Neural network approximation for superhedging prices

This article examines neural network-based approximations for the superhedging price process of a contingent claim in a discrete time market model. First we prove that the α-quantile hedging price converges to the superhedging price at time 0 for α tending to 1, and show that the α-quantile hedging price can be approximated by a neural network-based price. This provides a neural network-based approximation for the superhedging price at time 0 and also the superhedging strategy up to maturity. To obtain the superhedging price process for $t>0$, by using the Doob decomposition, it is sufficient to determine the process of consumption. We show that it can be approximated by the essential supremum over a set of neural networks. Finally, we present numerical results.     

Do risk and competition trigger conditional cooperation? Evidence from public good experiments

We investigate the effect of intra-group competition and risk marginal per capita returns on subjects' cooperative behavior in a one-shot public good game—following the well-known approach proposed by Fischbacher, Gächter, and Fehr (2001) and extending the Colasante et al. (2018, 2019) parametrization. We study the interaction between environment and social preferences and test the existence of a causal relationship of risk and competition over cooperative behavior when an individual's benefit of the public good is heterogeneous and uncertain. Our results report experimental evidence about competition fostering cooperative behavior leading to a rise in contribution for all the subjects regardless of their social preferences. However, risk has a detrimental effect on cooperative behavior due to encouraging free riding.     

Exploring the Impacts of the COVID-19 Pandemic on Productivity: A Study of Accounting Faculty Who Are Caregivers of Children*

This study explores how the COVID-19 pandemic affected the productivity of accounting faculty who identify as caregivers of children. We examine the effects on caregivers of children because of the significant shift in the family-work interface that resulted from remote working and learning. We draw on existing family-work conflict research to develop four hypotheses that explore why the productivity of accounting faculty who are caregivers of children might be affected differently during the pandemic than that of accounting faculty who are non-caregivers of children. We surveyed accounting faculty primarily across Canada and the United States. We find that accounting faculty caring for children during the pandemic experienced reduced research, teaching, and service productivity because of increased family-work conflict and depletion. We supplement our main findings with an analysis of open-ended questions to further understand productivity changes and supports for research, teaching, and service. Our study contributes to research examining family-work conflict, employee productivity, and the accounting profession by making practical recommendations for providing targeted support for caregivers of children during times of crisis.     

Household consumption patterns and the consumer price index,England, 1260–1869

Existing long-run consumer price indices for England rely on a fixed consumption basket. Here we construct a methodologically improved, chained-Laspeyres price index for ordinary households based on their changing expenditure patterns between 1260 and 1869. Rather than offering a revisionist perspective on long-run costs, it confirms the broad accuracy of existing indices for the pre-industrial period. The dominant dependence of the key items of expenditure on agricultural, particularly arable, prices explains this finding. The industrial period introduced a new dynamic. The shift in household expenditure towards imported groceries and manufactured goods allowed for more substitution in response to relative price and income changes. Adding the current series to those chained-Laspeyres indices available for later periods provides a CPI for ordinary households in England over nearly eight centuries; from 1260 to the present day.     

Ecotourism branding in protected areas of Iran: Using an efficient hybrid multi-criteria decision-making method model

Ecotourism, as a nature-based sustainable tourism, raises awareness about the protection of natural and cultural landscape values. This study aims to determine the ecotourism criteria to develop strategies for a sustainable ecotourism branding in Golestan, located in the northeast of Iran. To reach this aim, Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis, multi-criteria decision-making methods consisting of Analytic Hierarchy Process (AHP), and Best and Worst Method (BWM) were integrated. The most appropriate ecotourism strategies for the branding of the study area were ranked according to their priorities. The results of this study reveal that among the 5 main and 20 sub ecotourism criteria, “having natural protected areas,” which is an opportunity, and “having ecological values,” which is a strength, were determined as the highest priority strategies for ecotourism branding. The methods and results of this quantitative-based research present an exemplary hybrid model that prioritizes the strategies required for branding ecotourism in similar protected areas.     

Optional projection under equivalent local martingale measures

We study optional projections of \({\mathbb{G}}\)-adapted strict local martingales on a smaller filtration \({\mathbb{F}}\) under changes of equivalent martingale measures. General results are provided as well as a detailed analysis of two specific examples given by the inverse Bessel process and a class of stochastic volatility models. This analysis contributes to clarify the absence of arbitrage opportunities of market models under restricted information.