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This paper explores the impact of investor flows and financial market conditions on returns in crude oil futures markets. I argue that informational frictions and the associated speculative activity may induce prices to drift away from \"fundamental\" values, and may result in price booms and busts. Particular attention is given to the interplay between imperfect information about real economic activity, including supply, demand, and inventory accumulation, and speculative activity in oil markets. Furthermore, I present new evidence that there were economically and statistically significant effects of investor flows on futures prices, after controlling for returns in the United States and emerging-economy stock markets, a measure of the balance sheet flexibility of large financial institutions, open interest, the futures/spot basis, and lagged returns on oil futures. The largest impacts on futures prices were from intermediate-term growth rates of index positions and managed-money spread positions. Moreover, my findings suggest that these effects were through risk or informational channels distinct from changes in convenience yield. Finally, the evidence suggests that hedge fund trading in spread positions in futures impacted the shape of term structure of oil futures prices. This paper was accepted by Wei Xiong, finance.

\"Futures and Options Markets: An Introduction provides the reader with an economic understanding of the development and operation of global futures and options markets, where everything from coffee to gold to foreign currencies are traded. Starting with the fundamentals of commodity futures, the text advances the reader through the exciting world of financial futures and options, including currencies and equity indexes. Utilizing real-world examples, this text brings the markets to life by explaining how and why these markets function, how they indirectly affect us in our daily lives, and how they are used to manage market risk\"--Page 4 of cover.

Despite their widespread use as predictors of the spot price of oil, oil futures prices tend to be less accurate in the mean-squared prediction error sense than no-change forecasts. This result is driven by the variability of the futures price about the spot price, as captured by the oil futures spread. This variability can be explained by the marginal convenience yield of oil inventories. Using a two-country, multi-period general equilibrium model of the spot and futures markets for crude oil we show that increased uncertainty about future oil supply shortfalls under plausible assumptions causes the spread to decline. Increased uncertainty also causes precautionary demand for oil to increase, resulting in an immediate increase in the real spot price. Thus the negative of the oil futures spread may be viewed as an indicator of fluctuations in the price of crude oil driven by precautionary demand. An empirical analysis of this indicator provides evidence of how shifts in the uncertainty about future oil supply shortfalls affect the real spot price of crude oil.

For this study of the simple properties of commodity futures as an asset class, an equally weighted index of monthly returns of commodity futures was constructed for the July 1959 through December 2004 period. Fully collateralized commodity futures historically have offered the same return and Sharpe ratio as U.S. equities. Although the risk premium on commodity futures is essentially the same as that on equities for the study period, commodity futures returns are negatively correlated with equity returns and bond returns. The negative correlation is the result, primarily, of commodity futures' different behavior over a business cycle. Commodity futures are positively correlated with inflation, unexpected inflation, and changes in expected inflation. Imagine an asset class that has returns that (1) are the same as those on the U.S. stock market but (2) are less volatile than stock returns, (3) are negatively correlated with the returns on stocks and bonds, and (4) are positively correlated with inflation. The asset class is an investment in commodity futures. Despite being an old asset class, commodity futures are not widely appreciated. Futures contracts are agreements to buy or sell a commodity at a future date at a price that is agreed upon today. Except for collateral requirements, futures contracts do not require a cash outlay for either buyers or sellers. The buyer of a futures contract is, on average, compensated by the seller of futures if the futures price is set below the expected spot price at the time of the expiration of the futures contract. The opposite is true when the futures price is set above the expected future spot price. In 1930, John Maynard Keynes postulated that sellers of futures (hedgers) would, on average, compensate the buyers of futures (speculators)-a situation he referred to as \"normal backwardation.\" By examining the returns to futures over long periods, we indirectly tested this Keynesian prediction. We constructed a dataset of returns on individual commodity futures going back as far as 1959. The dataset combines information about individual commodity futures prices obtained from the Commodity Research Bureau (covering, among other exchanges, the Chicago Board of Trade and Chicago Mercantile Exchange) and the London Metal Exchange. We computed investment returns by rolling positions in individual futures contracts forward over time. Commodity futures were combined into an equally weighted index, and much of the article is concerned with the behavior of this index. We show that over a 45-year period, a diversified investment in collateralized commodity futures earned historical returns that are comparable to U.S. stock returns. The economic rationale for these returns is the reward that investors in commodity futures receive for providing price insurance to commodity producers. The reward for providing price protection (rather than foreseeable trends in commodity prices) is the key to the returns that a futures investor can expect. Individual commodity futures can be very volatile, but much of this volatility can be avoided by investing in a diversified index of commodity futures. The average historical returns to the equally weighted index of commodity futures has exceeded the return on U.S. T-bills by about 5 percent a year. This excess return is about the same as the historical risk premium on the S&P 500 Index over the 1959-2004 period, but the commodity futures index had a slightly lower standard deviation than the S&P 500. The relatively low volatility of the commodity futures index stems from the fact that the pairwise correlations between individual commodity futures are relatively low. Commodity futures are less risky by other standards. First, the distribution of commodity futures returns is skewed to the right, whereas equity return distributions are skewed to the left. In other words, relative to a normal bell-shaped curve, equities experience proportionally more crashes whereas the \"crashes\" in commodities most often occur on the upside, leading to positive returns to investors in commodity futures. Second, commodity futures have the ability to diversify portfolios of stocks and bonds. The sources of the diversification benefits are the ability of commodity futures to provide a (partial) hedge against inflation-stocks and bonds are poor hedges by comparison-and to partially offset the cyclical variation in the returns of stocks and bonds. Finally, when we compared an investment in our index with a portfolio of stocks of commodity-producing companies, we found that these portfolios are not close substitutes: The stocks of commodity producers are more correlated with the broad stock market than with an index of commodity futures.

