投资组合VaR分解的应用研究

针对VaR的不足,Garman M．于1997年提出了成分VaR和边际VaR。采用德尔塔——正态法度量投资组合的VaR、边际VaR和成分VaR,使用假设检验法对模型进行回测的研究结果表明,该计算方法下的VaR模型有效,边际VaR和成分VaR能为资产管理者提供更多有关投资组合风险的信息。     

最小平均VaR套期保值比率计算模型及实证研究

针对传统的套期保值模型只考虑最小化套期保值组合在到期日的价格风险,而且没有充分利用资产历史价格样本数据所提供的收益率信息的特点,本文提出了考虑套期保值期内不同期限价格风险的最小平均VaR套期保值比率计算模型。基于我国外汇市场及股票市场数据,本文对最小平均VaR套期保值模型进行了实证分析,并与常用的最小方差及最小VaR套期保值模型进行了对比,得出了最小平均VaR模型在套期保值过程中的效果要优于其他两种模型,能更有效地降低投资者提前终止套期保值可能面临额外风险的结论。     

Modelling VaR for foreign-asset portfolios in continuous time

VaR is widely viewed as a measure of market risk of a portfolio. The purpose of this article is to provide a VaR model for foreign-asset portfolios in continuous time. In the VaR model, the VaRs are not only a function of volatilities of asset returns and exchange rate but also a function of correlation coefficient between foreign assets and exchange rate. Moreover, by backtesting, the empirical results show that the new VaR model can efficiently evaluate the market risk of foreign-asset portfolios.     

科技保险基金风险管理与投资策略研究展望

在介绍科技保险与再保险研究情况的基础上,探讨如何针对科技保险的风险机制和保险特征研究科技保险基金的风险管理与投资策略问题。在综述相关研究现状与趋势后认为,可从以下方面展开：建立风险资产模型,构造一个新型风险函数,研究最优再保险策略与各参数之间的关系以及最优分红策略,并研究风险资产模型对破产概率和确定时刻预期累计收益的影响;研究再保险方式对破产概率和确定时刻预期累计收益的影响;研究不同效用函数对不同确定时刻预期累计收益的影响,并引入不同风险测度方法,研究在不同情形下如何选择最优风险测度准则;考虑再保险双方,设计一种新的保险机制;建立试点平台,采集大量经验概率,并以此为基础建立科技保险的费率厘定模型,进而形成一套方法体系。     

Incentive contracts in delegated portfolio management under VaR constraint

This paper studies the incentive effect of linear performance-adjusted contracts in delegated portfolio management under a value-at-risk (VaR) constraint. It is shown that a linear performance-based contract can provide incentives for the portfolio manager to work at acquiring private information under a VaR risk constraint. The expected utility and optimal effort of a risk-averse manager are increasing functions of the return sharing ratio in the contract. However, a risk constraint causes the portfolio manager to reduce effort in gathering private information, suggesting that the VaR constraint increases the moral hazard between the investor and the manager.     

Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash

Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.     

我国国际储备资产的最优结构研究——基于时变Copula及VaR的投资组合模型分析

文章通过构建效用评估函数,使用时变相关T-Copula模型、Monte Carlo模拟和VaR计算方法系统研究了我国国际储备的最优结构。结果发现,我国黄金的最优占比应至少为23%。据此,文章对多个国家储备资产的变化情况进行了动态和静态比较,发现不同类别的演化路径,而以我国和其他金砖四国为代表的类别处于收益递减、风险增大的状态中,亟须加大黄金储备至优化区间。     

Portfolio optimization through Kriging methods

This article presents a new methodology for optimizing financial asset portfolios. The proposed methodology, based on the Kriging method, allows for approximating the risk surface – and thus the optimal solution to the problem – in a generalized fashion, relaxing every restrictive hypothesis inherent to the available methods and with the ability to estimate the error in the risk surface approximation. Illustratively, the proposed methodology is applied to the portfolio problem with the Variance, VaR and CVaR as objective functions. The results are compared to those obtained using the Khun–Tucker technique, for the former, and the Rockafellar method, for the latter.     

