the International Sugar Agreement (ISA) on the various conditional volatilities of the model. We conclude on the relative ineffectiveness of these agreements in limiting fluctuations of sugar prices.     

Stock Prices and Exchange Rates in Australia: Are Commodity Prices the Missing Link?

There are still significant gaps in our knowledge of the relationship between stock prices and exchange rates; not least, the ambiguity about the sign of the coefficient linking them. One explanation which we explore in the Australian context in this paper is the omission of commodity prices. We show that a relationship which omits commodity prices performs poorly but, once commodity prices are added, our results are plausible and robust. We also throw light on the commodity‐currency issue: the link from the exchange rate to commodity prices is stronger and more consistent than that in the opposite direction.     

Commodity Prices and the Dynamics of Inflation in Commodity‐Exporting Nations: Evidence from Australia and Canada*

A commodity‐price boom is under way. What does this boom mean for inflation in countries with substantial net commodity exports? The answer depends on movements in commodity prices, changes in foreign exchange rates and the determinants of domestic price inflation. We estimate equations to provide indications of the strength of each of these forces for both Australia and Canada. The results show that world commodity prices move pro‐cyclically with world industrial production and that rates of change in commodity prices are directly related to domestic inflation in both countries. However, there is an offsetting impact of exchange‐rate changes, which is strong enough in the case of Australia, but not Canada, to substantially eliminate the inflationary impact of a commodity‐price boom.     

Long horizon predictability of exchange rates: Is it for real?

This paper reexamines recent results on the predictability of nominal exchange rate returns by means of fundamental models. Using a monthly sample of the post-Bretton Woods period we show that the in-sample fit between long-horizon exchange rate returns and various models is not significant if we correct for the persistence that is caused by overlapping data and spurious regression phenomena. The long horizon out-of-sample predictive power of the fundamental exchange rate models is found to be very weak. This is especially the case when we conduct the out-of-sample forecasting tests for a longer time span than that of earlier papers. We show that this failure in forecasting performance, resulting from extending the time span, is due to the absence of cointegration between exchange rates and structural exchange rate models. First version received: September 1997/final version received: November 1998     

Four harmonic cycles explain and predict commodity currencies' wide long term fluctuations

In theory and practice, it is difficult to accept a particular model of explanation and forecasting of exchange currencies as the literature review reveals. However, the currencies that are called commodity currencies, such as the Australian dollar are heavily influenced by commodity prices cycles, and hence they might be easier to analyze and predict. We investigate the possibility that the Australian dollar is primarily determined by a handful of harmonic cycles which in turn are based not only on commodity prices cycles but also on commodity production cycles and in general on economic cycles. In this way we can get a very good fit of the relevant data and good out-of-sample forecasts. We cross check these results by referring to the main issues involved, such as fundamentals, short and long cycles, and so on. In addition, our analysis, forecasting ability, and conclusions still hold for three more commodity currencies examined here: New Zealand's dollar, Canada's dollar, and Norway's krone.     

Relationship between oil price and exchange rate by FDA and copula

This article investigates the relationship between daily crude oil prices and exchange rates. Functional data analysis is used to show the clustering pattern of exchange rates and oil prices over the time period through high dimensional visualizations. We select exchange rates for important currencies related to crude oil prices by using the objective Bayesian variable selection method. The selected sample data exhibits non-normal distribution with fat tails and skewness. Under the non-normality of the return series, we use copula functions that do not require to assume the bivariate normality to consider marginal distribution. In particular, our study applies the popular and powerful statistical methods such as Gaussian copula partial correlations and Gaussian copula marginal regression. We find evidence of significant dependence for all considered pairs, except for the Mexican peso-Brent. Our empirical results also show that the rise in the West Texas Intermediate (WTI) oil price returns is associated with a depreciation of the US dollar.     

