An Improved Fixed-Rate Mortgage Valuation Methodology with Interacting Prepayment and Default Options

This paper considers in detail a realistic mortgage valuation model (including the potential for early prepayment and the risk of default), based on stochastic house-price and interest-rate models. As well as the development of a highly accurate numerical scheme to tackle the resulting partial differential equations, this paper also exploits singular perturbation theory (a mathematically rigorous procedure, based on the idea of the smallness of the volatilities), whereby mortgage valuation can be accurately approximated by very simple closed-form solutions. Determination of equilibrium contract rates, previously requiring many computational hours is reduced to just a few seconds, rendering this a highly useful portfolio management tool; these approximations compare favorably with the full numerical solutions. The method is of wide applicability in US or other mortgage markets and is demonstrated for UK fixed-rate mortgages, including insurance and coinsurance.     

Spatial patterns of poverty in Vietnam and their implications for policy

This study examines the geographic distribution of poverty in Vietnam by applying small area estimation methods to household budget data and population census data. The resulting district-level poverty estimates suggest that the incidence of poverty is highest in the remote northern and central highlands and lowest in the south-east and in large urban centres. However, mapping the density of poverty reveals that most poor people do not live in the poorest districts but in the two lowland deltas, where poverty incidence is intermediate. The policy implications of these findings present an important trade-off between targeting poor areas and poor people that can only be resolved with better information on the relative costs of delivering different programmes and their expected impact. Existing government estimates of poverty at the district level are not closely correlated with our poverty estimates, perhaps because of regional variation in their methods of collecting poverty data.     

Resurrecting the size effect: Evidence from a panel nonlinear cointegration model for the G7 stock markets

Firm size is known to be an important factor affecting stock returns. This study proposes a panel threshold cointegration model to investigate the impact of the size effect on stock returns for the panel of G7 countries: Canada, France, Germany, Italy, Japan, the U.K., and the U.S. over the period 1991:1–2012:12. The empirical analysis is based upon the nonlinear cointegration framework using the asymmetric ARDL cointegration methodology (Shin et al., 2011). This methodological approach permits a much richer degree of flexibility in the dynamic adjustment process toward equilibrium, than in the classical linear model. Our findings indicate the presence of asymmetric adjustment around a unique long-run equilibrium. In particular, the empirical analysis provides evidence of asymmetric effects between stock returns and the size effect, while controlling for the book-to-market ratio and the price-to-earnings ratio.     

Election predictions as martingales: an arbitrage approach

The more volatile the prediction the closer to an even call     

Why are African commodity exchanges languishing? A case study of the Zambian Agricultural Commodity Exchange

Food price volatility and high transactions costs remain major problems in African food markets. These persistent problems provide a strong theoretical justification for the development of commodity exchanges. However, the majority of African commodity exchanges remain underdeveloped. Through a case study of the Zambian Agricultural Commodity Exchange (ZAMACE), this article explores why agricultural commodity exchanges in the region have thus far failed to develop into sustainable trading platforms and identifies the most important changes needed to enhance their performance.     

Gibbs posterior inference on value-at-risk

ABSTRACT

Accurate estimation of value-at-risk (VaR) and assessment of associated uncertainty is crucial for both insurers and regulators, particularly in Europe. Existing approaches link data and VaR indirectly by first linking data to the parameter of a probability model, and then expressing VaR as a function of that parameter. This indirect approach exposes the insurer to model misspecification bias or estimation inefficiency, depending on whether the parameter is finite- or infinite-dimensional. In this paper, we link data and VaR directly via what we call a discrepancy function, and this leads naturally to a Gibbs posterior distribution for VaR that does not suffer from the aforementioned biases and inefficiencies. Asymptotic consistency and root-n concentration rate of the Gibbs posterior are established, and simulations highlight its superior finite-sample performance compared to other approaches.     

中国经济再平衡的算术题

本文认为,只要中国经济保持较快增长,降低投资增速,扩大消费支出,实现年均GDP增速7.5%,投资占GDP比重年均下降1%,消费水平年均增长9.7%,中国可能在10年内实现经济再平衡。而且,政治改革并非经济再平衡的前提条件。