This paper examines the dynamic linkages between oil prices and the stock market. Prior work argues that daily oil futures price changes and the S&P 500 stock index movements are not related. This conclusion could be due to the fact that only linear linkages have been examined. Relying on nonlinear causality tests, this study provides evidence that oil shocks affect stock index returns, which is consistent with the documented influence of oil on economic output. Moreover, the study finds that the linkage between oil prices and the stock market was stronger in the 1990s.

https://www.csb.uncw.edu/people/cinerc/Courses%20Web%20Page/Research/energy%20shocks%20and%20financial%20markets.pdf

Energy Shocks and Financial Markets: Nonlinear Linkages

This paper investigates the causal relations between stock return and volume based on quantile regressions. We first define Granger non-causality in all quantiles and propose testing non-causality by a sup-Wald test. Such a test is consistent against any deviation from non-causality in distribution, as opposed to the existing tests that check only non-causality in certain moment. This test is readily extended to test non-causality in different quantile ranges. In the empirical studies of three major stock market indices, we find that the causal effects of volume on return are usually heterogeneous across quantiles and those of return on volume are more stable. In particular, the quantile causal effects of volume on return exhibit a spectrum of (symmetric) V-shape relations so that the dispersion of return distribution increases with lagged volume. This is an alternative evidence that volume has a positive effect on return volatility. Moreover, the inclusion of the squares of lagged returns in the model may weaken the quantile causal effects of volume on return but does not affect the causality per se.

/pdf/causality-in-quantiles-and-dynamic-stock-return-volume-2zw52krrzb.pdf

Causality in quantiles and dynamic stock return–volume relations

Market efficiency and unbiasedness are tested in four agricultural commodity futures markets - live cattle, hogs, corn, and soybean meal - using cointegration and error correction models with GQARCH-in-mean processes. Results indicate each market is unbiased in the long run, although cattle, hogs and corn futures markets exhibit short-run inefficiencies and pricing biases. Models for cattle and corn outperform futures prices in out-of-sample forecasting. Results also suggest short-run time-varying risk premiums in cattle and hog futures markets.

/pdf/market-efficiency-in-agricultural-futures-markets-8jdne0fhvd.pdf

Market efficiency in agricultural futures markets

Nonlinear dynamics of daily futures prices: Conditional heteroskedasticity or chaos?

The ability of futures markets to predict subsequent spot prices has been a controversial topic for a number of years. Empirical evidence to date is mixed; for any given market, some studies find evidence of efficiency, others of inefficiency. In part, these apparently conflicting findings reflect differences in the time periods analyzed and the methods chosen for testing. A limitation of existing tests is the classification of markets as either efficient or inefficient with no assessment of the degree to which efficiency is present. This article presents tests for unbiasedness and efficiency across a range of commodity and financial futures markets, using a cointegration methodology, and develops a measure of relative efficiency. In general, the findings suggest that spot and futures prices are cointegrated with a slope coefficient that is close to unity, so that the postulated long-run relationship is accepted. However, there is evidence that the long-run relationship does not hold in the short run; specifically, changes in the spot price are explained by lagged differences in spot and futures prices as well as by the basis. This suggests that market inefficiencies exist in the sense that past information can be used by agents to predict spot price movements. A measure of the relative degree of inefficiency (based on forecast error variances) is then used to compare the performance of different markets. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 413–432, 1999

The relative efficiency of commodity futures markets

This article examines the relationship between returns and trading volume for three petroleum futures contracts. Using daily data on futures prices and trading volume, the study first tests for linear causality between returns and volume. The results of this linear causality test show that futures returns and volume have no predictive power for one another. However, because the distribution of the returns and volume series provides some evidence of nonlinear dependence, the study formally tests for and finds evidence of significant nonlinearities in the returns and volume for the three petroleum futures contracts. The returns and volume series are then filtered for linear dependence through the use of a VAR process. A nonparametric test statistic based on the correlation inWe thank Andrew C. Szakmary for supplying the data used in this study. We also thank Deborah R. Kaplan and John Wagster for helpful comments and editorial assistance.

/pdf/an-examination-of-linear-and-nonlinear-causal-relationships-43l1ye2etp.pdf

An Examination of Linear and Nonlinear Causal Relationships Between Price Variability and Volume in Petroleum Futures Markets

Linear dependence, nonlinear dependence and petroleum futures market efficiency

The probability distribution of futures prices in the foreign exchange market: A comparison of candidate processes

Whereas previous studies have focused on the causal relation between nominal interest rates, this paper examines causal relationships between real rates for the United States and six other countries. Based on evidence from our full sample, we find that U.S. and foreign interest rates are not highly informative for one another. This would suggest that even if the United States is regarded as a large player in international financial markets, this does not necessarily translate into the transmission of U.S. real interest rates to other countries. However, an examination of various sub- periods of our sample reveals that this conclusion may be sensitive to the U.S. monetary policy regime. We also report results for linkages between European countries which indicate that Germany provides some information on real interest rates in France and the United Kingdom but not in Italy. An analysis of various sub-periods for the European countries show that the result for France is not robust, with German rates having an impact only in the first period through March 1983. This latter evidence does not provide strong support for the hypothesis that Germany's monetary policy plays a dominant role in the European Monetary System. In general, we would argue that domestic factors play a prominent role in determining real interest rates, quite independently from the influence of interest rates from abroad.

Roger A. Fujihara

Papers

An Examination of Linear and Nonlinear Causal Relationships Between Price Variability and Volume in Petroleum Futures Markets

Linear dependence, nonlinear dependence and petroleum futures market efficiency

The probability distribution of futures prices in the foreign exchange market: A comparison of candidate processes

International Linkages between Short-Term Real Interest Rates

International linkages between short-term real interest rates