Assessing the influence of external factors on agricultural production in Brazil

This article uses 2017 Brazilian agricultural census data (aggregated at county level) to evaluate the impact of external factors on agricultural efficiency in Brazil. The external factors are defined as access to credit, participation in cooperatives, proportion of literacy, technical assistance, and environmental production practices. All variables are transformed as the log of the municipal (county) rank. The response variable is defined as the free disposal hull (FDH) conditional ratio and a one-inflated beta regression is estimated. The results show that in counties where the FDH ratio is equal to 1, cooperatives have the biggest impact on efficiency, and where the FDH ratio is not equal to 1, environmental practices, which are most often associated with technology, have the largest effect on efficiency. Finally, the regions that are expected to see the largest gains in efficiency with increases in external factors are the Northeastern and the Northern regions of Brazil.     

Fractional cointegration and price discovery in Canadian commodities

Using as a unifying theme commodities important to the Canadian economy, recently developed tools are applied to studying price discovery in the spot and futures markets. For each commodity the fractionally cointegrated vector autoregression (FCVAR) model of Johansen and Neilsen is estimated and tested against the special case of the conventional cointegrated vector autoregression (CVAR). These models characterize the fundamental value of a commodity as the common stochastic trend shared by its cointegrated spot and futures prices, and so price discovery can be analyzed using the permanent-transitory decomposition of Gonzalo and Granger. Model forecasts are evaluated and compared using a distributional result due to Clark and West. The generalization to fractional cointegration is found to be statistically significant. However the economic significance of this generalization—in terms of forecast accuracy and the profitability of mean–variance dynamic trading strategies—is more fragile than may have been appreciated.     

Skew-Brownian motion and pricing European exchange options

This article derives a closed-form pricing formula for European exchange options under a non-Gaussian framework for the underlying assets, intending to resolve mispricing associated with a geometric Brownian motion. The dynamics of each of the two correlated underlying assets are assumed to be governed by the exponential of a skew-Brownian motion, which is specified as a sum of a standard Brownian motion and an independent reflected Brownian motion. The proposed pricing formula does not incur additional computational costs than the standard Black–Scholes framework, which one can quickly recover as a particular case of the proposed framework. Finally, we present some numerical experiments followed by a valuable discussion on the results.     

Piecewise linear double barrier options

A piecewise linear double barrier option generalizes classical double barrier options because of its versatility in designing various double boundaries. This paper discusses how to price piecewise linear double barrier options. To this purpose, we derive the probability that an underlying process does not cross a given piecewise linear double barrier, where the underlying process follows the Brownian motion of piecewise constant drift. Using the established non-crossing probability, we provide the explicit pricing formulas of piecewise linear double barrier options and show how the shape of a double barrier affects the option prices through extensive numerical experiments.     

Estimation of a dynamic multi-level factor model with possible long-range dependence

A dynamic multi-level factor model with possible stochastic time trends is proposed. In the model, long-range dependence and short memory dynamics are allowed in global and local common factors as well as model innovations. Estimation of global and local common factors is performed on the prewhitened series, for which the prewhitening parameter is estimated semiparametrically from the cross-sectional and local average of the observable series. Employing canonical correlation analysis and a sequential least-squares algorithm on the prewhitened series, the resulting multi-level factor estimates have centered asymptotic normal distributions under certain rate conditions depending on the bandwidth and cross-section size. Asymptotic results for common components are also established. The selection of the number of global and local factors is discussed. The methodology is shown to lead to good small-sample performance via Monte Carlo simulations. The method is then applied to the Nord Pool electricity market for the analysis of price comovements among different regions within the power grid. The global factor is identified to be the system price, and fractional cointegration relationships are found between local prices and the system price, motivating a long-run equilibrium relationship. Two forecasting exercises are then discussed.     

Why display motion on packaging? The effect of implied motion on consumer behavior

Visual packaging elements play a crucial role in influencing consumer behavior in stores. Front of pack (FOP) formats frequently present images of the product in motion (i.e., implied motion), especially in food categories. Despite the popularity of implied motion in real-world business, little research has been done to understand its effect on consumer behavior. To fill this gap, the present study adopts an evolutionary lens to investigate the impact of implied motion as a packaging design technique on consumers’ attention, product evaluation, purchase intention and choice. We carried out two experiments using realistic milk and orange juice packaging. Specifically, Experiment 1 was conducted in a lab using an eye tracking method to provide an objective measure of attention. The findings show that implied motion significantly increases visual attention and consequently generates more frequent choices. Using an online experimental design and declarative measures, Experiment 2 indicates that implied motion also enhances freshness, which translates into greater tastiness, product attractiveness and, ultimately, purchase intention. The study provides marketers with an inexpensive yet efficient way to enhance in-store marketing performance by incorporating implied motion into the FOP design.     

Min–max multi-step barrier options and their variants

This paper studies a new type of barrier option, min–max multi-step barrier options with diverse multiple up or down barrier levels placed in the sub-periods of the option’s lifetime. We develop the explicit pricing formula of this type of option under the Black–Scholes model and explore its applications and possible extensions. In particular, the min–max multi-step barrier option pricing formula can be used to approximate double barrier option prices and compute prices of complex barrier options such as discrete geometric Asian barrier options. As a practical example of directly applying the pricing formula, we introduce and evaluate a re-bouncing equity-linked security. The main theorem of this work is capable of handling the general payoff function, from which we obtain the pricing formulas of various min–max multi-step barrier options. The min–max multi-step reflection principle, the boundary-crossing probability of min–max multi-step barriers with icicles, is also derived.     

A semi-analytic valuation of two-asset barrier options and autocallable products using Brownian bridge

Barrier options based upon the extremum of more than one underlying prices do not allow for closed-form pricing formulas, and thus require numerical methods to evaluate. One example is the autocallable structured product with knock-in feature, which has gained a great deal of popularity in the recent decades. In order to increase numerical efficiency for pricing such products, this paper develops a semi-analytic valuation algorithm which is free from the computational burden and the monitoring bias of the crude Monte Carlo simulation. The basic idea is to combine the simulation of the underlying prices at certain time points and the exit (or non-exit) probability of the Brownian bridge. In the literature, the algorithm was developed to deal with a single-asset barrier option under the Black–Scholes model. Now we extend the framework to cover two-asset barrier options and autocallable product. For the purpose, we explore the non-exit probability of the two-dimensional Brownian bridge, which has not been researched before. Meanwhile, we employ the actuarial method of Esscher transform to simplify our calculation and improve our algorithm via importance sampling. We illustrate our algorithm with numerical examples.     

Growth vs value investing: Persistence and time trend before and after COVID-19

Value investing and growth investing allow economic experts to adopt different investment strategies depending on their chosen specialty; the two investment types have been conditioned by the pandemic, changing the trend of investments and their results. This research aims to analyze the behavior and trends of the different investment strategies before and after the health crisis. We use methodologies based on fractional integration and cointegration to analyze the persistence and trend of the series and their relationship in the long run. We find that the shock is long-lived and causes a change in trend; however, we find no evidence of mean reversion. In addition, we use multivariate wavelet analysis to analyze the correlation between both time series, concluding that a growth-based investment strategy is more successful than a value-based investment strategy. We use neural networks to corroborate our results.