ARBITRAGE BOUNDS FOR PRICES OF WEIGHTED VARIANCE SWAPS

We develop a theory of robust pricing and hedging of a weighted variance swap given market prices for a finite number of co‐maturing put options. We assume the put option prices do not admit arbitrage and deduce no‐arbitrage bounds on the weighted variance swap along with super‐ and sub‐replicating strategies that enforce them. We find that market quotes for variance swaps are surprisingly close to the model‐free lower bounds we determine. We solve the problem by transforming it into an analogous question for a European option with a convex payoff. The lower bound becomes a problem in semi‐infinite linear programming which we solve in detail. The upper bound is explicit. We work in a model‐independent and probability‐free setup. In particular, we use and extend Föllmer's pathwise stochastic calculus. Appropriate notions of arbitrage and admissibility are introduced. This allows us to establish the usual hedging relation between the variance swap and the “log contract” and similar connections for weighted variance swaps. Our results take the form of a FTAP: we show that the absence of (weak) arbitrage is equivalent to the existence of a classical model which reproduces the observed prices via risk‐neutral expectations of discounted payoffs.     

区间时变时滞线性系统稳定性准则的改进

研究了区间时变时滞线性系统的稳定性问题,基于Lyapunov泛函方法,使用新的处理技术估计Lyapunov泛函导数的上界,以线性矩阵不等式形式给出了系统稳定性准则的改进结果。所给稳定性准则比已有结果具有更低的保守性,数值实例表明了结果的有效性。     

Assessing the economic impact of entrepreneurship on a regional economy using social accounting matrices: the case of Andalusia

This article analyses the impact that entrepreneurial activity has, from the economic point of view, on a regional economy (Andalusia), based on a Social Accounting Matrix linear model. Moreover, to measure entrepreneurship at regional level, it is defined what can be considered an entrepreneurial initiative company from a quantitative point of view. The results obtained, in terms of Production, GDP and job creation, show how entrepreneurship, in the case of Andalusia, contributes to the sustainability of the economy, its growth and, above all, the reduction of unemployment in the short term.     

The dynamics of financial development,globalisation, economic growth and life expectancy in sub‐Saharan Africa

The importance of life expectancy is recognised in the development economics literature because of its increasing effects on labour productivity and economic growth in long‐run. However, no published study to date empirically examines the nonlinear relationships between globalisation, financial development, economic growth and life expectancy in sub‐Saharan African (SSA) countries. Therefore, our study intends to fill this gap by using non‐parametric cointegration test and multivariate Granger causality test towards a non‐linear empirical understanding of the factors affecting the life expectancy. We consider the case of 16 sub‐Saharan African economies using annual data over the period 1970–2012. The empirical analysis indicates that financial development, globalisation and economic growth appear to have a positive impact upon life expectancy in sub‐Saharan African economies, except for Gabon and Togo. Our empirical findings may provide insightful policy implications towards improving population health conditions which are vital for promoting the productivity of labour force and long‐run economic growth in sub‐Saharan African countries. In light of these policy implications, governments should incorporate globalisation, financial development and economic growth as key economic instruments in formulating sustainable developmental policy to promote life expectancy for the people in sub‐Saharan African countries.     

Predicting bid prices by using machine learning methods

It is well-known that empirical analysis suffers from multicollinearity and high dimensionality. In particular, this is much more severe in an empirical study of itemized bids in highway procurement auctions. To overcome this obstacle, this article employs the regularized linear regression for the estimation of a more precise interval for project winning bids. The approach is put to the test using empirical data of highway procurement auctions in Vermont. In our empirical analysis, we first choose a set of crucial tasks that determine a bidder’s bid amounts by using the random forest variable selection method. Given the selected tasks, project bid forecasting is conducted. We compare our proposed methodology with the least square linear model based on the bias and the standard root mean square error of the bid estimates. There is evidence supporting that the suggested approach provides superior forecasts for an interval of winning bids over the competing model. As far as we know, this article is the first attempt to provide reference bids of highway construction contracts.     

提升算法对传统车险索赔频率建模模型的改进——基于我国五省交强险保单数据

广义线性模型作为非寿险定价的经典模型,在非寿险定价中得到了广泛的应用。近年来,以提升算法为代表的机器学习算法在保险领域取得了很好的效果,为保险产品定价提供了一种新的选择。本文将提升算法思想分别融入到回归树模型和广义线性模型(GLM)中去,用得到的新模型对我国车险索赔频率进行预测建模分析,并与传统的回归树模型和GLM进行比较。结果表明,加入提升算法后传统车险索赔频率建模模型的效果得到了很大的改善,并且在不存在过拟合的前提下,随着模型深度和迭代次数的增加,模型的效果也在不断优化。     

河南省城镇居民消费结构的比较实证分析

本文根据扩展线性支出系统模型的计算结果,通过横向和纵向比较,发现河南省城镇居民消费水平已经提高,消费结构已经得到提升,交通通信等享受性支出已经成为重点消费支出项目,但基本生存型消费仍然占较大比重,而且城镇居民收入差距对消费状况造成一定程度的影响。为此,提高河南省城镇居民收入水平是解决问题的根本途径,同时,消费信贷种类的增加,社会保障水平的提高等也是解决问题的有效方法。     

直线法线式方程在建筑施工放样中的应用

建筑物轴线的放样主要是计算出各轴线的交点的坐标,然后通过全站仪极坐标放样的方法定出轴线交点的位置。由于建筑物坐标系和测量坐标系不同,应先通过坐标转换将建筑物轴线交点转换为测量指标,本文提出无需进行坐标转换,而是通过建立建筑方格网主轴线法线式直线方程,并以此推求出建筑物轴线的法线式直线方程,进而通过解方程组求得交点坐标。     

线性和非线性视角下的费雪效应实证检验

基于2000年1月~2009年12月我国名义利率和通货膨胀率均为非平稳时间序列的事实,采用Johansen协整检验和门限协整(threshold cointegration)两种方法对我国是否存在费雪效应进行检验;实证发现,两种方法均支持我国存在弱费雪效应,但得出来的弱费雪效应程度却存在差别,前者认为我国通货膨胀率的变化只有6%反应到名义利率上面,而后者认为这个比例达到42.4%。     

Tourist market segmentation with linear and non-linear techniques

The need for in-depth knowledge of tourist market segments and the need to overcome the limitations of using linear techniques to analyse non-linear relationships requires a re-assessment of generally used approaches such as cluster analysis and multiple linear regression. The objectives of the research are (1) to consider the use of self-organising (SOM) neural networks for segmenting tourist markets and (2) to analyse the predictive ability of backpropagation (BP) neural networks for classifying tourists from follow-up surveys by using the output provided by a SOM neural network. The findings of the SOM neural network modelling indicate three natural clusters. In addition, the predictive ability of the BP neural network model appears to be superior to that of MLR static filter and logistic regression models. The BP neural network model developed for this application appears suitable for deployment (i.e. classification of tourists from follow-up surveys).