Pricing mortgage insurance contracts under housing price cycles with jump risk: evidence from the U.K. housing market

Previous studies have investigated the determinants of housing price cycles in the housing market; however, we observed the phenomenon of housing price jumps in the 2007 subprime crisis. This paper presents a discussion on the housing price cycle and abnormal price jumps to describe the behavior of housing prices in the United Kingdom. The empirical results show that the impact factors of housing cycles are market risk and the switching factor. Furthermore, the impact factors of jump risks include the bursting of the housing bubble and financial crises. Therefore, in this paper, we employ the Markov switching model with jump risks to value the MI contracts and analyze the influences of housing price cycles, jump risks, risks of market interest rate, and the prepayment risks on MI premiums. The results of sensitivity analysis show that more volatile housing price index returns, as well as longer periods of higher volatility in housing prices, raise MI premiums. Moreover, the MI premium is positively related to the absolute value of the average jump amplitude and the shock frequency of abnormal events. There is the tradeoff between the market interest rate and the prepayment risk. The influences of market interest rate are different on MI premium with/without prepayment risks.     

Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

In this article, Copula GARCH models have been employed to study the inter-temporal process of currency market co-movements between ASEAN+6 countries (referred to in this study as East Asian Economic Community) and ASEAN+6 currency market index. Empirical results show that the sample countries of the region exhibit varying levels of currency co-movements with the Asian benchmark. Markov regime switching results show that many of the countries which had high dependences with the regional currency index as was found in copula estimations had also overlapping currency market cycles. Using Principal Component Analysis, we find that three statistical factors explain exchange rate co-movements which came out to be trade linkages, economic risk, and currency market openness in our dynamic panel data estimation.     

Export Sophistication: A Dynamic Panel Data Approach

In this article, we analyze export sophistication based on a large panel dataset (2001–2015; 101 countries) and using various estimation algorithms. Using Monte Carlo simulations, we evaluate the bias properties of estimators and show that GMM-type estimators outperform instrumental-variable and fixed-effects estimators. Based on our analysis we document that GDP per capita and the size of the economy exhibit significant and positive effects on export sophistication; weak institutional quality exhibits negative effect. We also show that export sophistication is path-dependent and stable even during a major economic crisis, which is especially important for emerging and developing economies.     

Non-coercive influence: Scale development and validation based on resource and relational paradigms

To overcome competition in an increasingly network dependent market, retailers are required to influence upstream channel partners while sustaining relationships. However, the contemporary supply chain literature has not sufficiently leveraged the resource and relational paradigms to examine influence. Grounded on resource dependency theory and commitment-trust theory paradigms, this study describes conceptualization and operationalization of a 12-item scale for measuring non-coercive influence on upstream channel partners in retail supply chain management (R-SCM) context. The study is based on responses from 547 retail professionals in India obtained over four successive surveys. Psychometric properties were assessed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The proposed scale demonstrates construct validity. Invariance-testing carried out over 4-levels of increasingly demanding equivalence confirmed cross-validation. Nomological validity of the scale was tested by evaluating association with suppliers’ intention to cooperate. The results indicate existence of three dimensions of non-coercive influence: collaborative intent, market intelligence dissemination, and operational support. Retailers can use the scale to assess their personnel's non-coercive influence behavior over suppliers.     

Optimizing the credit term decisions in supply chain finance

We study a credit term determination problem in the context of a supplier-buyer supply chain. The supplier's credit term decision is simultaneously made with its production and inventory decisions, and most importantly, it is impacted by the buyer's order quantity. We present a new game-theoretic framework to model this problem, which captures the interaction between the supplier's credit term decision and the buyer's order decision in a multi-period setting. An exact method based on nonlinear programming is implemented to obtain the optimal solutions. We apply our methodologies on a real world case. The computational results show that our approach significantly outperforms the heuristics with fixed credit terms, and either a short or a long credit term can be sub-optimal for the supplier in profitability. Our work offers the first data-driven model and solution approach that assists purchasing and supply managers to make optimal dynamic credit term decision in conjunction with production, ordering and inventory decisions in a game-theoretic setting.     

Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

互联网企业价值评估模型比较研究

基于互联网企业轻资产、高估值、迭代快以及风险大等特点,比较传统价值评估模型与Schwar-tz-Moon等实物期权价值评估模型,分别运用于评估案例企业泛微网络价值.结果发现,相较于传统现金流贴现模型,实物期权价值评估模型评估结果更接近于公司实际价值.三种实物期权模型敏感性分析表明:Schwartz-Moon模型评估误差最小,且模型稳健性最强,适用于不确定性高的互联网企业估值.     

随机利率影响下信用风险的Monte—Carlo模拟

在前人利用马尔科夫链表示公司信用等级的基础上,将信用等级和随机利率引入离散时间的信用风险模型中,从而提出随机利率影响下的新的信用风险模型。就上述模型,对不同初始信用等级、初始盈余以及不同时刻的破产概率进行Monte—Carlo模拟,并讨论了相同条件下初始盈余与破产概率、初始信用等级与破产概率以及时间长短与破产概率之间的相互关系。     

电子信息产业国内价值链省域比较优势测度及空间差异研究

为应对后疫情时代全球电子信息产业加剧的“比较优势陷阱”,中国亟需通过国内价值链省域比较优势的互补协同提升整体国际竞争力。在价值链产品内,基于垂直专业化分工框架,兼顾增值能力与劳动生产率两个维度,使用非竞争型投入占用产出模型,设计一个评测国家内部区域电子信息产业真实比较优势的新指标。结果表明,东部沿海省域比较优势强度与广度最为显著,内陆省域比较优势集中于上游能源型部门;制造业部门比较优势凸显,服务业部门比较优势相对薄弱;比较优势高省域集中度与低省域集中度的产业部门中,均存在整体比较优势强弱差异,其中,高省域集中度产业部门比较优势强度更高。     

Non-linear dynamics in international resource markets: Evidence from regime switching approach

This paper examines the nonstationary and nonlinear features of the non-renewable resource markets: the crude oil (US West Texas Intermediate and UK Brent), bituminous coal and natural gas markets. In particular, we achieve this goal by using the Markov switching unit root regression. This approach is attractive because it allows price to switch between stationary and nonstationary regimes (partial nonstationarity). It also allows price to switch between two stationary regimes (varied stationarity) or to switch between two nonstationary regimes (varied nonstationarity). The results of a range of non-linear tests show that the independently and identically distributed (i.i.d.) hypothesis or the random walk hypothesis is untenable for the non-renewable resource prices. The results from the Markov regression indicate that, in the cases of US West Texas Intermediate, UK Brent as well as bituminous coal, prices are characterized by the local nonstationarity in both regimes, and therefore varied nonstationarity is sustained. The price of natural gas is characterized by partial nonstationarity, indicating that this market is inconsistent with the efficient market.