Market interdependence and volatility transmission among major crops

This article provides a comprehensive analysis of the dynamics of volatility across major agricultural commodities in the United States. Volatility interactions across markets may lower the effectiveness of diversification strategies to mitigate price risks and should be taken into account when analyzing the pricing behavior of different agricultural commodities. We follow a multivariate GARCH approach to evaluate the time evolution of conditional correlations and volatility transmission across corn, wheat, and soybeans price returns on a daily, weekly, and monthly basis. The period of analysis is from 1998 to 2012. The estimation results indicate a lack of lead‐lag relationships between corn, wheat, and soybeans price returns at the mean level. We find, however, important volatility spillovers across commodities, particularly at the weekly and monthly level. Wheat and corn seem to play a major role in terms of volatility transmission. Despite the supposed higher financial market integration of agricultural commodities, we do not observe that agricultural markets have become more interdependent in recent years.     

Preference Uncertainty in Non-Market Valuation: A Fuzzy Approach

In this article, we consider uncertain preferences for non-market goods, but we move away from a probabilistic representation of uncertainty and propose the use of fuzzy contingent valuation. We assume that a decision maker never fully knows her own utility function and we treat utility as a fuzzy number. The methodology is illustrated using data on forest valuation in Sweden. Fuzzy contingent valuation provides estimates of resource value in the form of a fuzzy number and includes estimates obtained using a standard probabilistic approach.     

Galton's Error and the under-representation of systematic risk

Science progresses by improving its measurement apparatus. This holds true in finance too. The new methodology of “complete identification”, using simple algebraic geometry, throws new light on Galton's Error in finance and economics and the resulting misinformation of investors. Mutual funds conventionally advertise their relative systematic market risk, or “betas”, to potential investors based on incomplete measurement by unidirectional bivariate projections: they commit Galton's Error by under-representing their systematic risk. Consequently, far too many mutual funds are marketed as “defensive” and too few as “aggressive”. Using the new methodology it is found that, out of a total of 3217 mutual funds, 2047 funds (63.7%) claimed to be defensive based on the current industry standard methodology, but only 608 (18.9%) actually are. This under-representation of systematic risk leads to inefficiencies in the capital allocation process, since biased betas lead to mispricing of mutual funds. Complete bivariate projections produce a correct representation of the epistemic uncertainty inherent in the bivariate measurement of relative market risk and provide a new CAPM taxonomy. Our conclusions have also serious consequences for the proper “bench-marking” and recent regulatory proposals for the mutual funds industry. Extension of the new methodology to multivariate systematic risk measurement by Asset Pricing Theory (APT) is suggested.     

Bottom-up sales forecasting through scenario analysis

A simple but effective bottom-up sales forecasting system, developed for a large New Zealand printing and packaging company, is described and analyzed. A central feature of the method is a procedure called “scenario analysis,” enabling the forecaster to incorporate in a systematic manner a large number of uncertainties in his or her assessment of the future.     

Persistence characteristics of the Chinese stock markets

Using advanced signal processing, this paper identifies the lack of ergodicity, stationarity, independence and the degree of persistence of the Shanghai (SHI) stock market and Shenzhen A shares (SZI) and B shares (SZBI), before and after the various deregulations and reregulations. Their lack of stationarity and ergodicity are ascribed to (1) the initial interventions in these stock markets by the Chinese government by imposing various daily price change limits, and (2) the changing trading styles, after the Chinese government left these equity markets to develop by themselves. The SHI, SZI, and SZBI are moderately persistent with Hurst exponents slightly greater than the Fickian 0.5 of the Geometric Brownian Motion. These stock markets were considerably more persistent before the deregulations, but they now behave more like Geometric Brownian Motions, i.e., efficiently. Thus, the Chinese stock markets are gradually and properly being integrated into one Chinese stock market. Our results are consistent with similar empirical findings from Latin American, European, and other Asian emerging financial markets.     

Marginal Valuation of Charismatic Species: Implications for Conservation

Most contingent valuation studies focus on total willingness to pay (WTP) as a measure of welfare change. For policy involving species preservation, however, it is important to distinguish between the benefits of preventing a species from going extinct and the benefits of preserving numbers above the minimum viable population (MVP) level. Once MVP is exceeded, marginal WTP becomes relevant. These propositions are illustrated for the case of one charismatic species whose management is much debated, minke whales in the Northeast Atlantic Ocean. It is shown that, for a given estimate of total preservation value, strict conservation and extinction can both be optimal. This finding highlights the importance of collecting marginal values in contingent valuation surveys.     

Boreal Forest Carbon Sequestration Strategies: A Case Study of the Little Red River Cree First Nation Land Tenures*

In this paper, creation of carbon offset and emission reduction credits are examined from the perspective of the Little Red River Cree Nation (LRRCN), a forest tenure holder in northern Alberta. Carbon credits are produced under three scenarios: (1) carbon uptake in forest ecosystems, with postharvest waste left on site; (2) carbon uptake in forests and products; and (3) carbon uptake in forests with harvested fiber used for energy production. A mathematical programming model is used to solve for the minimum prices that cause the LRRCN to include production of carbon credits in its forest management and post‐harvest processing strategies. If LRRCN is paid according to its costs of creating carbon credits, it will opt to use fiber for forest products as this provides the greatest earning potential. If LRRCN faces a fixed price for carbon credits, it will produce fiber for generating electricity in lieu of coal as this strategy has the lowest average cost. However, when costs of feedstock transportation and construction of a power plant are taken into account, carbon uptake in biomass and forest products turn out to be more competitive.