模型FI-EGARCH-M的建立及实证分析

近年来,金融市场在经济发展中占据了越来越重要的位置,金融数据波动规律成为各国学者竞相研究的热门课题.根据我国近几年来股票市场的波动特点,为其寻找更为合适的模型来拟合股票价格波动规律,即对股票价格波动做进一步分析.提出具有有效市场和分形市场二者优点的FI-EGARCH-M模型,并用所建立的模型对上证指数进行了实证分析.     

Doves and hawks in economics revisited: An evolutionary quantum game theory based analysis of financial crises

The last financial and economic crisis demonstrated the dysfunctional long-term effects of aggressive behaviour in financial markets. Yet, evolutionary game theory predicts that under the condition of strategic dependence a certain degree of aggressive behaviour remains within a given population of agents. However, as a consequence of the financial crisis, it would be desirable to change the “rules of the game” in a way that prevents the occurrence of any aggressive behaviour and thereby also the danger of market crashes. The paper picks up this aspect. Through the extension of the well-known hawk-dove game by a quantum approach, we can show that dependent on entanglement, evolutionary stable strategies also can emerge, which are not predicted by the classical evolutionary game theory and where the total economic population uses a non-aggressive quantum strategy.     

Smoothly truncated stable distributions,GARCH-models,and option pricing

Although asset return distributions are known to be conditionally leptokurtic, this fact has rarely been addressed in the recent GARCH model literature. For this reason, we introduce the class of smoothly truncated stable distributions (STS distributions) and derive a generalized GARCH option pricing framework based on non-Gaussian innovations. Our empirical results show that (1) the model’s performance in the objective as well as the risk-neutral world is substantially improved by allowing for non-Gaussian innovations and (2) the model’s best option pricing performance is achieved with a new estimation approach where all model parameters are obtained from time-series information whereas the market price of risk and the spot variance are inverted from market prices of options. The paper subsumes a previous one under the title “A New Class of Probability Distributions and Its Application to Finance”. The authors gratefully acknowledge comments made by seminar participants at University of California, Santa Barbara, University of Washington, Seattle, Hochschule für Banken, Frankfurt, Cornell University, Princeton University, American University, Washington DC, and the Risk Management and Financial Engineering Conference held in Gainesville, FL in April 2005. All views and opinions expressed in this article are strictly those of the author and do not necessarily represent the views of Sal. Oppenheim.     

A Note on Randomly Weighted Sums of Dependent Subexponential Random Variables

The author obtains that the asymptotic relations■hold as x→∞,where the random weightsθ_1,···,θ_(n )are bounded away both from 0 and from∞with no dependency assumptions,independent of the primary random variables X_1,···,X_(n )which have a certain kind of dependence structure and follow non-identically subexponential distributions.In particular,the asymptotic relations remain true whenX_1,···,X_(n )jointly follow a pairwise Sarmanov distribution.     

基于W-SVM的民营环保企业信用风险预警模型

2019年中国绿色债券发行量依旧稳居世界前列,成为民营环保企业重要融资渠道,但是2018年至今,大量环保企业信用风险事件频发为我们敲响了警钟,构建合适的民营环保企业信用风险预警机制迫在眉睫.环保产业属于新兴产业,并以国有企业为主导,民营企业的样本数据具有样本量小,维度高等特征,这导致传统的信用风险模型适用性不强.因此选用加权支持向量机模型,对不同类别样本采取不同权值,选取大量财务特征,最终构建出风险预警模型．研究发现加权支持向量机模型具有十分优秀的预警性能.环保企业本身具有资金回收周期较长并且项目前期投入较高等特点,建议加强财务管理,保障资产流动性,建立完善产业链.     

Birnbaum‐Saunders autoregressive conditional range model applied to stock index data

This article proposes a new approach to the conditional autoregressive range (CARR) model using the Birnbaum‐Saunders (BS) distribution. The model aims to develop volatility clustering, which incorporates extreme fluctuations, using a time‐varying evolution of the range process called the BSCARR model. Furthermore, diagnosis analysis tools for diagnosis analysis were developed to evaluate the goodness of fit, such as residual analysis, global influence measures based on Cook's distance, and local influence analysis. For illustrative purposes, three real financial market indices are analyzed. A comparison with classical CARR models was also carried out in these examples. The results indicated that the proposed model outperformed some existing models in the literature, especially a recent CARR model based on the gamma distribution even under the presence of atypical cases (observed values).     

Incomplete financial markets model with nominal assets: Variational approach

We deal with the analysis of the general equilibrium model with incomplete financial markets and nominal assets. We assume that there are 2 periods of time, say today and tomorrow. We define a consumption, portfolio holding, commodity and asset price vector as an equilibrium vector associated with a given economy if at those prices and economies households maximize utility under a budget constraints and markets clear. While the path breaking proofs of existence by Cass [6] and Werner [25] use a fixed point argument, we provide an independent existence proof in terms of variational inequalities (about the variational approach for the analysis of general equilibrium models see for example [9] and [10]). The analysis presented in this paper indicates that the variational inequality approach promises to be applicable in many specifications of the incomplete market model.     

基于混沌理论的金融系统稳定性研究

运用混沌理论,研究了金融系统稳定性问题.首先,通过理论分析得出金融系统的稳定性主要受金融创新、金融监管以及投资者的非理性行为三方面的因素共同影响;其次,借助混沌动力学中的Lo-gistic模型,从模型分析与数值模拟两个方面,对金融创新与金融监管这两个主要因素如何影响金融系统稳定性展开了深入的研究.最后,提出了当前在进行金融创新的同时,须加强金融创新与金融监管的协调发展,以保障金融系统稳定、有序运行,进而为经济社会的发展营造一个良好的金融环境.     

A knowledge based approach to loss severity assessment in financial institutions using Bayesian networks and loss determinants

Modelling loss severity from rare operational risk events with potentially catastrophic consequences has proved a difficult task for practitioners in the finance industry. Efforts to develop loss severity models that comply with the BASEL II Capital Accord have resulted in two principal model directions where one is based on scenario generated data and the other on scaling of pooled external data. However, lack of relevant historical data and difficulties in constructing relevant scenarios frequently raise questions regarding the credibility of the resulting loss predictions. In this paper we suggest a knowledge based approach for establishing severity distributions based on loss determinants and their causal influence. Loss determinants are key elements affecting the actual size of potential losses, e.g. market volatility, exposure and equity capital. The loss severity distribution is conditional on the state of the identified loss determinants, thus linking loss severity to underlying causal drivers. We suggest Bayesian Networks as a powerful framework for quantitative analysis of the causal mechanisms determining loss severity. Leaning on available data and expert knowledge, the approach presented in this paper provides improved credibility of the loss predictions without being dependent on extensive data volumes.     

基于随机矩阵理论的股市网络拓扑性质研究

本文运用随机矩阵理论(RMT)和相关系数动态演化模型建立全球股指二次“去噪”相关系数矩阵,并采用阀值法构建全球股市网络,进而分析该网络拓扑结构特性和解释风险在网络中的传染效应。研究发现,全球股市网络呈现出“小世界”效应;在θ=0.1数量水平下,全球股市网络具有较强的鲁棒性。同时,英国和荷兰的股票市场风险传染对网络整体的冲击较大;股市网络中各个股市间的风险传染路径与相关国家经济实力相关联,体现出较强的同配性。