我国期货市场违约风险的研究

引入违约距离的概念,建立了期货市场违约风险评估模型,采用GARCH-M模型对期货合约价格收益的波动率进行估计.运用此模型研究了郑州商品交易所上市品种小麦的违约风险,所得结果与实际市场结果相吻合.因此,可以运用本文提出的期货市场违约风险评估模型能预测临近交割月时期货市场发生违约的概率,实时捕捉期货市场发生违约事件的信息.     

期货市场中持仓量及参与者对资产价格的影响研究

本文通过建立一个期货市场的均衡模型,提出在具有套保需求和有限风险承受能力的前提下,期货价格能够预测未来资产价格变动的方向,持仓量能够辅助预测未来资产价格变动的剧烈程度;此外,市场中不知情投机者具有风险调整市场收益的作用,不知情套保者的参与能够稳定市场。对于持仓量是否能够辅助预测未来资产价格变动的剧烈程度,本文利用中国商品期货市场数据进行了实证检验,结果表明与理论研究的结论一致。     

国际铜期货市场整合：沪铜国际影响凸显

本文运用含协整残差的双变量EGARCH模型,研究上海SHFE和伦敦LME铜期货市场的动态整合关系.统计结果显示两个市场的收益及其风险存在对称的溢出效应,全球铜市供求因素驱动最新收益和风险信息在两者之间传递。沪铜期货有突出的国际定价影响.在全球24小时交易中,LME和SHFE交替成为国际铜价的主要信息来源.SHFE和LME市场的收益变化均以对方市场的影响为主;市场风险则以本市场的影响为主.影响两个市场动态整合度的因素有滞后一期的市场风险、沪铜成交量、伦铜的超额收益等。     

Pricing stock and bond derivatives with a multi-factor Gaussian model

The martingale approach to pricing contingent claims can be applied in a multiple state variable model. The idea is used to derive the prices of derivative securities (futures on stock and bond futures, options on stocks, bonds and futures) given a continuous time Gaussian multi-factor model of the returns of stocks and bonds. The bond market is similar to Langetieg's multi-factor model, which has closed-form solutions. This model is a generalization of Vasicek's model, where the term structure depends on state variables following correlated mean reverting processes. The stock market is affected by systematic and unsystematic risk.     

Modeling carbon spot and futures price returns with GARCH and Markov switching GARCH models

This paper makes use of spot and futures market data to carry out a thorough analysis of the dynamics of carbon price returns in the European Union Emission Trading Scheme for the whole first commitment period from 2008 to 2012. Understanding the properties of carbon price returns is especially crucial for industries which have to comply with an emission trading system and other market participants such as risk managers and speculators. We therefore seek to develop accurate models which capture the behavior of carbon price returns comprehensively. We apply a broad spectrum of GARCH model specifications, using different distributions for model innovations. As both time series, spot and futures price returns, exhibit asymmetric behavior in their variance, we additionally take Markov regime switching models for the variance equation into consideration. Empirical results demonstrate that AGARCH, NARCH and GJR fit the data best. We further show that, in the error term of any model, fat-tailed distributions—in particular the generalized error distribution—significantly improve the fit. Additionally, as futures returns seem to carry informational content concerning subsequent spot returns, we propose a sound, yet parsimonious, spot returns model, well-suited to capturing the dynamics. Finally, the most appropriate models for spot and futures price returns are tested in an out-of-sample environment, and further checked for robustness in data subsets. Subsequently a model for each market is proposed.     

Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips

To create efficient funds appealing to a sector of bank clients, the objective of minimizing downside risk is relevant to managers of funds offered by the banks. In this paper, a case focusing on this objective is developed. More precisely, the scope and purpose of the paper is to apply the mean-semivariance efficient frontier model, which is a recent approach to portfolio selection of stocks when the investor is especially interested in the constrained minimization of downside risk measured by the portfolio semivariance. Concerning the opportunity set and observation period, the mean-semivariance efficient frontier model is applied to an actual case of portfolio choice from Dow Jones stocks with daily prices observed over the period 2005–2009. From these daily prices, time series of returns (capital gains weekly computed) are obtained as a piece of basic information. Diversification constraints are established so that each portfolio weight cannot exceed 5 per cent. The results show significant differences between the portfolios obtained by mean-semivariance efficient frontier model and those portfolios of equal expected returns obtained by classical Markowitz mean-variance efficient frontier model. Precise comparisons between them are made, leading to the conclusion that the results are consistent with the objective of reflecting downside risk.     

