变结构Copula模型在金融波动溢出效应中应用研究综述

在经济全球化和金融一体化的推动下,金融市场之间的联动性变得更加紧密,金融市场间的波动溢出效应也更加剧烈,传统的金融波动模型无法精确地描述金融市场间错综复杂的波动溢出特征,因此构建刻画金融市场间的波动溢出机制的模型是众多学者研究的焦点。文章通过查阅国内外学者关于金融波动的相关学术论著,总结了变结构Copula模型在金融波动溢出效应中的优势,发现变结构Copula模型问题的解决将为金融市场的发展作出更大的贡献,提出变结构Copula模型在金融波动溢出效应方面未来的可能发展方向。     

猪肉价格波动与通货膨胀相依关系研究

本文将具有资本品特征的农产品称为资产化农产品,以猪肉作为资产化农产品的代表,利用五种Copula函数计算了通货膨胀率序列和猪肉价格指数收益序列的相依系数;通过AIC和BIC法则选择Frank Copula为最优模型,并基于Frank Copula模型计算了通货膨胀率和猪肉价格波动率之间的Kendall’τ和Spearman’ρ相依系数。结果表明通货膨胀率和猪肉价格波动率之间存在正的相依关系,猪肉价格上涨对诱发通货膨胀有很强的推动作用。     

GARCH和Copula模型在股市中的实证比较

长期以来资产收益率的波动性一直都是金融学家关注的问题,资产选择理论用方差来描述收益率的波动性,进而寻找最优资产组合。传统的金融计量方法认为方差是独立于时间变化的变量,但是近年来大量的金融时间序列实证分析发现,方差是随时间变化而变化的,而且金融时间序列的波动具有类聚性。近年来,一些学者把GARCH模型与Copula结合,动态地对金融变量间的相依性和风险加以研究。本文将结合两者的实证分析进行比较。     

中国金融市场韧性研究

本文基于2005年1月至2022年10月的中国金融市场数据,采用的是时变参数因子增广型向量自回归模型（TVP-FAVAR）（以下简称TVP-FAVAR模型）定量测度中国金融市场韧性,利用网络拓扑方法构建各子市场间的韧性关联网络,并进一步分析金融市场韧性影响因素。研究发现,中国金融市场韧性具有明显时变特征;面对外部金融风险冲击,不同子市场在保持和恢复原始状态的能力上存在异质性。对于提升金融市场韧性而言,中国当前的首要任务是不断完善金融基础设施建设、建立多层次的金融体系,同时需要重点维护外汇市场稳定。     

对Copula函数的选择及其在金融分析中的若干应用探讨

Copula理论是基于联合分布的一种建模方法,函数提供了一种灵活使用的方法,目前被广泛引用在金融领域。本文主要对Copula函数进行研究,探讨了copula函数在金融分析中的主要应用。研究表明Copula函数对金融数据的建模和分析有着重要的意义。     

金融市场的风险值测量及动态分析

介绍了基于高斯核估计历史模拟法的金融市场风险值(VAR)测量的算法理论过程,再建立时变系数的单因素资本资产定价模型(CAPM),并用带时变参数系统的Kalman滤波法对该模型下时变系数进行估计.最后对上海证券市场商业版块类做实证分析。     

基于时变Copula的我国股票市场联动性研究

通过运用Copula技术,构建4种Copula-GARCH模型,讨论金融市场的相关模式问题得出的结论是Joe-ClaytonCopula比正态Copula好,动态模型比静态模型要好。表明沪港股市确实存在非对称的相关变化规律。同时表明沪、港股票市场股市相关程度较小,两个市场联动性较弱,上海股市的波动具有相对的独立性,通过组合上海股市和香港股市的方式可以较好的降低投资风险。     

金融市场的风险值测量及动态分析

介绍了基于高斯核估计历史模拟法的金融市场风险值（VAR）测量的算法理论过程，再建立时变系数的单因素资本资产定价模型（CAPM），并用带时变参数系统的Kalman滤波法对该模型下时变系数进行估计．最后对上海证券市场商业版块类做实证分析。     

基于环境要素的商业银行碳金融全面风险度量研究

商业银行以参与碳金融的方式服务低碳经济发展成为当前金融创新的主要领域.作为环境资本的核准减排量的数量和价格波动对碳金融风险具有显著影响,在碳金融风险度量时加入环境要素具有重要意义.文章运用Copula理论对商业银行碳金融业务中的信用风险和市场风险进行整合时,将环境资本的相关变量加入到模型中,建立基于环境要素的碳金融全面风险度量模型.     

