We examine the effects of unconventional monetary policy (UMP) events in the United States on asset price risk using risk-neutral density functions estimated from options prices. Based on an event study including a key exchange rate, an equity index, and five commodities, we find that “tail risk” diminishes in the immediate aftermath of UMP events, particularly downside left tail risk. We also find that QE1 and QE3 had stronger effects than QE2. We conclude that UMP events that serve to ease policies can help to bolster market confidence in times of high uncertainty.
The recent relatively high levels of global oil prices have led to a significant improvement in the public finances of several hydrocarbon-exporting countries. However, despite the increase in fiscal buffers, medium-term risks remain high. Fiscal vulnerabilities have increased as a consequence of the substantial spending packages that have been implemented in recent years. This has raised break-even prices—that is, the price levels that ensure that fiscal accounts are in balance at a given level of spending—in these countries. This study analyses such risks and develops measures of fiscal risk stemming from oil price fluctuations. An empirical application to hydrocarbon-exporting countries from the Middle East and North Africa region is included. Additionally, it is noted that countries with large net assets and proven oil reserves are much less vulnerable to fiscal risk than is indicated by standard measures based on break-even prices.
We assess the spot price forecasting performance of 10 commodity futures at various horizons up to two years and test whether this performance is affected by market conditions. We reject efficient markets based on in-sample tests but, out-of-sample, we find that the forecast from the futures market is hard to beat. We find that the forecasting performance of futures does not depend on the slope of the futures curve, in contrast to the predictions of well-known models of commodity markets. We also find futures' forecasting performance to be invariant to whether prices are in an upswing or downswing, casting doubt on aspersions that uninformed investors participating during bull markets impede the price discovery process.
Building on the widely-used double-lognormal approach by Bahra (1997), this paper presents a multi-lognormal approach with restrictions to extract risk-neutral probability density functions (RNPs) for various asset classes. The contributions are twofold: first, on the technical side, the paper proposes useful transformation/restrictions to Bahra’s original formulation for achieving economically sensible outcomes. In addition, the paper compares the statistical properties of the estimated RNPs among major asset classes, including commodities, the S&P 500, the dollar/euro exchange rate, and the US 10-year Treasury Note. Finally, a Monte Carlo study suggests that the multi-lognormal approach outperforms the double-lognormal approach.
Commodities are back following a stellar run of price performance, attracting financial investor attention. What are the fundamental reasons to hold commodities? One reason is the exposure offered to underlying risk factors. In this paper, I assess the macro risk exposure offered by commodity futures and test whether these risks are priced, using Merton's (1973) intertemporal capital asset pricing model for a sample of commodity prices covering the period January 1973 - February 2008. I find that commodity futures offer a hedge against lower interest rates and that investors are willing to accept lower expected returns for this position. Although some commodities are also a hedge against U.S. dollar depreciation, this risk is not priced.
This paper assesses the performance of three types of commodity price forecasts—those based on judgment, those relying exclusively on historical price data, and those incorporating prices implied by commodity futures. For most of the 15 commodities in the sample, spot and futures prices appear to be nonstationary and to form a cointegrating relation. Spot prices tend to move toward futures prices over the long run, and error-correction models exploiting this feature produce more accurate forecasts. The analysis indicates that on the basis of statistical- and directional-accuracy measures, futures-based models yield better forecasts than historical-data-based models or judgment, especially at longer horizons.
This paper undertakes an econometric investigation into the presence of risk premium in commodity futures markets. The statistical tests are derived from a formal model of asset pricing and are applied to futures prices in a variety of commodity markets. The results suggest that for several commodities there is evidence of a time varying risk premium, particularly in futures contracts maturing six months ahead. The implications of the study for the efficiency of the futures markets and the costs of using these markets for hedging are also noted.
The IMF Working Papers series is designed to make IMF staff research available to a wide audience. Almost 300 Working Papers are released each year, covering a wide range of theoretical and analytical topics, including balance of payments, monetary and fiscal issues, global liquidity, and national and international economic developments.