中国股指期现货市场间的非对称风险溢出效应——基于分位数Granger因果检验

为了揭示中国股指期现货市场之间风险溢出效应的非对称特征,本文利用已实现半方差将中国股指期现货市场的风险区分为下跌风险和上涨风险,并运用均值Granger因果检验和分位数Granger因果检验,考察两市场之间下跌风险溢出效应和上涨风险溢出效应的差异。研究发现,中国股指期现货市场之间不仅存在显著的下跌风险溢出,还存在显著的上涨风险溢出,而且溢出效应随着分位数区间不同而呈现出显著的非对称特征。一方面,期货市场对现货市场的下跌风险溢出在全部分位数区间均显著,而上涨风险溢出仅在分布的中间位置和上尾显著。另一方面,现货市场对期货市场的下跌风险溢出主要集中在尾部极端分位数区间,而上涨风险溢出主要集中在分布的中间位置和低分位数区间。     

沪深300股指期货价格发现能力研究

利用沪深300指数及其期货当月主力合约的5分钟高频数据,本文采用Granger因果检验、向量自回归模型、Johansen协整检验及向量误差修正模型,系统分析不同价格趋势下沪深300股指期货的价格发现能力。研究表明:第一,在上涨趋势中期货收益率单方面引起现货收益率变化,现货收益率不是引导期货收益变化的原因;但是,在下跌趋势中现货收益率与期货收益率具有相互引导的Granger因果关系。第二,无论在上涨阶段还是下跌阶段,期货市场都在价格发现能力方面处于主导地位。第三,期货价格与现货价格存在长期均衡关系,当二者短期内偏离均衡时,期货价格引导现货价格向均衡方向调整。     

天然气期货和现货价格间的相关性研究

基于天然气期货价格与现货价格序列间具有强非线性特征,本文将GARCH模型和Copula函数思想进行结合,同时考虑了天然气期货和现货价格间的时变相关结构,构建了时变Copula(GARCH-Normal、GARCH-GED和GARCH-t)模型,利用美国纽约商品交易所(NYMEX)Henry Hub交易中心天然气期货价格和现货价格数据进行实证研究。实证结果表明:GARCH-GED模型能够准确地拟合天然气期货与现货价格时间序列;时变SJC-Copula函数能够更好的描述天然气期货价格与现货价格间的相关性;天然气期货与现货价格间的相关性不是对称的,上尾的相关性小于下尾相的相关性。     

Modeling futures price dynamics on the RTS and MICEX indices

Reasons for the substantial differences of historical and theoretical futures prices on RTS and MICEX indices are investigated. A model is proposed that considers the observed differences for the modeling of futures prices within the risk assessment of a portfolio of derivatives using the Monte Carlo method.     

GARCH模型对期铜市场风险的研究

期货市场是一个高风险的市场,因此需要有效地控制并且监管风险。本文以上海期铜市场97年到04年的收盘价格为研究样本,通过拉格朗日检验,发现价格收益率序列服从ARCH过程,在正态、student-t和GED三种分布假设下,估计了GARCH(1,1)模型的参数,结果表明student-t假设下模型的拟和程度较好,然后利用EGARCH(1,1)-M模型检验了上海期铜市场杠杆效应和波动集群效应。最后在两种置信水平下,利用GARCH(1,1)和Risk Metrics方法计算了期铜市场每天的VaR,Kupiec检验表明基于t分布的GARCH(1,1)模型能更准确地反映上海期铜市场的风险。     

解读巴塞尔协议Ⅱ中内部评级法关于资本要求的计算

鉴于新巴塞尔协议中内部评级法关于资本要求的计算缺乏透明度,本文在归纳总结内部评级法关于资本要求计算的基础上,对资本要求计算的理论依据和统计含义进行了描述和分析。本文指出,资本要求计算的核心内容是Vasicek公式,它可以被解释为单一借款者的条件违约概率,或者单一个充分分散化贷款组合的风险价值。最后,我们对内部评级法关于资本要求计算中存在的一些问题作了简单讨论。     

Optimal reinsurance with regulatory initial capital and default risk

In a reinsurance contract, a reinsurer promises to pay the part of the loss faced by an insurer in exchange for receiving a reinsurance premium from the insurer. However, the reinsurer may fail to pay the promised amount when the promised amount exceeds the reinsurer’s solvency. As a seller of a reinsurance contract, the initial capital or reserve of a reinsurer should meet some regulatory requirements. We assume that the initial capital or reserve of a reinsurer is regulated by the value-at-risk (VaR) of its promised indemnity. When the promised indemnity exceeds the total of the reinsurer’s initial capital and the reinsurance premium, the reinsurer may fail to pay the promised amount or default may occur. In the presence of the regulatory initial capital and the counterparty default risk, we investigate optimal reinsurance designs from an insurer’s point of view and derive optimal reinsurance strategies that maximize the expected utility of an insurer’s terminal wealth or minimize the VaR of an insurer’s total retained risk. It turns out that optimal reinsurance strategies in the presence of the regulatory initial capital and the counterparty default risk are different both from optimal reinsurance strategies in the absence of the counterparty default risk and from optimal reinsurance strategies in the presence of the counterparty default risk but without the regulatory initial capital.     