基于GARCH模型的证券投资基金VaR计算与实证研究

基于统计技术的度量金融市场风险值(Value at Risk,VaR)已成为测量市场风险的新标准和新方法。鉴此,如何高效、准确地进行VaR的计算将是问题所在。基于GARCH模型,讨论了对数收益率时间序列在正态、学生t和广义误差(GED)三种不同分布下的VaR计算方法,对样本基金的市场风险进行估计,并通过返回检验来检验模型的准确性。研究结果表明,基于GED分布的GARCH模型计算的VaR值最能真实地反映基金风险。     

VaR-implied tail-correlation matrices

Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail-correlation matrices based on Value-at-Risk (VaR) estimates. We demonstrate how to obtain more efficient tail-correlation estimates by use of overidentification strategies and how to guarantee positive semidefiniteness, a property required for valid risk aggregation and Markowitz-type portfolio optimization. An empirical application to a 30-asset universe illustrates the practical applicability and relevance of the approach in portfolio management.     

我国主要证券市场VaR模型变动性研究

对证券市场风险度量模型的探索,一直是国内外金融风险管理者关注和研究的热点之一。VaR(Value-at-Risk)风险度量模型,目前已成为金融机构、非金融企业、金融监管部门测量和监控市场风险的主流工具。然而VaR模型能否有效正确地度量证券市场风险,不但取决于估计的精度,还取决于选用VaR模型本身的变动性。因此,探索我国主要证券市场VaR模型的变动性,有一定的现实意义。针对我国主要证券市场指数,本文首先通过图形展示了三类(参数、半参数和非参数)VaR估计方法在不同的窗口设定下控制风险的表现;其次在平均相对偏差(MRB)和平方根相对偏差(RMSRB)的双重标准下,对三类VaR估计模型的变动性进行了比较研究,结果表明:在我国主要证券市场上,参数类VaR估计模型本身的变动性和偏离程度较小,半参数类VaR估计模型次之,而非参数类VaR估计模型本身的变动性和偏离程度较大,这在一定程度上符合新兴国家证券市场存在较大投机收益的特点。     

大宗农产品价格风险评估——基于小波神经网络-Bootstrap方法的实证研究

构建了一个将小波神经网络与Bootstrap抽样相结合的价格风险评估模型。采用国际通用的VaR(在险价值)风险指标评估了国内小麦、水稻、玉米、大豆和棉花5种主要大宗农产品现货价格的风险水平,仿真研究了以上大宗农产品价格下跌风险和价格上涨风险的分布特征。结果表明:按价格风险水平由高到低对5种主要大宗农产品进行排序依次为棉花、大豆、玉米、小麦和水稻;从风险均值来看,我国大宗农产品价格特别是粮食价格的风险处于较低水平;从风险的经验分布来看,除大豆外,其他大宗农产品(特别是小麦、水稻和玉米)的涨价风险高于跌价风险;5种农产品的价格均存在偏度风险和峰度风险。     

标准仓单质押组合的价格风险——基于中国农产品期货规范市场的实证研究

利用基于Copula函数的AR(p)-GARCH(p,q)模型计算的VaR能够对农产品标准仓单的价格风险进行准确度量。对大连商品交易所的典型期货交易品种——黄大豆一号、豆油、豆粕的期货合约日结算价进行了实证研究。研究结果显示:从对价格风险预测的盯市频率来看,时变VaR优于静态VaR,因此重视农产品价格风险的频次预测应替代传统风险判断的单次监测;从对风险因子间相依性结构的刻画来看,基于t-Copula函数计算的VaR优于基于正态Copula函数计算的VaR,因此质押物价格波动间的相关系数是度量组合风险时必须考虑的重要变量。     

Consumption versus asset smoothing: testing the implications of poverty trap theory in Burkina Faso

