No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Rational Expectations, Risk and Efficiency in the London Metal Exchange: An Empirical Analysis
Applied Economics
Abstract
There now exists a number of studies which reject efficiency of the London Metal Exchange, as a joint null hypothesis of rational expectations and risk neutrality. In this paper, we investigate the presence of time-varying risk premia in a number of metal price series, conditional on the assumption of rationality. Our findings include evidence to suggest that forward prices contain information on future spot prices over and above the information contained in current spot prices; that there is some evidence of time-varying premia in the forward prices for tin and zinc; and that the behaviour of these premia are intuitively plausible-in particular there appears to be significant covariation between risk premia and the expected spot price change.
... Furthermore, authors have cited the lack of analysis of various issues in commodity markets, relative to the importance of the exchange to world markets in industrially used metals, as a reason for analysing LME markets. For example, the fact that there is little research in metal markets on time-varying risk premia is noted in MacDonald and Taylor (1989). More generally, Hsieh and Kulatilaka (1982) note that metals have no discontinuities in production and are not subject to such seasonal patterns commonly observed in agricultural commodities. ...
... Several papers broke their samples into sub-samples to model structural change or to test hypotheses relating to different time periods in the data. The largest number of sub-samples used in any one paper is 15 (Bracker and Smith, 1999), but two or Fama and French (1988), Chang et al. (1990), MacDonald and Taylor (1989), Sephton and Cochrane (1990a,b) and Slade (1991)]. ...
This article evaluates the significance of the empirical models and the distributional properties of prices in non-ferrous metal spots and futures markets published in leading refereed economics and finance journals between 1980 and 2002. The survey focuses on econometric analyses of pricing and return models applied to exchange-based spot and futures markets for the main industrially used non-ferrous metals, namely aluminium, copper, lead, nickel, tin and zinc. Published empirical research is evaluated in the light of the type of contract examined, frequency of data used, choice of both dependent and explanatory variables, use of proxy variables, type of model chosen, economic hypotheses tested, methods of estimation and calculation of SEs for inference, reported descriptive statistics, use of diagnostic tests of auxiliary assumptions, use of nested and non-nested tests, use of information criteria and empirical implications for non-ferrous metals. Copyright Blackwell Publishers Ltd, 2004.
... En este capítulo se han analizado las características de las series de precios spot y de contratos futuros de cobre y petróleo, además de la presencia de cointegración entre los precios spot y cada uno de los contratos futuros. Se encuentra evidencia a favor de la no estacionariedad de las series y de la relación de cointegración entre el precio de los contratos spot y futuros, lo que refuerza anteriores conclusiones de la literatura (Chowdhury, 1991;Krehbiel y Adkins, 1993;Macdonald y Taylor, 1989;Moore y Cullen, 1995). El análisis llega a este mismo resultado para cada uno de los contratos spot y futuros de cobre y petróleo. ...
... where I t-1 is the information set available at time t-1, P t is the actual price at time t, P*t is the expected price which is based on the information set I t-1 , so P*t, is uncorrelated with ut, and additionally the forecast error Pt-P*t is uncorrelated with variables in the information sel I t-1 . Thus, price changes and consequently stock returns, under the assumptions of a constant equilibrium return and risk neutrality, are uncorrelated with variables in the information set I t-1 and empirical tests for market efficiency usually examine the above proposition, Cootner (1962), Fama (1965), Gowland and Baker (1970), Cutler, Poterba and Summers (1989), MacDonald and Taylor (1988 Taylor ( , 1989). Fama (1970), distinguished three types of market efficiency. ...
The purpose of this study is to investigate whether it is possible to predict stock market returns with the use of macroeconomic variables in the Athens Stock Exchange. The emerging stock market of Greece, is a small and relatively underinvestigated market. Hence, there is a possibility that a predictive model may exist for stock returns, violating the Efficient Market Hypothesis (E.M.H.) which states that stock market returns cannot be predicted. In the international literature there is a wide variety of methods used for predictive purposes. In this study we have used cointegration analysis, and as explanatory variables some macroe conomic factors which are believed by economists and market practitioners, to influence stock returns. Namely the macroeconomic predictive variables are, the inflation rate measured by the Consumer Price Index, the M3 measure of money supply and the exchange rate of US Dollar/Greek Drachmae (JEL G14).