The relationship between agricultural commodity prices,crude oil prices and US dollar exchange rates: a panel VAR approach and causality analysis

This study examines the relationship between crude oil prices, US dollar exchange rates and 30 selected international agricultural prices and five international fertilizer prices in a panel framework. The study uses panel VAR methods and Granger causality tests on panel data sets of agricultural commodity prices (as well as specific agricultural commodity sub-groups) and fertilizer prices with monthly observations of the period from June 1983 to June 2013. The empirical results of the present study indicate that crude oil prices as well as US dollar exchange rates affect international agricultural commodity and fertilizer prices. Furthermore, contrary to the findings of several studies in the literature, the present study supports bidirectional panel causality effects between crude oil prices and international agricultural prices as well as between US exchange rates and international agricultural prices.     

Autoregressive conditional durations: An application to the Surinamese dollar versus the US dollar exchange rate

The parallel market nominal exchange rate of the United States dollar vis-à-vis the Surinamese dollar (USD/SRD) exhibited periods of severe volatility which were often followed by episodes of stability, usually at a cost of sharp depreciations. This study seeks to model this exchange rate using autoregressive conditional duration models. These models are suitable for modelling events occurring with irregular intervals. Exchange rates in developing countries have distinct features compared to exchange rates in countries with well-established and accessible financial markets. A key feature is that for these developing countries, exchange rates only occasionally experience jumps. Our findings suggest that past exchange rate changes appear to be a significant driver of future exchange rate jumps. Furthermore, our results show that money, international reserves, and commodity prices can explain jumps in the market USD/SRD exchange rate.     

RELATIONSHIPS AMONG STRATEGIC COMMODITIES AND WITH FINANCIAL VARIABLES: A NEW LOOK

We examine the comovements among the prices of four strategic commodities that have long, adequate daily series: oil, gold, silver, and copper as a group. We also explore their causal relationships with two commodity-relevant macrofinancial variables: interest and exchange rates as an expanded group to shed some light on the prediction behaviors of those individual commodity prices relative to the selected financial variables. In the expanded group, the selected interest rate can provide a transmission link between commodity prices and the dollar exchange rate. The results and their policy implications are discussed at length . ( JEL C51, E27, Q43)     

Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract

This study applies linear and nonlinear Granger causality tests to examine the dynamic relation between London Metal Exchange (LME) cash prices and three possible predictors. The analysis uses matched quarterly inventory, UK Treasury bill interest rates, futures prices and cash prices for the commodity lead traded on the LME. The effects of cointegration on both linear and nonlinear Granger causality tests is also examined. When cointegration is not modelled, evidence is found of both linear and nonlinear causality between cash prices and analysed predictor variables. However, after controlling for cointegration, evidence of significant nonlinear causality is no longer found. These results contribute to the empirical literature on commodity price forecasting by highlighting the relationship between cointegration and detectable linear and nonlinear causality. The importance of interest rate and inventory as well as futures price in forecasting cash prices is also illustrated. Failure to detect significant nonlinearity after controlling for cointegration may also go some way to explaining the reason for the disappointing forecasting performances of many nonlinear models in the general finance literature. It may be that the variables are correct, but the functional form is overly complex and a standard VAR or VECM may often apply.     

The dynamic causality between commodity prices,inflation and output in China: a bootstrap rolling window approach

In this article, we empirically study the time-varying bilateral causality between commodity prices, inflation and output in China. We first perform a series of parameter stability tests and find strong evidence of instability in the parameters estimated for Granger causality tests. We then use the bootstrap rolling window approach to test the causality and find that the causality from commodity prices to both inflation and output is time-varying in the entire sample period and asymmetric in different phases of the business cycle. We also find evidence of the causality from both inflation and output to commodity prices in certain sub-periods. Further discussion on the cost-price mechanism through which the economy fluctuates cyclically suggests that the dynamic causality between commodity prices and inflation contributes to understanding the nature of economic fluctuations and to forecasting economic crises. Overall, our results provide a new perspective to disentangle economic fluctuations.     

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.     