股指期货基差与流动性的动态关系研究

本文利用Copula函数,构建时变Copula-GARCH模型,对沪深300指数期现货基差和流动性的动态相关性进行实证研究。结果表明:沪深300指数期现货基差与流动性之间存在非对称的相关变化规律,二者的相关程度较小,联动性较弱。时变SJC-Copula模型计算结果表明上尾相关性显着,而下尾相关性为零。     

基于Copula理论的金融资产传染效应研究

某一突发性金融事件可能使整个金融市场间的联动程度显著增强,并对一定区域乃至世界范围的经济体系产生传染效应。对此,采用Copula函数方法,通过t-GARCH(1,1)模型对资产收益时序进行过滤,运用非参数估计,分析多变量之间相关结构及尾部相关性的变化进而考察变量间的传染效应。通过对美国次贷危机前后多国证券市场的实证分析,结果表明次贷危机后,美国标准普尔指数与代表性的亚洲证券市场间的联动性显著加强,次贷危机对亚洲股市存在传染效应。     

Toward A Convergence Theory For Continuous Stochastic Securities Market Models1

This article reviews some recently developed approximation schemes for financial markets with continuous trading. Two methods for approximating continuous-time stochastic securities market models whose exogenously given prices have continuous sample paths are described and compared One method approximates both the paths and the information structure; the other is an approximation in distribution with a Markovian structure. In both cases, the approximating models have a finite state space, discrete time, and possess the same “structural” properties (e.g., “no arbitrage” and “completeness”) as the continuous model. the latter characteristic is an important criterion for judging the merits of the approximations. Taking advantage of the “structure-preserving” characteristic, one can formulate a convergence theory for frictionless markets with continuous trading. the theory provides convergence results for objects such as contingent claim prices, replicating portfolio strategies (hedging policies), optimal consumption policies, and cumulative financial gains (i.e., stochastic integrals), which are constructed along the approximation. the convergence theory enables one to combine the intuitive appeal of discrete models and the analytic tractability of continuous models to provide new insight into the theory of modern financial markets. We survey the current state of such a convergence theory and illustrate the results with some examples of well-known continuous securities market models.     

A model for unpacking big data analytics in high-frequency trading

This study develops a conceptual model of the 7 V′s of big data analytics to gain a deeper understanding of the strategies and practices of high-frequency trading (HFT) in financial markets. HFT is computerized trading using proprietary algorithms. Empirical data collected from HFT firms and regulators in the US and UK reveals competitive asymmetries between HFTs and low-frequency traders (LFTs) operating more traditional forms of market trading. These findings show that HFT gains extensive market advantages over LFT due to significant investment in advanced technological architecture. Regulators are challenged to keep pace with HFT as different priorities to the 7 V′s are given in pursuit of a short term market strategy. This research has implications for regulators, financial practitioners and investors as the technological arms race is fundamentally changing the nature of global financial markets.     

