Relationship between oil,stock prices and exchange rates: A vine copula based GARCH method

In this paper, we apply a vine copula approach to investigate the dynamic relationship between energy, stock and currency markets. Dependence modeling using vine copulas offers a greater flexibility and permits the modeling of complex dependency patterns for high-dimensional distributions. Using a sample of more than 10 years of daily return observations of the WTI crude oil, the Dow Jones Industrial average stock index and the trade weighted US dollar index returns, we find evidence of a significant and symmetric relationship between these variables. Considering different sample periods show that the dynamic of the relationship between returns is not constant over time. Our results indicate also that the dependence structure is highly affected by the financial crisis and Great Recession, over 2007–2009. Finally, there is evidence to suggest that the application of the vine copula model improves the accuracy of VaR estimates, compared to traditional approaches.     

A NEW LOOK AT SHORT‐TERM IMPLIED VOLATILITY IN ASSET PRICE MODELS WITH JUMPS

We analyze the behavior of the implied volatility smile for options close to expiry in the exponential Lévy class of asset price models with jumps. We introduce a new renormalization of the strike variable with the property that the implied volatility converges to a nonconstant limiting shape, which is a function of both the diffusion component of the process and the jump activity (Blumenthal–Getoor) index of the jump component. Our limiting implied volatility formula relates the jump activity of the underlying asset price process to the short‐end of the implied volatility surface and sheds new light on the difference between finite and infinite variation jumps from the viewpoint of option prices: in the latter, the wings of the limiting smile are determined by the jump activity indices of the positive and negative jumps, whereas in the former, the wings have a constant model‐independent slope. This result gives a theoretical justification for the preference of the infinite variation Lévy models over the finite variation ones in the calibration based on short‐maturity option prices.     

Kernel-type estimators for the distortion risk premiums of heavy-tailed distributions

A new kernel-type estimator for the distortion risk premiums of heavy-tailed losses is introduced. Using a least-squares approach, a bias-reduced version of this estimator is proposed. Under suitable assumptions, the asymptotic normality of the given estimators is established. A small simulation study, to illustrate the performance of our method, is carried out.     

When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods

This paper uses three classes of univariate time series techniques (ARIMA type models, switching regression models, and state-space/structural time series models) to forecast, on an ex post basis, the downturn in U.S. housing prices starting around 2006. The performance of the techniques is compared within each class and across classes by out-of-sample forecasts for a number of different forecast points prior to and during the downturn. Most forecasting models are able to predict a downturn in future home prices by mid 2006. Some state-space models can predict an impending downturn as early as June 2005. State-space/structural time series models tend to produce the most accurate forecasts, although they are not necessarily the models with the best in-sample fit.     

Measuring systemic risk with regime switching in tails

This paper motivates the importance of modeling nonlinearities in measuring systemic risk. I capitalize this motivation by generalizing the CoVaR approach proposed by Adrian and Brunnermeier (2016) to allow it switching between a high and a normal risk regime filtered from data.. Considering the U.S. large bank holding companies (BHCs), this paper shows that modeling regime changes in tails is capable of capturing both amplification and mean-reversion effects of an adverse shock to a bank's balance sheet on the banking system. Using the Kolmogorov–Smirnov test statistics with and without bootstrapping, I perform the significance test to identify systemically important financial institutions (SIFIs), and the stochastic dominance test to rank the identified SIFIs. The stochastic dominance test raises the concern that the CoVaR measure underestimates systemic risk contributions for SIFIs but overestimates for non-SIFIs. Finally, applying the BHCs' characteristics and housing market price to forecast the regime-switching systemic risk out-of-sample, I obtain from 4- and 8-quarter-ahead horizons a desirable countercyclical, forward-looking measure of systemic risk.     

有关过程能力指数基准的若干问题

基准是过程能力指数的一个重要属性，对有关过程能力指数基准的若干问题作出详尽阐述，可为进一步纠正过程能力指数公式错误（诸如Cpk、CpU、CpL等）提供了理论基础。     

评价阻燃纤维及其性能表征方法研究

阻燃纤维的研究和生产发展迅速，但尚无建立适合纤维形态的阻燃性能检测方法和评判标准。纤维阻燃性能测检方法的空白已在很大程度上制约阻燃纤维产品的开发和市场推广。经过三年的不懈努力，我们建立了涤纶和粘胶短纤维及涤纶长丝阻燃性能试验方法——氧指数法来表征其阻燃性能。     

The niponic management of human resources in the performance of the enterprises in the Iberian Peninsula

This article had an objective of studying the niponic management of human resources in the performance of the enterprises that work in the Iberian Peninsula. The search was to evaluate the competition in these enterprises when the niponic management of human resources was used. There were two used data base： one with an economic nature treating the performance of productivity in an enterprise economic view, of salary and technologic, and the other about the niponic management of human resources adopted by the enterprises using an list of questions. Through statistic evaluations it was verified that the competition between enterprises with niponic capital, it＇s not induced by the economic competition, and the same enterprises used competitive strategies based on the qualification of the human resources and technological process.     

The Hong Kong tourist satisfaction index

This study develops a tourist satisfaction assessment system based on a dual-model framework and demonstrates its general applicability. The first model concerns tourist satisfaction and its key antecedents and consequences. Structural equation modelling is employed to investigate the relationships amongst the constructs in the theoretical framework, and is then used as a basis for the computation of sectoral-level tourist satisfaction indexes. The second model is designed to estimate an aggregate service satisfaction index and an overall destination satisfaction index using a multiple indicator and multiple cause approach. The framework is applied to a large dataset that represents six tourism-related sectors and seven major source markets of inbound tourism to Hong Kong.     

Stochastic Dominance Analysis of iShares

Abstract

Country indices as represented by iShares exhibit non-normal return distributions with both skewness and kurtosis. Earlier studies provide procedures for determining the statistical significance of stochastic dominance measures and the Sharpe Ratio. This present study uses these refinements to compare the performance of 18 country market indices. The iShares are indistinguishable when using the Sharpe Ratio as no significant differences are found. In contrast, stochastic dominance procedures identify dominant iShares. Although the results vary over time, stochastic dominance appears to be both more robust and discriminating than the CAPM in the ranking of the iShares.