Securitizing and tranching longevity exposures

We consider the problem of optimally designing longevity risk transfers under asymmetric information. We focus on holders of longevity exposures that have superior knowledge of the underlying demographic risks, but are willing to take them off their balance sheets because of capital requirements. In equilibrium, they transfer longevity risk to uninformed agents at a cost, where the cost is represented by retention of part of the exposure and/or by a risk premium. We use a signalling model to quantify the effects of asymmetric information and emphasize how they compound with parameter uncertainty. We show how the cost of private information can be minimized by suitably tranching securitized cashflows, or, equivalently, by securitizing the exposure in exchange for an option on mortality rates. We also investigate the benefits of pooling several longevity exposures and the impact on tranching levels.     

Energy futures prices: term structure models with Kalman filter estimation

We present a class of multi-factor stochastic models for energy futures prices, similar to the interest rate futures models recently formulated by Heath. We do not postulate directly the risk-neutral processes followed by futures prices, but define energy futures prices in terms of a spot price, not directly observable, driven by several stochastic factors. Our formulation leads to an expression for futures prices which is well suited to the application of Kalman filtering techniques together with maximum likelihood estimation methods. Based on these techniques, we perform an empirical study of a one- and a two-factor model for futures prices for natural gas.     

碳市场EUA与CER 期货价格变动关系的实证研究

基于VAR模型,对碳市场中的EUA期货价格和CER期货价格的变动关系进行了实证研究．选取欧洲气候交易所（ECX）的EUA期货价格和CER期货价格作为研究对象,运用Johansen协整检验、Granger因果关系检验、向量误差修正模型、广义脉冲响应函数和方差分解方法形成递进式的计量分析框架．研究结果表明：第一,EUA期货价格与CER期货价格之间存在着相互影响关系;第二,CER期货价格对市场信息的反映比EUA期货价格更为敏感,反映速度更快;第三,两种价格之间,CER期货价格变动的影响起主导作用,更好地发挥了期货的定价功能,两市场间存在杠杆效应．     

Modelling Credit Risk in the Jump Threshold Framework

ABSTRACT

The jump threshold framework for credit risk modelling developed by Garreau and Kercheval enjoys the advantages of both structural- and reduced-form models. In their article, the focus is on multidimensional default dependence, under the assumptions that stock prices follow an exponential Lévy process (i.i.d. log returns) and that interest rates and stock volatility are constant. Explicit formulas for default time distributions and basket credit default swap (CDS) prices are obtained when the default threshold is deterministic, but only in terms of expectations when the default threshold is stochastic. In this article, we restrict attention to the one-dimensional, single-name case in order to obtain explicit closed-form solutions for the default time distribution when the default threshold, interest rate and volatility are all stochastic. When the interest rate and volatility processes are affine diffusions and the stochastic default threshold is properly chosen, we provide explicit formulas for the default time distribution, prices of defaultable bonds and CDS premia. The main idea is to make use of the Duffie–Pan–Singleton method of evaluating expectations of exponential integrals of affine diffusions.     

A mean reverting process for pricing treasury bills and futures contracts

An analytically tractable, discrete-time single-factor model is developed for valuing treasury bills and futures contracts. It uses a multiplicative binomial foward process that creates neither negative nor implausibly large positive interest factors, and which can incorporate different possible degrees of mean reversion. The paper derives explicit formulae for bill prices, futures prices, their conditional variances and risk premia in a setting that relates the evolution of the term structure more closely to both model and data than do other similar works. In contrast to other term-structure constrained models, this paper emphasizes that in a one-factor model the martingale probabilities cannot be treated independently of the perturbation functions. The paper's empirical methods also differ from the customary approaches. Instead of comparing differences between model-predicted and observed prices, the paper applies ARCH methodology to test model-predicted ratios of conditional variances to risk premia. Our tests find influences exogenous to the model, but these factors do not seem capable of being explained with two-factor models using only interest rates.     

Multiple structural changes in the tail behavior: Evidence from stock index futures returns

The study provides an approach of nonlinear analysis for detecting multiple structural changes in the tails of financial returns distributions. The proposed approach can simultaneously determine the number of structural breaks in a series of tail-indexes and estimate the mean tail-index levels in distinct regimes. The method is applied to the tail behavior of DJIA futures returns. The sample period covered various recent financial crises, and ran from October 1999 to December 2003, enabling assessment of the relationships between changes in the tail shape of returns distribution and known extreme events in financial markets. The empirical results demonstrate the existence of at least one break point in the left and common tails of the DJIA futures returns distribution during the sample period, and the mean tail-index levels in different regimes classified by estimated break points display an increase in the left and common tails that coincides the phenomenon of gradually decreasing financial turbulence in DJIA futures contracts. The empirical evidence indicates that the structural changes in the tail behavior of the distribution of DJIA futures returns are associated more with negative shocks than positive ones, creating differences in risk management between long and short investors in futures markets.