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The purpose of this paper is to introduce a continuous time version of the speculative storage model of Deaton and Laroque (1992) and to use for pricing derivatives, in particular insurances on agricultural prices.

The methodology of financial engineering is used in order to find the partial differential equations that the dynamics of derivative prices have to satisfy. Furthermore, by using the Monte-Carlo method (and Feynman-Kac theorem) the insurance prices is computed.

Results of this paper show that insurance prices (and derivative prices in general) are heavily influenced by market structure, in particular, the demand function specifications. Furthermore, through an empirical analysis, the performance of the continuous time speculative storage model is compared with the geometric Brownian motion model. It is shown that the speculative storage model outperforms the actual data.

Since the agricultural insurances in many countries are subsidised by government, the results of this paper can be used by policy makers to measure changes in agricultural insurance premiums in scenarios that market experiences changes in demand. In the same manner, insurance companies and investors can use the results of this paper to better price agricultural derivatives.

The issue of agricultural insurance pricing (in general derivative pricing) is of great concern to policy makers, investors and insurance companies. To the author’s knowledge, an approach which uses the methodology of financial engineering to compute the insurance prices (in general derivatives) is new within the literature.

The authors' paper aims to deal with the question whether speculative bubbles are present in agricultural commodity prices.

The authors apply a regime switching regression model to test the hypothesis that agricultural prices contain periodically collapsing bubbles. Using daily futures prices for six agricultural commodities, the authors calculate net convenience yields from which price fundamentals are derived.

The authors discover pronounced deviations between observed prices and their fundamental values. However, they do not find evidence for the presence of periodically and partially collapsing speculative bubbles for five of six commodities. Except for soybeans, the signs and the significance of the estimated coefficients are not entirely in line with the predictions of the theoretical model.

The authors' study adds to the heated discussion on the impact of speculative behavior on agricultural commodity prices. So far, most contributions in the literature either use theoretical arguments for the (non‐) existence of bubbles or apply indirect tests which are plagued by low statistical reliability. In contrast, the authors apply a direct test. They find that the outcome of empirical bubble tests depends on the considered bubble type and on the testing procedure. In view of these ambiguities, definite statements on the presence of speculative bubbles as well as demands for limitations of speculative positions in commodity futures markets should be carefully reconsidered.

This paper aims to better understand if speculative activity is a factor or even the main factor in the run-up of oil prices in the spot market, particularly in the recent price bubble that occurred in the period from mid-2003 to 2008.

The methodology used is based on an existing vector autoregressive model proposed by Kilian and Murphy (2014), which is a structural model of the global market for crude oil that accounts for flow demand and flow supply shocks and speculative demand oil shocks.

From the output of the authors’ structural model, the authors ruled out speculation as a factor of rising oil prices. The authors have found instead that the rapid oil demand caused by an unexpected increase in the global business cycle is the most accurate culprit. Despite the change of perspective in the speculative component, the authors’ conclusions concur with the findings of Kilian and Murphy (2014) and others.

As far as the authors are aware, this is the first time that a study has used as a spread oil variable, a speculative component of the real price, replacing the oil inventories considered by Kilian and Murphy (2014). Another contribution is that the model used allows estimating traditional oil demand elasticity in production and oil supply elasticity in spread movements, casting doubt on existing models with perfect price-inelastic output for crude oil.

Oil market VAR models have become the standard tool for understanding the evolution of the real price of oil and its impact on the macro economy. As this literature has expanded at a rapid pace, it has become increasingly difficult for mainstream economists to understand the differences between alternative oil market models, let alone the basis for the sometimes divergent conclusions reached in the literature. The purpose of this survey is to provide a guide to this literature. Our focus is on the econometric foundations of the analysis of oil market models with special attention to the identifying assumptions and methods of inference.

This paper considers properties of an optimization-based sampler for targeting the posterior distribution when the likelihood is intractable. It uses auxiliary statistics to summarize information in the data and does not directly evaluate the likelihood associated with the specified parametric model. Our reverse sampler approximates the desired posterior distribution by first solving a sequence of simulated minimum distance problems. The solutions are then reweighted by an importance ratio that depends on the prior and the volume of the Jacobian matrix. By a change of variable argument, the output consists of draws from the desired posterior distribution. Optimization always results in acceptable draws. Hence, when the minimum distance problem is not too difficult to solve, combining importance sampling with optimization can be much faster than the method of Approximate Bayesian Computation that by-passes optimization.