Commodity currencies and commodity prices: modelling static and time-varying dependence

This article employs the copula approach to study the relationship between exchange rates and commodity prices for large commodity exporters. Using data for the nominal exchange rates of four commodity currencies (Australian, Canadian and New Zealand dollars, and Norwegian krone) against the US dollar and the relevant country-specific commodity price indices, constructed on a daily basis, we find (1) a positive dependence between the values of commodity currencies and commodity indices, i.e. a commodity index increases when a respective currency appreciates and provides several explanations for this finding; (2) no major asymmetries in the tail dependence for most pairs of exchange rates and commodity indices and (3) a pronounced increase in the time-varying tail dependence following the global financial crisis.     

Testing for weak-form efficiency of crude palm oil spot and future markets: new evidence from a GARCH unit root test with multiple structural breaks

There is a sizeable literature that tests for weak-form efficiency in commodity and energy spot and future prices. While many studies now allow for multiple structural breaks to address the criticism that conventional unit root tests have low power to reject the unit root null in the presence of structural change, the extant literature overlooks the fact that conventional unit root tests are biased in the presence of conditional heteroscedasticity. We apply a recently developed generalized autoregressive conditional heteroscedasticity (GARCH) unit root test with multiple structural breaks to crude palm oil spot and future prices and find much more evidence against weak-form efficiency than that found using tests that fail to allow for conditional heteroscedasticity. Our results point to the importance of allowing for heteroscedasticity when testing for efficiency in commodity and energy spot and future prices.     

An empirical examination of long-run purchasing power parity as theory of international commodity arbitrage

An empirical analysis of long-run purchasing power parity (PPP) as a theory of international commodity arbitrage between UK and US prices and the sterling/US dollar exchange rate for the period 1975–1980 is presented. Econometric techniques concerning the cointegration of economic time series are applied to a sample of 35 manufactured commodities which in 1977 constituted approximately a quarter of the net output of all manufacturing industry in Great Britain. Our results are extremely unfavourable to the PPP hypothesis as a stable long-run proportionality between exchange rates and disaggregated 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.     

Do bookmakers possess superior skills to bettors in predicting outcomes?

In this paper we test the hypothesis that bookmakers display superior skills to bettors in predicting the outcome of sporting events by using matched data from traditional bookmaking and person-to-person exchanges. Employing a conditional logistic regression model on horse racing data from the UK we find that, in high liquidity betting markets, betting exchange odds have more predictive value than the corresponding bookmaker odds. To control for potential spillovers between the two markets, we repeat the analysis for cases where prices diverge significantly. Once again, exchange odds yield more valuable information concerning race outcomes than the bookmaker equivalents.     

Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory

This paper employs a multi-equation model approach to consider three statistic problems (heteroskedasticity, endogeneity and persistency), which are sources of bias and inefficiency in the predictive regression models. This paper applied the residual income valuation model (RIM) proposed by Ohlson (1995) to forecast stock prices for Taiwan three sectors. We compare relative forecasting accuracy of vector error correction model (VECM) with the vector autoregressive model (VAR) as well as OLS and RW models used in the prior studies. We conduct out-of-sample forecasting and employ two instruments to assess forecasting performance. Our empirical results suggest that the VECM statistically outperforms other three models in forecasting stock prices. When forecasting horizons extend longer, VECM produces smaller forecasting errors and performs substantially better than VAR, suggesting that the ability of VECM to improve VAR forecast accuracy is stronger with longer horizons. These findings imply that an error correction term (ECT) of the VECM contributes to improving forecast accuracy of stock prices. Our economic significance analyses and robustness tests for different data frequency are in favor of the superiority of VECM estimator.     

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.     

Volatility forecasting of exchange rate by quantile regression

Exchange rates are known to have irregular return patterns; not only their return volatilities but the distribution functions themselves vary with time. Quantile regression allows one to predict the volatility of time series without assuming an explicit form for the underlying distribution. This study presents an approach to exchange rate volatility forecasting by quantile regression utilizing a uniformly spaced series of estimated quantiles. Based on empirical evidence of nine exchange rate series, using 19 years of daily data, the adopted approach generally produces more reliable volatility forecasts than other key methods.