... In studies relating directly to the market tor metals, Hsieh and Kulatilaka (1982), using monthly data on LME forward contracts from January 1970 to September 1980, reported average risk premia of 2.8% for copper, 17% for tin, 12.7% for zinc, and 16% for lead. In a later study, MacDonald and Taylor (1989) reported evidence for a "time-varying premium" in the forward prices for tin and zinc. ...
Storage and Commodity Markets is primarily a work of economic theory, concerned with how the capability to store a surplus affects the prices and production of commodities. Its focus on the behaviour, over time, of aggregate stockpiles provides insights into such questions as how much a country should store out of its current supply of food considering the uncertainty in future harvests. Related topics covered include whether storage or international trade is a more effective buffer and whether stockpiles are more useful in raw or processed form. Several chapters are devoted to analysing such government programmes as price bands, buffer stocks, and strategic reserves. This material is in the domain of applied welfare analysis with public finance. Because the theory presented is sufficiently general, it should be of interest to macroeconomists studying aggregate inventories or savings and to those in operations research studying inventory and pricing policies of large firms.
Previous research on price determination for non-ferrous metals at the London Metal Exchange (LME) suffers from three limitations: first it has employed single equation methods only, which cannot explain the simultaneous determination of spot and futures prices; second, by focusing on current and lagged prices, previous research does not analyse the effect on price determination of critical variables such as expectations, consumption and inventories; third, the outcome of prior research regarding market efficiency is ambiguous.
This paper, which addresses these issues, develops a simultaneous model of the copper market at the LME, with representation of the activities of hedgers, speculators and consumers. This model produces post-sample forecasts of the spot price which outperform conventional benchmarks, thus providing evidence against the efficient market hypothesis. Model-derived forecasts are employed as the foundation of a trading program which produces risk-adjusted profits (net of commission costs) for holding periods of one week and one month, thus fulfilling the ‘sufficient condition’ for market inefficiency.
This study, therefore, provides new insights into price determination on the LME copper market, and resolves the ambiguity of previous research regarding the efficiency of that market. This is the first application of the model forecasting approach to the question of performance of the market for copper.
The use of futures prices to predict commodity cash prices is important both to practitioners and researchers yet the literature provides conflicting results on the ability of futures prices to predict cash prices. Brenner and Kroner [Journal of Financial and Quantitative Analysis 30 (1995) 23] argue that if the cost of carry model applies to commodity futures pricing then current futures prices may not accurately predict subsequent cash prices. Inventory, cash price return variance, cash price return first order auto-correlation and interest rates are used to proxy carrying costs in a test of the ability of commodity futures prices to predict cash prices. Various predictive models relating futures price to cash price are described, including univariate and multivariate error correction models. London Metal Exchange (LME) lead cash prices, lead futures prices, lead inventory and UK treasury bill rates are collected over the period 1964 to 1995. Analysis of this data confirms the importance of the cost of carry model elements as well as futures price in forecasting cash prices.
Copper futures returns are characterized by negative skewness and excess kurtosis. Research has not yet examined this nonnormality, which contributes to their volatility. To date little attention has been paid to the modeling of these series. Therefore, the purpose of this paper is to (i) detect alternating subperiods of volatility by using a method that uses an iterated cumulative sum of squares (ICSS) algorithm to identify breakpoints in the series; and (ii) compare the ability of five models (the random walk, GARCH, EGARCH, AGARCH, and the GJR model) to capture the volatility within each ICSS identified subperiod. These tests were applied to two copper futures series (open to close and close to close prices). Results indicate that the ranking (in terms of the root mean square error) is similar for both series. That is, the GARCH or EGARCH model rank first and second, depending on the series, followed by the GJR model. AGARCH and the random walk models perform poorly.© 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 79–100, 1999
A brief discussion of the efficiency of the LME's copper market. The theoretical underpinnings of the efficient market hypothesis are described and recent econometric evidence reviewed. Despite a lack of consistency in the findings, it is concluded that the market probably is efficient.
The London Metal Exchange (LME) is a centre for spot and futures trading in the main industrially-used non-ferrous metals. In this paper, the market for 3-month LME copper futures contracts is analysed. The risk premium hypothesis and the cost-of-carry (COC) model are the standard theoretical models for pricing futures contracts, but these two models have rarely been estimated within a unified framework for metals futures. Single equation versions of the risk premium hypothesis and the COC model are nested within a general model. If the spot price, futures price, interest rate and stock level variables contain stochastic trends, long-run versions of the general model can be estimated within the cointegration framework. The long-run pricing models are estimated using daily LME copper price data over the period 3 January 1989 to 30 September 1998. Likelihood ratio tests are used to test restrictions on the general model.