This chapter develops a no-arbitrage, futures equilibrium cost-of-carry model to demonstrate that the existence of cointegration between spot and futures prices in the New York Mercantile Exchange (NYMEX) crude oil market depends crucially on the time-series properties of the underlying model. In marked contrast to previous studies, the futures equilibrium model utilizes information contained in both the quality delivery option and convenience yield as a timing delivery option in the NYMEX contract. Econometric tests of the speculative efficiency hypothesis (also termed the “unbiasedness hypothesis”) are developed and common tests of this hypothesis examined. The empirical results overwhelming support the hypotheses that the NYMEX future price is an unbiased predictor of future spot prices and that no-arbitrage opportunities are available. The results also demonstrate why common tests of the speculative efficiency hypothesis and simple arbitrage models often reject one or both of these hypotheses.

This paper examines the pricing of Initial Public Offerings (IPOs) in the secondary market on the first day of aftermarket trading. The focus of this study is on shifts in average returns over time, and does not necessarily address the cross‐sectional implications of a risk/return relation. The focus of the study is to examine the reasonableness of first day trading prices of IPOs. Initial returns of IPOs, issued during the period, January 1, 1999 to June 30, 2000, reached as much as 800 per cent, and the average initial return for the study sample was of 76 per cent. An important question is whether the high initial returns, observed during this time period, are appropriate for the level of risk associated with these new issues. Related to this question is the pricing of these securities by investment bankers (i.e. the offer price) and the pricing of the securities in aftermarket trading (i.e the secondary market). The results of this study indicate the presence of speculative excesses in the initial pricing of IPOs in aftermarket trading during 1999 and part of 2000. Further there is no indication that IPOs are excessively underpriced by investment bankers during the study period, January 1, 1997 through June 30, 2000. The results of this study may be useful to investors in making decisions about purchasing new public securities in the secondary market.

Examines the reasons driving French food retailers to build major speculative inventories through forward buying from their suppliers. First analyses the origin of the phenomenon and its strategic basis. Then, using the model of postponement‐speculation proposed by Louis Bucklin in the mid‐1960s, explains why forward buying does not conflict with a reduction of in‐store inventories. Finally, offers comments on the future of speculative inventories in the French context, which is characterized by permanently conflicting relations between manufacturers and distributors. To do so, reference is made to information collected in the course of interviews with the logistics managers of ten of the leading companies in the sector.

This paper aims to explore the relationship between prudence in risk attitudes and patience of time preference of Chinese apple growers regarding off-farm cold storage of production and marketing in non-harvest seasons. The authors also consider the effect of farmer participation in cooperative-like organizations known as Farm Bases (FBs).

The authors use multiple list methods and elicitation strategies to measure Chinese apple farmers' risk attitudes and time preferences. Because these farmers can either sell their apples immediately to supermarkets or intermediaries or place them in storage, the authors assess correlations between their storage decisions and their preferences regarding risk and time. The authors also differentiate risks involving gains and losses and empirically examine individual risk attitudes in different scenarios.

Marketing decisions are moderately associated with risk attitudes but not time preference. Farmers with memberships in local farmer cooperatives are likely to speculate more in cold storage. Thus, risk aversion behavioral and psychological motives affect farmers' decision-making of cold storage and intertemporal marketing activities. However, membership in cooperatives does not always result in improved income and welfare for farmers.

The research confirms that behavioral factors may strongly drive vulnerable smallholder farmers to speculate into storage even under seasonal and uncertain marketing volatility. There is the need to think deeper about the rationale of promoting cooperatives and other agricultural forms, because imposing these without careful consideration can have negative impacts.

Do risk and time preferences affect the decision of farmers to utilize storage facilities? This question is important because it is not clear if and how risk preferences affect the tradeoff between consuming today and saving for tomorrow, especially for farmers in developing countries.

During world price spike periods, the government is more likely to apply trade distortions to stabilize domestic prices, but the trade distortions would amplify fluctuations of international market prices. Which type of policy may stabilize the domestic market price, but not disturb the international market? This paper answers the question by taking public storage policy as a case study in the context of trade policy. Specially, this paper tries to identify the effect of domestic public storage on the world market price.

This article extends a standard theoretical model of trade policy through incorporating domestic public storage policy and makes the model more applicable in the context of China. The extended model is then applied to analysis how domestic public storage policy affects the international market price in the context of trade policy. Finally, a properly identified structural vector auto-regression technique is applied to test the effect of domestic public storage on the world market price by using cotton data from China.

The theoretical model indicates that China's public storage policy could stabilize the international market price. In order to test the working mechanisms, China's soaring public storage between 2010 and 2014 is employed to identify the effects of China's cotton storage on the volatility of the world price. The empirical findings show that China was able to stabilize the international price of cotton to a non-trivial extent through alteration of its public stockpile.

The first contribution is that this paper extends a standard theoretical model of trade policy to incorporate domestic public storage policy, which enables us to explore the effects of domestic public storage policy on the world price in the context of China. The second major contribution is that this paper provides evidence that, as a large player in the world market, China's public storage policy could stabilize the international agricultural price to a substantial degree.