Despite solid theoretical foundations for the notion that poor, borrowing-constrained households will intertemporally manage assets to smooth consumption, the consumption-smoothing hypothesis has not always withstood empirical scrutiny. This paper reassesses the intertemporal asset management problem with a poverty trap model and shows that we would expect to see asset smoothing, not consumption smoothing, in the neighborhood of critical asset levels at which optimal accumulation behavior bifurcates. We then employ threshold estimation techniques to empirically confirm the co-existence of consumption and asset smoothing regimes using a household panel data set from West Africa. Households above the estimated threshold almost completely insulate their consumption from weather shocks, whereas those below the threshold do not. These results not only indirectly provide evidence of the existence of poverty traps but also speak to the level and incidence of the costs of uninsured risk.     

Calculating Value-at-Risk for high-dimensional time series using a nonlinear random mapping model

In this study, we propose a non-linear random mapping model called GELM. The proposed model is based on a combination of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the Extreme Learning Machine (ELM), and can be used to calculate Value-at-Risk (VaR). Alternatively, the GELM model is a non-parametric GARCH-type model. Compared with conventional models, such as the GARCH models, ELM, and Support Vector Machine (SVM), the computational results confirm that the GELM model performs better in volatility forecasting and VaR calculation in terms of efficiency and accuracy. Thus, the GELM model can be an essential tool for risk management and stress testing.     

股票资产组合VaR研究基于混合D藤Copula模型

本文在对上证市场五种股票资产组合的风险分析中以VaR作为风险度量指标,采用基于Pair Copula高维建模理论的混合D藤Copula模型,建立了反应多个资产组合相关结构的联合分布模型。该模型对传统D藤Copula建模方法作了进一步的改进,通过一定的选择标准,确定了D藤中每个Pair Copula函数的最优函数族,这样使得所建立的模型不仅考虑到了资产维数的影响,而且还能捕捉到组合内部因子间相关结构的差异性,从而改进后的模型能更好地描述资产组合的相关结构,并且能更精确地反映资产组合收益的实际分布。最后,以混合D藤Copula模型为基础,利用Monte Carlo方法计算了上证市场五种股票资产组合的VaR,并通过实证研究进一步证明了该模型的有效性。     

Growth Optimal Investment Strategy: The Impact of Reallocation Frequency and Heavy Tails

The strategy to maximize the long‐term growth rate of final wealth (maximum expected log strategy, maximum geometric mean strategy, Kelly criterion) is based on probability theoretic underpinnings and has asymptotic optimality properties. This article reviews the allocation of wealth in a two‐asset economy with one risky asset and a risk‐free asset. It is also shown that the optimal fraction to be invested in the risky asset (i) depends on the length of the basic return period and (ii) is lower for heavy‐tailed log returns than for light‐tailed log returns.     

跳跃随机波动的阈值模型风险值的贝叶斯估计

文章基于一类跳跃随机波动的阈值模型风险值估计贝叶斯分析,在给定先验分布下,以马尔科夫链蒙特卡洛方法估计模型中的未知参数,并给出了MCMC模拟算法,进而讨论了风险值的预测。根据模拟结果,我们得知,如果没有考虑金融时间序列的外生冲击导致的跳跃行为,将会高估风险值,因此考虑跳跃行为后,将增加风险值估计的精度。     

基于VaR的沪深300股指期货风险管理实证研究

我国以沪深300为标的指数的股指期货即将推出。股指期货在具有控制风险功能的同时,也与其他金融衍生产品一样,具有风险性,且其风险远远大于股票现货市场。因此,必须采用积极的风险管理技术,加强对股指期货的风险防范。在GARCH模型的基础上,采用VaR方法对我国的沪深300股指期货仿真交易进行定量研究,计算出它们的VaR值,并将其与期望值进行比较。经过对比分析可以得出:基于GARCH模型的VaR方法适合我国的股指期货风险管理。