我国黄金期货市场价格波动研究

以上海期货交易所2008年1月9日至2011年6月30日的黄金期货市场量价关系为研究对象,构建了GARCH(异方差)族模型检验我国黄金期货市场的价格波动特征.研究结果表明,当分别引入黄金期货市场的交易量和持仓量时,交易量对价格波动的影响在当期和滞后期均十分显著,而持仓量对价格波动的影响在当期显著,滞后期则不显著;当同时引入黄金期货市场交易量和持仓量时,他们对价格波动的解释作用增加,且当期统计检验显著,滞后期效应则不明显.     

Portfolio optimization based on GARCH-EVT-Copula forecasting models

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-$t$ and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-$t$ copulas, are best at reducing the portfolio risk.     

汽车行业股价波动性的实证研究——基于GARCH类模型

近年来，我国汽车产业发展迅猛，汽车股价波动日趋复杂。鉴于GARCH模型能够较好地拟合时间序列的尖峰厚尾特征．本文采集了2008年1月1日至2009年11月30日共计1260个道琼斯第一财经中国600汽车和零件行业领先指数的数据，并将其分为熊市牛市两个阶段．运用GARCH类模型进行实证分析，证实了我国汽车行业股价具有尖峰厚尾、显著异于正态分布的特征，说明了两阶段股市中均存在杠杆效应，同时得出了收益随风险的增加而增加的现象在熊市中更加明显。     

STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG‐RUN RESTRICTIONS VIA HETEROSKEDASTICITY

Long‐run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long‐run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.     

The perception of biotechnology in agro-forestry: The opinion of undergraduates and researchers

Genetically modified organisms (GMOs) cropping promoted by different researchers, and the subsequent crisis regarding the safety of food derived from them, has resulted in strong public mistrust towards the authorities, both scientific and political. The aim of this work is to investigate the perception of Italian undergraduates and researchers towards the introduction of GMOs in agro-forestry. The factors determining attitudes towards GMOs were examined by means of 66 questions divided into three units: Knowledge, Opinon, Trust. Anagrafic and socio-cultural information were also analyzed. Data was processed through a multivariate analysis approach. The hierarchical clustering on undergraduates and researchers allowed to distinguish clusters of respondents skilled in biotechnology from those skilled in off-topic disciplines. Principal component analysis and K-means demonstrated that the positive or negative opinion toward GMOs, as for undergraduates, does not depend on their knowledge, but it is associated with the level of trust in the institutions. On the contrary, for researchers, it is related to their expertise level, without any linkage to trust in the institutions. This type of study may represent a key step for understanding the social, economic and scientific components underlying the choices of citizens, communities and society about GMOs.     

Litteraturanmeldelse

This article examines the notion of distortion of copulas, a natural extension of distortion within the univariate framework. We study three approaches to this extension: (1) distortion of the margins alone while keeping the original copula structure; (2) distortion of the margins while simultaneously altering the copula structure; and (3) synchronized distortion of the copula and its margins. When applying distortion within the multivariate framework, it is important to preserve the properties of a copula function. For the first two approaches, this is a rather straightforward result; however, for the third approach, the proof has been exquisitely constructed in Morillas (2005). These three approaches unify the different types of multivariate distortion that have scarcely scattered in the literature. Our contribution in this paper is to further consider this unifying framework: we give numerous examples to illustrate and we examine their properties particularly with some aspects of ordering multivariate risks. The extension of multivariate distortion can be practically implemented in risk management where there is a need to perform aggregation and attribution of portfolios of correlated risks. Furthermore, ancillary to the results discussed in this article, we are able to generalize the formula developed by Genest &; Rivest (2001) for computing the distribution of the probability integral transformation of a random vector and extend it to the case within the distortion framework. For purposes of illustration, we applied the distortion concept to value excess of loss reinsurance for an insurance policy where the loss amount could vary by type of loss.     

Impacts of derivative markets on spot market volatility and their persistence

In this article, we investigate the impacts of futures and options markets on the volatility of the underlying market. Unlike earlier studies, the focus is on their persistence over time. Tests on the Hang Seng index yield several interesting results that often contrast with previous findings. Empirical results suggest that the quality of new information generated by derivative trading determines the impacts on the spot market volatility. The futures market provides new, material information reducing spot market volatility. The Options market, on the other hand, generates noisy information and distorts price, which is followed by an increase in volatility and a decrease in its sensitivity to price change. While the impact of futures persists, that of options mostly disappears as the market matures. Our conjecture is that the futures market is mainly driven by informed, experienced participants, while the options market attracts new, inexperienced investors.     

基于VaR修正理论的投资组合优化模型

根据风险价值VaR的计算思路,本文提出了基于GARCH理论的风险计量投资组合优化模型;同时在修正的VaR——尾条件期望的基础上对证券组合投资的优化模型做了进一步的改进。     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.