Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

Tracing VARDI coefficients: a proposal

ABSTRACT

We propose a new approach for tracing the so-called ‘value-added-(re)distribution-important coefficients’ (in short the VARDI coefficients) in a world input–output model. From the perspective of a selected group of economies, VARDI coefficients may be defined as those elements in world input–output matrix in the case of which a small change in their levels leads to the maximization of a share of this group of economies in value added in global value chains. Due to the rapid development of the World Input Output Database, this approach may be easily applied in empirical research to different groups of countries and sectors in world IO models. In an illustrative empirical case study, we use the new approach in order to answer a question regarding what the main directions of the future macroeconomic policy of the U.S. could be in order to ensure the maximization of the country’s share in global value added.     

Measuring industrial upgrading: applying factor analysis in a global value chain framework

ABSTRACT

A key question for promoting international competition is how to improve the position of countries and industries in global value chains (GVCs). The first step is to properly measure industrial upgrading in GVCs. This is not a trivial issue because upgrading has not been defined unambiguously. Several authors have used different (and sometimes related) measures, all of which indicate certain aspects of upgrading. Rather than trying to find the single, ultimate measure of upgrading, we propose a different approach. We examine the multidimensionality of industrial upgrading, using eight indicators in factor analysis. Four of the eight indicators adopt the GVC perspective and include, for example, the growth of the share in value-added exports. We provide three quantitative dimensions of industrial upgrading: process upgrading, product upgrading, and skill upgrading. With these dimensions, we compare and analyze the upgrading of different countries and industries using the World Input–Output Database.     

The anthropocenic imaginary: political ecologies of tourism in a geological epoch

Abstract

The Anthropocene is fundamentally a social imaginary that is both shaped by and is reshaping tourism practice. In this article, we enroll the concept of the anthropocenic imaginary to describe how the Anthropocene is symbolically and materially produced as well as the ways in which it draws on the historical separation of Humanity and Nature. As the structural roots from which the anthropocenic imaginary has grown, this binary co-produces new and old forms of political and ecological inclusion and exclusion. We demonstrate how core themes in tourism studies have fertilized the seeds from which the theoretical branches of post-humanist, capitalist and ecological imaginaries in tourism have taken shape. These anthropocenic imaginaries, we argue, are appropriated in market-based solutions to environmental degradation that emanate from neoliberal contexts internal to the problem. Thus, we question the reconciliation of capitalist accumulation and environmental limits in sustainable tourism. This article and the papers in this issue push forward emerging approaches in the political ecology of tourism that recognize the Anthropocene as both a geological epoch and conceptual regime. In doing so, the issue contributes to emerging conversations on the relationship between politics, ecology and tourism in the so-called recent age of man.     

Return of the inoperability

There has been unrest in the research community investigating the inoperability of an economic system under disaster situations. The inoperability input–output model (IIM), which is very popular in the risk management field, has become a center of argument, particularly from the input–output researchers, that IIM is a straightforward application of the standard Leontief input–output model. This paper revisits the concept of inoperability, rather than IIM, and proposes its new role in disaster impact analysis using a conventional tool, i.e. the RAS method, for illustrating how the inoperability of an economic system in the aftermath of disaster can be evaluated. The proposed framework is employed to examine the inoperability of industries resulting from the 1995 Kobe earthquake. The findings of the analysis reveal the usefulness of inoperability concept that can even incorporate resilience (gained operability) using the proposed framework of this paper.     

Optimal transit fare and service frequency of a nonlinear origin-destination based fare structure

This paper proposes a new nonlinear distance-based transit fare structure, which is measured by a function of the Euclidean distance between the origin and destination stations, termed as Origin-Destination (OD)-based fare. The novel fare structure encourages passengers to freely choose the most efficient trip plan. An optimization model is formulated based on a three-party game (involving the transport authority, transit company, and passenger) to determine the optimal fare function and frequency. An artificial bee colony algorithm is adopted to solve the model. Finally, a numerical example is provided to verify the proposed method.     

Classification of ownership patterns in Korean conglomerates

This study classifies the ownership structure of conglomerates considering the conglomerates' choices of pyramidal vs. horizontal structures and the magnitude of equity held by the controlling shareholders, namely the owner family. It proposes four patterns of ownership structure: (1) horizontal ownership with a high family stake, (2) horizontal ownership with a low family stake, (3) pyramidal ownership with a high family stake, and (4) pyramidal ownership with low family stake. Further, an attempt has been made to identify the series of economic variables contributing to the varying patterns of ownership structure in the 30 largest Korean conglomerates.     

The Feminization U in South Africa: Economic Structure and Women's Labor Force Participation

The feminization U theory claims that women’s labor force participation drops during the initial phase of industrialization and rises once a certain level of development is reached. This paper is the first to exploit the diversity in economic structure across municipalities to consider the shape of the feminization U in a developing country. Using data from South Africa’s 2007 Community Survey, this study investigates whether a feminization U exists. Results reveal a U-shaped relationship between the share of nonagricultural employment and women’s probability of being in the labor force. Results show that the exclusion of informal urban employment leads to an overestimation of the U slope and part of the decline in women’s labor force participation during early structural change is likely related to household and care constraints. A U-shaped relationship is not found between the share of households with electricity and women’s probability of being in the labor force.