Affine processes, arbitrage-Free Term structures of legendre polynomials,and option pricing

Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modeled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. (2000) in exploring Legendre conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives. Closing the article, the empirical section presents precise evidence on the reward of implementing arbitrage-free parametric term structure models: The ability of obtaining a good approximation for the state vector by simply using cross sectional data.

Homogeneous middles vs. heterogeneous tails, and the end of the ‘Inverted-U’: the share of the rich is what it’s all about

This paper examines the current global scene of distributional disparities within-nations. There are six main conclusions. First, about 80 per cent of the world’s population now live in regions whose median country has a Gini not far from 40. Second, as outliers are now only located among middle-income and rich countries, the ‘upwards’ side of the ‘Inverted-U’ between inequality and income per capita has evaporated (and with it the statistical support there was for the hypothesis that posits that, for whatever reason, ‘things have to get worse before they can get better’). Third, among middle-income countries Latin America and mineral-rich Southern Africa are uniquely unequal, while Eastern Europe follows a distributional path similar to the Nordic countries. Fourth, among rich countries there is a large (and growing) distributional diversity. Fifth, within a global trend of rising inequality, there are two opposite forces at work. One is ‘centrifugal’, and leads to an increased diversity in the shares appropriated by the top 10 and bottom 40 per cent. The other is ‘centripetal’, and leads to a growing uniformity in the income-share appropriated by deciles 5 to 9. Therefore, half of the world’s population (the middle and upper-middle classes) have acquired strong ‘property rights’ over half of their respective national incomes; the other half, however, is increasingly up for grabs between the very rich and the poor. And sixth, Globalisation is thus creating a distributional scenario in which what really matters is the income-share of the rich — because the rest ‘follows’ (middle classes able to defend their shares, and workers with ever more precarious jobs in ever more ‘flexible’ labour markets). Therefore, anybody attempting to understand the within-nations disparity of inequality should always be reminded of this basic distributional fact following the example of Clinton’s campaign strategist: by sticking a note on their notice-boards saying “It’s the share of the rich, stupid”.