The purpose of this article is to contribute to the research on informationally linked markets by investigating the relationships between the Chinese copper futures market and its London counterparts. There is a long run relationship between the Shanghai Futures Exchanges (SFE) with London Metals Exchange (LME) copper futures prices. Furthermore, we find that three regime Markov switching model with changing intercept and variance turns out to be good description of the data. The influence of LME on SFE is bigger than that of SFE on LME.
The reliance on primary commodity exports posits a weighty problem for a large number of low-income less-developed countries, which is further aggravated by the erratic behaviour of commodity prices. Rational expectations competitive storage models conjecture that storage behaviour engenders nonlinear commodity pricing processes. Motivated by theoretical considerations state of the art nonlinear time series models are put to the task of forecasting an important subset of primary commodities, base metals. Nonlinear models, especially feedforward artificial neural networks, meet their mettle and hence may prove useful tools from a commodity-policy standpoint by providing at least some degree of visibility.
A recent addition to the ARCH family of econometric models was introduced by Ding and co-workers wherein the power term by which the data is transformed was estimated within the model rather than being imposed by the researcher. This paper considers the ability of the Power GARCH class of models to capture the stylized features of volatility in a range of commodity futures prices traded on the London Metals Exchange (LME). The results of this procedure suggest that asymmetric effects are not generally present in the LME futures data. Further, unlike stock market data which is well described by the model, futures data is not as well described by the APGARCH model. Nested within the APGARCH model are several other models from the ARCH family. This paper uses the standard log likelihood procedure to conduct pairwise comparisons of the relative merits of each and the results suggest that it is the Taylor GARCH model which performs best.
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.
Recent evidence suggests that some markets on the London Metal Exchange do not exhibit the major characteristics of efficient markets: rationality and risk neutrality. In this note we ilustrate several shortcomings of recent work in this area. We suggest that one can be confident that the tin market exhibited a risk premium, that is, was inefficient, between 1976 and 1985. Reliable results on the efficiency of the lead, copper, aluminium, and nickel markets escape the Fama approach to testing the efficient markets hypothesis as it is currently employed.
During the last few years there has been growing evidence against the Efficient Market Hypothesis. In this study we investigate the hypothesis using stock prices of common and preferred stocks from the Athens Stock Exchange. In Greece, preferred shares are regarded as part of the equity capital of the Greek companies and they are not considered as part of the borrowed funds. Under the Efficient Market Hypothesis their price behaviour, as far as the speed of adjustment to news is concerned, should be the same. However, our empirical evidence contradicts the above proposition. It seems that in the Greek market there are factors, other than news, which influence the price behaviour of the two categories of stocks.
The London Metal Exchange (LME) is the most important centre for spot and futures trading in the main industrially-used non-ferrous metals. In this study, data on 3-month futures contracts for aluminium, aluminium alloy, copper, lead, nickel, tin, and zinc are analysed. The risk premium hypothesis and the cost-of-carry model are the standard theoretical models for pricing futures contracts, but these two models have rarely been estimated within a unified framework for metals futures. Single equation versions of the risk premium hypothesis and the cost-of-carry model are nested within a more general model. If the spot price, futures price, interest rate, and stock level variables contain stochastic trends, long run versions of the general model can be estimated within a cointegration framework. Various long run pricing models are estimated using daily LME price data for the period 1 February 1986 to 30 September 1998. Likelihood ratio tests are used to test restrictions on the general model to examine the validity of alternative nested specifications.
Using daily settlement prices for a range of real and financial futures over the period 6 April 1981-31 October 1995, this paper considers the extent to which, ex post, asset prices depart from random behaviour and investigates the efficiency of the markets within which the prices of the assets are determined. Our findings suggest, first, that there would appear to be substantial departures from randomness across markets. Second, the characteristics of the reported departures from randomness differ between markets. Third, for six of the nine assets analysed we found some evidence to suggest rejection of semi-strong market efficiency. Copyright @ 1998 by John Wiley & Sons, Ltd. All rights reserved.