\"In Markets & Momentum: How Profiling Gives Traders an Advantage, James F. Dalton dramatically expands on his first revolutionary book, Markets in Profile. Summarizing six decades of experience--from formative memberships on the CBOE and CBOT to his role as UBS Director of Hedge Fund Research--Dalton challenges traders to recognize that self-understanding must be balanced with market-understanding. Dalton and his partners, Jennifer Loh and Raghu Rajput, continue to promote education explains the foundational elements of market understanding through the only reliable and objective source of actionable trading information: the market itself. You'll discover how to begin your investing journey with a clean slate, focusing only on the information that truly matters. Or, if you're already a trader, you'll learn how to level-up your skills in a discipline with little room for error\"-- Provided by publisher.

A popular view is that the surge in the real price of oil during 2003-08 cannot be explained by economic fundamentals, but was caused by the increased financialization of oil futures markets, which in turn allowed speculation to become a major determinant of the spot price of oil. This interpretation has been driving policy efforts to tighten the regulation of oil derivatives markets. This survey reviews the evidence supporting this view. We identify six strands in the literature and discuss to what extent each sheds light on the role of speculation. We find that the existing evidence is not supportive of an important role of speculation in driving the spot price of oil after 2003. Instead, there is strong evidence that the co-movement between spot and futures prices reflects common economic fundamentals rather than the financialization of oil futures markets.

Price discovery is the incorporation of information to prices through the actions of traders. Previous studies in financial markets have found evidence that informed traders may submit limit orders instead of market orders as part of their trading strategies. If so, the steps of limit order book (LOB) beyond the best bid and best ask spread (BAS) may contain valuable information and contribute to price discovery of the underlying asset. This is the first attempt to examine the informativeness of the LOB beyond the BAS for agricultural commodities. We reconstruct the LOB using market depth data and use three information share approaches to test to what extent the steps of LOB beyond the BAS contribute to price discovery. This is done for five major agricultural commodities, namely live cattle, lean hogs, corn, wheat, and soybeans, as well as the E-mini Standard and Poor’s 500 Index (S&P 500) futures contracts. The results show that the steps of the LOB beyond the BAS contribute by over 27% to price discovery of futures contracts. Across agricultural commodities, the steps of the LOB beyond the BAS have more information for grains than meats. Moreover, beyond the BAS, the steps closer to the top of the book contain more information for livestock and E-mini S&P 500. For grains, the steps farther from the BAS are as informative as the steps closer to the BAS. These findings suggest that informed traders in futures electronic markets actively use limit orders with price steps beyond the BAS.