我国不良资产处置实证分析

银行不良资产问题的解决不仅直接关系到银行的发展,而且关系到国有企业的改革乃至金融体系的稳定和整个社会经济的健康成长.在我国金融市场蓬勃发展的前提下,研究适合我国金融环境中应用的不良资产处置方法对我国的不良资产处置工作具有积极的指导意义.     

A machine learning efficient frontier

We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the mean–variance efficient frontier out-of-sample. Our results, therefore, shed important light on the appeal of machine learning into portfolio selection under estimation risk.     

Robust reward–risk ratio optimization with application in allocation of generation asset

In this article, we study reward–risk ratio models under partially known message of random variables, which is called robust (worst-case) performance ratio problem. Based on the positive homogenous and concave/convex measures of reward and risk, respectively, the new robust ratio model is reduced equivalently to convex optimization problems with a min–max optimization framework. Under some specially partial distribution situation, the convex optimization problem is converted into simple framework involving the expectation reward measure and conditional value-at-risk measure. Compared with the existing reward–risk portfolio research, the proposed ratio model has two characteristics. First, the addressed problem combines with two different aspects. One is to consider an incomplete information case in real-life uncertainty. The other is to focus on the performance ratio optimization problem, which can realize the best balance between the reward and risk. Second, the complicated optimization model is transferred into a simple convex optimization problem by the optimal dual theorem. This indeed improves the usability of models. The generation asset allocation in power systems is presented to validate the new models.     

基于商业银行面板数据的信贷资产证券化动因实证

在党的十九大提出建设现代化经济体系、国务院发文“盘活存量”等国家政策的背景下,回顾了国内外资产证券化动因研究,并结合我国国情给出了增加流动性、改善盈利性、风险管理需要和监管资本套利等动因理论假说.采用国内符合业界标准的56家银行2011—2017年的相关数据,以56家全样本银行和13家上市银行为研究对象进行实证分析,结果表明,我国银行开展信贷资产证券化主要出于改善盈利性而非增加流动性,更倾向于扩大资产规模、挖掘创新业务和优化管理效率等动因.     

Complex dynamics in equilibrium asset pricing models with boundedly rational,heterogeneous agents

We study a simple model based upon the Lucas framework where heterogeneous agents behave rationally in a fully intertemporal setting but do not know other investors' personal preferences, wealth or investment portfolios. As a consequence, agents initially do not know the equilibrium asset pricing function and must make guesses, which they update via adaptive learning with constant gain. We demonstrate that even in this simple environment the economy can, depending on parameters, exhibit either stable convergence to equilibrium, or chaotic dynamical behavior of asset prices and trading volume without converging to the rational expectations equilibrium of the Lucas model. This contradicts the assertion that the Lucas model is stable in the face of modest deviations from the strong assumptions required to compute the equilibrium. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–55, 2014     

社会保障的改善对我国居民家庭消费——投资选择的影响研究

与发达国家相比,我国居民家庭的资产配置中存在着消费比例过低、金融资产配置结构不合理等问题.而导致这一问题的重要因素是我国目前的社会保障仍处于较低水平.以跨期消费—投资组合理论为基础,研究社会保障制度的改善对居民家庭资产配置的影响机理及影响效果.结果表明,社会保障制度一方面通过降低居民家庭的风险厌恶水平,可以显著提高其消费比例及风险资产投资比例;另一方面通过提高退休后的收入水平,可以提高居民家庭的整体效用水平.同时,社会保障制度的改善,也有利于提高居民家庭对金融市场的参与热情,有利于活跃我国金融市场.     

Black-Litterman投资组合模型的进一步推导分析

在理论上通过推导首次得出了Black-Litterman模型(B-L模型)最优权重与信心水平的公式.在各资产收益不相关及单一绝对观点的假设下,得出各资产的B-L模型最优权重与信心水平的简化表达式.借助于此,还对信心水平与最优权重公式的进一步理论分析,并以光大证券的"乌龙指"做实证,详细分析投资者在没有市场观点、拥有内幕信息、以及信心水平在某范围变化时,其所持各投资品权重的特点.     

关于无风险资产不存在时资产组合选择的研究

以往关于资产组合选择的研究大多假设市场上存在无风险资产,但无风险资产实际上是不存在的.当不存在无风险资产时,假设投资者的效用定义在消费上,消费一直是投资者财富的一个固定比例,投资者的最优资产组合由两部分组成:短视的资产组合和对冲组合.假设只有股票和债券两种风险资产,当股票和债券的风险具有负的相关性时,投资者现在会消费更多,同时也会在股票上投资更多;两者正相关时,投资者无法降低风险,会减持股票并降低当前消费;两者不相关时,投资者持有的股票权重和存在无风险资产时一样.最后,还推导出了多种资产情况下最优消费和资产组合的解析表达式.     

基于粗集理论的组合预测法在无形资产评估中的应用

针对如何评估企业无形资产的问题,运用基于粗集理论的组合预测方法,建立了企业无形资产评估的数量模型。该模型的特点是将组合预测方法中权系数的确定问题转化为粗集理论中的属性重要性评价问题,这样就在很大程度上克服了传统组合预测方法中权系数确定主观性太大的缺陷,而使得权系数的确定更具客观性。最后,结合实例阐述了基于粗集理论的组合预测方法在企业无形资产评估中的应用,进一步说明了该方法的可行性和有效性。     

动态资产份额定价理论模型

运用倒向随机微分方程数学方法 ,建立了动态资产份额定价理论模型 .这一模型是资产份额定价法的改进 .求解模型得到动态资产份额定价理论公式 ,并得出结论 :资产份额定价公式完全可以作为特例 ,以离散时间意义和在不考虑动态投资的情况下 ,由动态资产份额定价理论公式得到 .