基于CVaR收益率约束的贷款组合优化决策模型实例研究

本文以银行贷款收益率为收益,以其波动率为标准反映贷款风险,目标是贷款组合CVaR最小,运用了贷款组合优化模型做实例分析研究。该模型用组合CVaR的收益率控制贷款的收益率风险,并且以VaR风险控制作为约束条件,这样银行风险便被设定在一定的承受范围内。     

基于CVaR收益率约束的贷款组合优化决策模型实例研究

本文以银行贷款收益率为收益,以其波动率为标准反映贷款风险,目标是贷款组合CVaR最小,运用了贷款组合优化模型做实例分析研究.该模型用组合CVaR的收益率控制贷款的收益率风险,并且以VaR风险控制作为约束条件,这样银行风险便被设定在一定的承受范围内.     

基于单指数模型的最优风险资产组合选择及分析

单指数模型在构造基于马科维茨资产组合选择模型所需的协方差矩阵时,有估计量少、计算简便等独特优势。因此,选择单指数模型,利用上证A股指数及上证A股股票进行最优风险资产组合的构造,并进行回归分析。回归结果显示,作为市场收益率测度的上证A股指数,其超额收益分布并不具有正态性,单指数模型并不适用于上证A股市场,其构造的投资组合会乐观估计组合的总体方差,从而低估风险。     

联保融资的有效边界：威海钢贸企业集体违约案例

联保融资模式因为具有分散单个企业信用风险、借助其他企业信用资源绕开抵押物缺乏障碍、实现有效融资的特点,近几年被融资主体广泛采用。但该模式存在的最大缺点是其有效性受经济环境影响较大,即联保融资模式的有效性存在以行业下行信号为标志的边界。本文通过对威海某钢贸城内经营商户采用联保模式融资、因行业景气程度下降引发集体违约的案例进行描述,揭示联保融资模式信用风险分散功能在突破有效边界时从有效变为无效的根本原因,提出引入第三方担保、确保担保机构业务多元化可以在一定程度上防范联保融资模式的系统性风险。     

CVaR限制下的动态最优投资组合策略

本文在经典的Matkowitz投资组合策略选择的框架下,用CVaR代替了方差作为风险测度,在Black-Scholes模型下,用几何布朗运动来刻画股票价格过程,得出均值-CVaR模型下的动态最优策略和有效前沿边界.     

基于VaR/CVaR的股票型QDⅡ基金评价

以成立时间在2012年前的21只股票型QDⅡ基金为样本,进行样本基金的评价。首先,采用传统的詹森指数考察基金业绩,然后采用VaR和CVaR对基金进行风险评价。通过计算样本基金的VaR和CVaR,得出基金收益率序列的尖峰厚尾特征对VaR和CVaR有相当大的影响的结论。     

最优消费和资产组合选择理论的研究综述

最优消费与资产组合选择理论是金融学中资产组合选择理论的扩展和延伸.本文将最优消费和资产组合选择理论文献按照完全市场和非完全市场的假设前提分为两大类进行回顾和总结,并重点介绍了国外学者研究劳动收入风险以及流动性约束对资产组合选择影响的最新成果,这对研究我国居民资产组合选择具有很大的启发.     

基于效用函数下的投资组合研究

投资组合是分散投资风险的有效途径。由于投资者既追求高收益,又想尽可能地回避风险,所以关于证券投资组合的最大收益、最小风险投资决策问题,提出了一个兼顾收益和风险的效用函数。对投资组合的选择,实际上是以效用最大化作为选择准则。由于大多数投资者都是风险厌恶者,厌恶风险的投资者其效用函数遵循边际效用递减规律,因此本文选用指数型效用函数曲线。文章首先讨论了Markowitz模型投资组合的有效边界,再利用投资者的效用函数,由根的唯一性定理,首先求出投资者的效用,进而求出最优组合下的期望收益率和方差,最后得到最优投资组合的比例。     

最优消费和资产组合选择理论的研究综述

最优消费与资产组合选择理论是金融学中资产组合选择理论的扩展和延伸。本文将最优消费和资产组合选择理论文献按照完全市场和非完全市场的假设前提分为两大类进行回顾和总结,并重点介绍了国外学者研究劳动收入风险以及流动性约束对资产组合选择影响的最新成果,这对研究我国居民资产组合选择具有很大的启发。     