Price relations among hog,corn, and soybean meal futures

This paper examines the relations among hog, corn, and soybean meal futures price series using the Perron (1997) unit root test and autoregressive multivariate cointegration models. Accounting for the significant seasonal factors and time trends, we find the three series are cointegrated with one single cointegrating vector, whose coefficients are comparable to the ratios used by the United States Department of Agriculture (USDA). Ex‐post trading simulations that utilize the cointegration results generate significant profits, suggesting that market expectations may not fully incorporate the mean‐reverting tendencies as indicated by the cointegration relations, and that inefficiency exists in these three commodity futures markets. Results from our ex‐ante trading simulations that employ the USDA ratios also provide some evidence in this regard. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:491–514, 2005     

Research on a stock-matching trading strategy based on bi-objective optimization

In recent years, with strict domestic financial supervision and other policy-oriented factors, some products are becoming increasingly restricted, including nonstandard products, bank-guaranteed wealth management products, and other products that can provide investors with a more stable income. Pairs trading, a type of stable strategy that has proved efficient in many financial markets worldwide, has become the focus of investors. Based on the traditional Gatev–Goetzmann–Rouwenhorst (GGR, Gatev et al., 2006) strategy, this paper proposes a stock-matching strategy based on bi-objective quadratic programming with quadratic constraints (BQQ) model. Under the condition of ensuring a long-term equilibrium between pairedstock prices, the volatility of stock spreads is increased as much as possible, improving the profitability of the strategy. To verify the effectiveness of the strategy, we use the natural logs of the daily stock market indices in Shanghai. The GGR model and the BQQ model proposed in this paper are back-tested and compared. The results show that the BQQ model can achieve a higher rate of returns.     

Do trend following strategies work in Chinese futures markets?

We examine the performance of trend following strategies in Chinese commodity futures markets. We provide evidence that trend following‐based technical trading rules yield better performance than the buy and hold strategy on both individual contracts and sorted portfolios. The outperformance is robust to transaction costs, data frequency, sub‐prime crisis, shorting constraint, delayed execution, liquidity and parameters. Finally, the profitability of the trend following strategy may be subject to data snooping bias.     

Half-day trading and spillovers

This paper investigates the linkage of returns and volatilities between the United States and Chinese stock markets from January 2010 to March 2020. We use the dynamic conditional correlation (DCC) and asymmetric Baba–Engle–Kraft–Kroner (BEKK) GARCH models to calculate the time-varying correlations of these two markets and examine the return and volatility spillover effects between these two markets. The empirical results show that there are only unidirectional return spillovers from the U.S. stock market to the Chinese stock market. The U.S. stock market has a consistently positive spillover to China’s next day’s morning trading, but its impact on China’s next day’s afternoon trading appears to be insignificant. This finding implies that information in the U.S. stock market impacts the performance of the Chinese stock market differently in distinct semi-day trading. Moreover, with respect to the volatility, there are significant bidirectional spillover effects between these two markets.     

OPTIMAL TRADE EXECUTION AND PRICE MANIPULATION IN ORDER BOOKS WITH TIME‐VARYING LIQUIDITY

In financial markets, liquidity is not constant over time but exhibits strong seasonal patterns. In this paper, we consider a limit order book model that allows for time‐dependent, deterministic depth and resilience of the book and determine optimal portfolio liquidation strategies. In a first model variant, we propose a trading‐dependent spread that increases when market orders are matched against the order book. In this model, no price manipulation occurs and the optimal strategy is of the wait region/buy region type often encountered in singular control problems. In a second model, we assume that there is no spread in the order book. Under this assumption, we find that price manipulation can occur, depending on the model parameters. Even in the absence of classical price manipulation, there may be transaction triggered price manipulation. In specific cases, we can state the optimal strategy in closed form.     

Religion, Ethics and Stock Trading: The Case of an Islamic Equities Market

Islamic banking, based on the prohibition of interest, is well established throughout the Muslim world. Attention has now turned towards applying Islamic principles in equity markets. The search for alternatives to Western style markets has been given added impetus in Muslim countries by the turmoil in Asian financial markets in 1997. Common stocks are a legitimate form of instrument in Islam, but many of the practices associated with stock trading are not. In this paper the instruments traded and the structure and practices of stock markets are examined from an Islamic perspective. Speculation is not acceptable in Islam and measures would have to be taken to control speculative trading. In addition short selling and margin trading are severely restricted. The use of stock index and equity futures and options are also unlikely to be acceptable within an Islamic market. Regulatory authorities in Muslim countries will therefore find a vast array of problems in attempting to structure a trading system that will be acceptable.