In this note we examine the market efficiency hypothesis with respect to six metals traded on the London Metal Exchange (LME). Using overlapping data and both single and multimarket models, we find evidence contradictory to the tenet that the LME is an efficient market.
This paper examines the proposition that forward rates are unbiased predictors of future spot rates for base metal prices on the London Metal Exchange. The analysis is complicated by the fact that the data are sampled more frequently than the life of the forward contracts. Though the implications of this for stationary inference are well known, it has not yet been addressed within the context of unit root econometrics. This is explored and an estimation and testing strategy is proposed. The results are surprisingly favorable to the unbiasedness proposition. Copyright 1995 by Blackwell Publishers Ltd and The Victoria University of Manchester
This paper represents the first results of a continuing project attempting both to describe and to explain yield and price volatility in asset markets in the UK and in other major industrialised countries. This paper confines itself to the first part of the project, using relatively high frequency weekly data to describe the volatility in the UK gilts, interbank, foreign exchange and share markets since the mid-1960s. One reason for interest in the volatility of these markets is, as with interest in the variance of inflation, because of the cost imposed on risk averse agents by increased variability; while even risk neutral agents will face higher costs in a more variable market, if the higher volatility reduces their ability to forecast the mean of the process.
By considering the model generating the sum of two or more series, it is shown that the mixed ARMA model is the one most likely to occur. As most economic series are both aggregates and are measured with error it follows that such mixed models will often be found in practice. If such a model is found, the possibility of resolving the series into simple components is considered both theoretically and for simulated data.
In this paper the three approaches available to test the hypothesis that the futures price is an unbiased predictor of future spot prices are utilized to analyze the ‘efficiency’ of the London Metal Exchange for the period January 1975–December 1983. The first technique uses non-overlapping observation and derives a test of this hypothesis using OLS. The second uses overlapping data and models explicitly the moving average process in the error structure using ARMA procedures. The third uses a FIML technique to estimate a bivariate stochastic stationary process of the spot and futures prices and tests the unbiased predictor hypothesis in the form of complex non-linear cross-equation restrictions. The results conform to the predictions of the unbiased predictor hypothesis regardless of the methodology and/or data employed.
When adjusted for variation through time in expected premiums, the forward rates of interest that are implicit in Treasury Bill prices contain assessments of expected future spot rates of interest that are about as good as those that can be obtained from the information in past spot rates. Moreover, in setting bill prices and forward rates, the market reacts appropriately to the negative autocorrelation in monthly changes in the spot rate and to changes through time in the degree of this autocorrelation. This evidence is consistent with the market efficiency proposition that in setting bill prices, the market correctly uses the information in past spot rates.
This paper presents a regression approach to measuring the information in forward interest rates about time varying premiums and future spot interest rates. Like earlier work, the regressions identify variation in the expected premiums on longer-maturity Treasury bills. The more novel evidence concerns the forecasts of future spot rates in forward rates. The regressions provide evidence that the one-month forward rate has power to predict the spot rate one month ahead. During periods preceding 1974, forward rates have reliable forecast power for one-month spot rates up to five months in the future.
We investigate the existence of a risk premium in the foreign exchange market, based on the conditional variance of market forecast errors. The forecast errors are assumed to follow the ARCH process introduced by Engle (1982). Estimation and diagnostic testing of the model are discussed, and results are presented for the currencies of the United Kingdom, France, Germany, Japan and Switzerland.
Most studies of the efficiency of the foreign exchange market focus on a single maturity — usually a one month forward exchange rate. However, one observes that forward contracts of many maturities are simultaneously traded in the foreign exchange market. The hypothesis that the foreign exchange market uses all available information has implications for the joint behavior of forward exchange rates of various maturities. This paper proposes an equilibrium theory of the term structure of the forward premium. The model is tested using data on the German and Canadian exchange rates; the results indicate that the data are consistent with the theory for Germany and inconsistent with the theory for Canada.
There is a general consensus that forward exchange rates have little if any power as forecasts of future spot exchange rates. There is less agreement on whether forward rates contain time varying premiums. Conditional on the hypothesis that the forward market is efficient or rational, this paper finds that both components of forward rates vary through time. Moreover, most of the variation in forward rates is variation in premium, and the premium and expected future spot rate components of forward rates are negatively correlated.
