Price Mean Reversion, Seasonality, and Options Markets

Options on agricultural commodities with maturities exceeding one year seldom trade. One possible reason to explain this lack of trading is that we do not have an accurate option pricing model for products where mean reversion in spot-price levels can be expected. Standard option pricing models assume proportionality between price variance and time to maturity. This proportionality is not a valid assumption for commodities whose supply response brings prices back to production costs. The model proposed here incorporates mean reversion in spot-price levels and includes a correction for seasonality. Mean reversion and seasonality are both observed in the soybean market. The empirical analysis lends strong support to the model

The repulsive lattice gas, the independent-set polynomial, and the Lov\'asz local lemma

We elucidate the close connection between the repulsive lattice gas in equilibrium statistical mechanics and the Lovasz local lemma in probabilistic combinatorics. We show that the conclusion of the Lovasz local lemma holds for dependency graph G and probabilities {p_x} if and only if the independent-set polynomial for G is nonvanishing in the polydisc of radii {p_x}. Furthermore, we show that the usual proof of the Lovasz local lemma -- which provides a sufficient condition for this to occur -- corresponds to a simple inductive argument for the nonvanishing of the independent-set polynomial in a polydisc, which was discovered implicitly by Shearer and explicitly by Dobrushin. We also present some refinements and extensions of both arguments, including a generalization of the Lovasz local lemma that allows for "soft" dependencies. In addition, we prove some general properties of the partition function of a repulsive lattice gas, most of which are consequences of the alternating-sign property for the Mayer coefficients. We conclude with a brief discussion of the repulsive lattice gas on countably infinite graphs.Comment: LaTex2e, 97 pages. Version 2 makes slight changes to improve clarity. To be published in J. Stat. Phy

Estimation of Endogenous Volatility Models with Exponential Trends

Nonlinearities, exponential trends, and Euler equations are three key features of standard dynamic volatility models of speculation, economic growth, or macroeconomic fluctuations with occasionally binding constraints and endogenous state-dependent volatility. A natural way to estimate a model with all such three features could be to use the observed nonstationary data in a single step without preliminary linearization, log-linearization, or preliminary detrending. Adoption of this natural strategy confronts a serious challenge that has been neither articulated nor solved: a dichotomy in the empirical model implied by the Euler equation. This leads to a discontinuity in the regression in the limit, rendering the approaches employed in available proofs of consistency inapplicable. We characterize the problem and develop a novel method of proof of consistency and asymptotic normality. Our methodological contribution establishes a foundation for consistent estimation and hypothesis testing of nonstationary models without resorting to preliminary detrending, an a priori assumption that any trend is exactly zero, linearization, or other restrictions on the model

Estimation of Endogenous Volatility Models with Exponential Trends

Nonlinearities, exponential trends, and Euler equations are three key features of standard dynamic volatility models of speculation, economic growth, or macroeconomic fluctuations with occasionally binding constraints and endogenous state-dependent volatility. A natural way to estimate a model with all such three features could be to use the observed nonstationary data in a single step without preliminary linearization, log-linearization, or preliminary detrending. Adoption of this natural strategy confronts a serious challenge that has been neither articulated nor solved: a dichotomy in the empirical model implied by the Euler equation. This leads to a discontinuity in the regression in the limit, rendering the approaches employed in available proofs of consistency inapplicable. We characterize the problem and develop a novel method of proof of consistency and asymptotic normality. Our methodological contribution establishes a foundation for consistent estimation and hypothesis testing of nonstationary models without resorting to preliminary detrending, an a priori assumption that any trend is exactly zero, linearization, or other restrictions on the model

The Value of Public Information in Storable Commodity Markets: Application to the Soybean Market

This study provides a framework to estimate the potential effects and benefits of the provision of market information in storable commodity markets. This framework is applied to the case of production forecasts for the soybean market. A rational expectations storage model of the global soybean market accounting for both inter-annual and intra-annual market dynamics is built. Shocks that occur between planting and harvesting affect the size of the potential harvest. Estimates of the size of these shocks are reported publicly, and affect the market equilibrium through adjustments to stock levels. By varying counterfactually the observability of seasonal shocks, we can estimate the efficiency gains related to the availability of advance information. They are equivalent to 2% of storage costs; the reduction of stock levels being the main channel explaining the welfare gains. The presence of advance information has a limited effect on inter-annual price volatility but redistributes price volatility during the season, increasing it just before harvest when almost all news has been received and stocks are tight, and decreasing it after harvest. The effect of news shocks is stronger on higher-order moments of the distribution with a strong decrease in skewness and kurtosis related to the lower frequency of price spikes