基于copula的投资组合选择模型的研究

本文首先介绍了投资组合理论与copula,然后给出基于概率的收益率等定义,建立基于概率的收益率的投资组合选择模型并给出具体解法,接着通过选取上证领先指数与深证领先指数2004年9月1日至2006年5月26日的日收盘数据进行实证分析,发现在收益率(基于概率的收益率)一定的情况下,通过投资组合可以降低风险。pápápá     

基于copula的投资组合选择模型的研究

本文首先介绍了投资组合理论与copula,然后给出基于概率P0的收益率等定义,建立基于概率P0的收益率的投资组合选择模型并给出具体解法,接着通过选取上证领先指数与深证领先指数2004年9月1日至2006年5月26日的日收盘数据进行实证分析,发现在收益率(基于概率的收益率)一定的情况下,通过投资组合可以降低风险.     

基于Copula的投资组合选择模型研究

基于概率收益率与概率风险的定义,建立基于风险与收益率的投资组合模型,为了更好拟合联合分布,在具体解法中采用Copula函数来构造多个资产收益率的联合分布。由于不要求收益率服从维纳过程,因此基于Copula的Markowitz投资组合选择模型具有更广的适用性。通过对上证领先指数与深证领先指数收盘数据实证分析发现,在收益率(基于概率ρ0的收益率)一定的情况下,通过投资组合可以降低风险。     

Correlation Risk and Optimal Portfolio Choice

We develop a new framework for multivariate intertemporal portfolio choice that allows us to derive optimal portfolio implications for economies in which the degree of correlation across industries, countries, or asset classes is stochastic. Optimal portfolios include distinct hedging components against both stochastic volatility and correlation risk. We find that the hedging demand is typically larger than in univariate models, and it includes an economically significant covariance hedging component, which tends to increase with the persistence of variance–covariance shocks, the strength of leverage effects, the dimension of the investment opportunity set, and the presence of portfolio constraints.     

Loan Portfolio Swaps and Optimal Lending

Theories on loan portfolio swap hedging are based on a portfolio-choice approach. This paper presents an alternative: a firm-theoretic model for bank behavior with loan portfolio swaps. Our paper derives the optimal loan rate and rate-taking loan amount of the banks portfolio, and relates them to the market loan rate, counterparty loan rate, swap default risk, capital-to-deposits ratio, and deposit insurance. We find that in the bilateral default risk approach, the comparative static results are generated by four factors: the banks risk magnitude about the equity market value, loan composition in the swap contract, the substitution effect in the loan portfolio, and the income effect from the swap transaction. The results imply that changes in the payoff asymmetry in the event of swap default and the banks regulatory parameters have a direct effect on the banks loan portfolio for lending and swap transactions.We would like to thank two anonymous referees for helpful comments and advice.     

基于GARCH族模型对H股指数期货的VaR与CVaR值的实证研究

本文以港交所H股指数期货的收盘价格数据作为实证载体,基于GARCH族模型中残差的正态分布、T分布和广义误差分布（GED）三种不同情形,分别采用GARCH、EGARCH及PARCH模型,计算H股指数期货收益波动序列的VaR和CVaR值,结果表明基于广义误差分布的PARCH模型（GED-PARCH）无论在计算VaR值还是CVaR值方面都是最优的。     

Model Predictive Control for Optimal Pairs Trading Portfolio with Gross Exposure and Transaction Cost Constraints

Model predictive control (MPC) is a flexible yet tractable technique in control engineering that recently has gained much attention in the area of finance, particularly for its application to portfolio optimization. In this paper, we extend the MPC with linear feedback setting in Yamada and Primbs (in: Proceedings of the IEEE conference on decision and control, pp 5705–5710, 2012) by incorporating the following two important and practical issues: The first issue is gross exposure (GE), which is the total value of long and short positions invested in risky assets (or stocks) as a proportion of the wealth possessed by a hedge fund. This quantity measures the leverage of a hedge fund, and the fund manager may limit the amount of leverage by imposing an upper bound, i.e., a GE constraint. The second issue is related to transaction costs, where the MPC algorithm may require frequent trades of many stocks leading to large transaction costs in practice. Here we assume that the transaction cost is proportional to the change in the amount of money (i.e., the change of absolute values of long or short positions) invested in each stock. We formulate the MPC strategy based on a conditional mean-variance problem which we show reduces to a convex quadratic problem, even with gross exposure and proportional transaction cost constraints. Based on numerical experiments using Japanese stock data, we demonstrate that the incorporation of the transaction cost constraint improves the empirical performance of the wealth in terms of Sharpe ratio, which may be improved further by adding the GE constraint.