Application of some advances in econometrics (in the theory of cointegrated vector autoregressive models) enables us to deal effectively with two problems in rational-expectations, present-valu e models: nonstationarity of time series and incomplete data on infor mation of market participants. With U.S. data, the authors find some relatively encouraging new results for the rational-expectations theo ry of the term structure and some puzzling results for the present-va lue model of stock prices. Copyright 1987 by University of Chicago Press.
This paper examines the hypothesis that the expected rate of return to speculation in the forward foreign exchange market is zero; that is, the logarithm of the forward exchange rate is the market's conditional expectation of the logarithm of the future spot rate. A new computationally tractable econometric methodology for examining restrictions on a k-step-ahead forecasting equation is employed. Using data sampled more finely than the forecast interval, we are able to reject the simple market efficiency hypothesis for exchange rates from the 1970s and the 1920s. For the modern experience, the tests are also inconsistent with several alternative hypotheses which typically characterize the relationship between spot and forward exchange rates.
The hypothesis that forward prices are the best unbiased forecast of future spot prices is often presented in the economic and financial analysis of futures markets. This paper considers the hypothesis independently of its implications for rational expectations or market efficiency and in order to stress this fact, the term "speculative efficiency" is used to characterize the state envisaged under the hypothesis. If a market is subject to efficient speculation, the supply of speculative funds is infinitely elastic at the forward price that is equal to the expected future spot price. The expected future spot price is a market price determined as the solution to the underlying rational expectations macroeconomic model. Although the paper is primarily concerned with testing this hypothesis in the foreign exchange market, the methodology introduced in the paper is of general application to all futures markets.
Future prices are rationally formed current prices relating to later delivery dates, and they are not forecasts of subsequent spot prices. Yet, if all available information, including economic agents' expectations, is fully taken into account in the price formation process, then both current spot and futures prices may be regarded as market anticipations of subsequent spot prices. This paper explores the hypothesis that futures prices (and spot) are predictors of subsequent spot prices in this sense. It assesses the predictive performance of futures prices for four non-ferrous metals traded on the London Metal Exchange using a simple linear model estimated by both ordinary least squres and instrumental variable estimators. Significant differences are found as between copper, zinc tin and lead. The paper begins with a discussion of the feasibility conditions for futures trading and the functions of futures markets, including a detailed review of the forward pricing function.
Value-at-Risk measures the potential loss on a portfolio, where the potential loss is linked directly to the probability of large, adverse movements in market prices. This paper considers four classes of Value-at-Risk model: variance-covariance models; historical-simulation models; Monte-Carlo simulation models; and extreme-value estimation models. Using portfolio data from all Australian banks over the past ten years, we compare the performance of specific implementations of each of the four Value-at-Risk model classes. Performance assessment is based on a range of measures that address the conservatism, accuracy and efficiency of each model.
The relationship between cointegration and error correction models, first suggested by Granger, is here extended and used to develop estimation procedures, tests, and empirical examples. A vector of time series is said to be cointegrated with cointegrating vector a if each element is stationary only after differencing while linear combinations a8xt are themselves stationary. A representation theorem connects the moving average , autoregressive, and error correction representations for cointegrated systems. A simple but asymptotically efficient two-step estimator is proposed and applied. Tests for cointegration are suggested and examined by Monte Carlo simulation. A series of examples are presented. Copyright 1987 by The Econometric Society.
This paper studies estimators that make sample analogues of population orthogonality conditions close to zero. Strong consistency and asymptotic normality of such estimators is established under the assumption that the observable variables are stationary and ergodic. Since many linear and nonlinear econometric estimators reside within the class of estimators studied in this paper, a convenient summary of the large sample properties of these estimators, including some whose large sample properties have not heretofore been discussed, is provided.
In this paper, the authors argue that survey data on exchange-rate expectations is especially useful fo r testing whether the forward market for foreign exchange is efficien t, since it obviates the need to impose a joint hypothesis on a stand ard efficiency equation. They utilize such data for this purpose for the deutsche mark-U.S. dollar exchange rate over the period 1985.2 to 1986.4. Copyright 1988 by Blackwell Publishing Ltd
This paper tests whether forward prices equal the traders' expectations of the future spot prices at maturity, under two different models of expectations formation: full information rational expectations and incomplete information mechanical forecasting rule. The tests are performed, over the period January 1970 through September 1980, on the forward markets for the primary metals—copper, tin, lead, and zinc‐traded in the London Metals Exchange. We find evidence consistent with the existence of time varying risk premia.