Leverage effect on stochastic volatility for option pricing in Hong Kong: A simulation and empirical study

This paper explores the importance of incorporating the financial leverage effect in the stochastic volatility models when pricing options. For the illustrative purpose, we first conduct the simulation experiment by using the Markov Chain Monte Carlo (MCMC) sampling method. We then make an empirical analysis by applying the volatility models to the real return data of the Hang Seng index during the period from January 1, 2013 to December 31, 2017. Our results highlight the accuracy of the stochastic volatility models with leverage in option pricing when leverage is high. In addition, the leverage effect becomes more significant as the maturity of options increases. Moreover, leverage affects the pricing of in-the-money options more than that of at-the-money and out-of-money options. Our study is therefore useful for both asset pricing and portfolio investment in the Hong Kong market where volatility is an inherent nature of the economy.     

Exchange rate volatility and its impact on the transaction costs of covered interest rate parity

This paper provides empirical evidence on the linkage between foreign exchange market volatility and daily 90-day covered interest rate parity (CIP) conditions of the three major exchange rates against the US dollar (US$). Markov regime shifting models were utilized to generate time series of volatility regime probabilities and these were used to explain the first and second moments of the daily deviations from and the transaction cost bands around the covered parity conditions. We find a significant positive relationship between the deviations and the regime probabilities, indicating an increasing probability of higher volatility state being associated with rising deviations (both first and second moments) from the parity condition. Similar positive relationship is found for the transaction bands. Rising (falling) probabilities of high (low) volatility regimes increased the first and second moments of the bands. Furthermore, we find a higher volatility state combined with a US$ depreciation is associated with significantly higher volatility in the daily deviations than an appreciation. Also, US$ depreciation is associated with widening transaction bands. This suggests that the level of market uncertainty was higher when the US$ was depreciating.     

CREDIBILITY, MACROECONOMIC FUNDAMENTALS AND MARKOV REGIME SWITCHES IN THE EMS

The main objective of this paper is to use the Markov regime‐switching modelling framework to describe and analyse the credibility of a number of countries participating in the European Monetary System during 1980–1998. Our credibility indicator, based on Hughes Hallet et al.'s (1997) methodology, is subject to discrete regime shifts and is made dependent on macroeconomic fundamentals. We carry out extensive testing to assess the specification of the Markov regime‐switching model and the potential existence of permanent breaks. A contribution of our paper is the specification of a multivariate Markov switching model that allows us to examine whether macroeconomic variables have asymmetric effects on credibility. Another contribution is the specification of a regime‐switching model with time‐varying transition probabilities, which enables us to determine whether changes in macroeconomic variables can trigger switches between the low and high credibility regimes. We find strong evidence of regime switching behaviour in all countries. Both the level of credibility and the transition probabilities display an asymmetric response to changes in macroeconomic variables, with the stance of fiscal policy exerting the most systematic influence in all countries.     

UNEMPLOYMENT, HYSTERESIS AND TRANSITION

In this paper, we quantify the degree of persistence in the unemployment rates of transition countries using a variety of methods benchmarked against the EU. Initially, we work with the concept of linear ‘Hysteresis’ as described by the presence of unit roots in unemployment as in most empirical research on this area. Given that this is potentially a narrow definition, we also take into account the existence of structural breaks and nonlinear dynamics in unemployment. Finally, we examine whether CEECs' unemployment presents features of multiple equilibria, that is, if it remains locked into a new level whenever some structural change or sufficiently large shock occurs. Our findings show that, in general, we can reject the unit‐root hypothesis after controlling for structural changes and business‐cycle effects, but we can observe the presence of a high and low unemployment equilibria. The speed of adjustment is faster for CEECs than the EU, although CEECs tend to move more frequently between equilibria.     

Statistics for Studies of Human Welfare

Developments in the recent past have substantially increased our ability to measure, compute, and communicate. We take the view that a corresponding improved understanding of processes in the life sciences will come about only through more intensive studies of properties of statistical methods and algorithms and transparent, open source computing environments.     

QUADRATIC TERM STRUCTURE MODELS FOR RISK-FREE AND DEFAULTABLE RATES

In this paper, quadratic term structure models (QTSMs) are analyzed and characterized in a general Markovian setting. The primary motivation for this work is to find a useful extension of the traditional QTSM, which is based on an Ornstein–Uhlenbeck (OU) state process, while maintaining the analytical tractability of the model. To accomplish this, the class of quadratic processes, consisting of those Markov state processes that yield QTSM, is introduced. The main result states that OU processes are the only conservative quadratic processes. In general, however, a quadratic potential can be added to allow QTSMs to model default risk. It is further shown that the exponent functions that are inherent in the definition of the quadratic property can be determined by a system of Riccati equations with a unique admissible parameter set. The implications of these results for modeling the term structure of risk-free and defaultable rates are discussed.     

纽约股票市场对中国A股市场的影响

首先，本文考察了纽约股市波动对中国A股市场的影响。一般认为，中国的A股市场由于严格的资本控制而免受外国影响。但是，通过月度、每周、每日的样本数据（1992年到2004年），经过季节性调整和汇率变动调整后，我们发现上海和深圳A股市场的变动与美国股票价格指数变动相一致。其次，我们考察国家贝塔值（country beta）在马尔可夫转换误差修正模型中的动态关系。对中国市场来说，国家贝塔值和错误纠正项的重要性紧密相连。在东亚金融危机之前，美国市场对中国A股市场的影响普遍存在，而东亚金融危机产生后，则是通过国家贝塔值来影响中国股市的收益。     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

EMBEDDED MATRICES FOR FINITE MARKOV CHAINS

For an arbitrary subset A of the finite state space 5 of a Markov chain the so–called embedded matrix P _A is introduced. By use of these matrices formulas expressing all kinds of probabilities can be written down almost automatically, and calculated very easily on a computer. Also derivations can be given very systematically.     

基于Markov链的物流园区需求灰色预测模型改进

物流因区是一项大型基础设施投资项目，在规划与设计上需要有一定的超前意识，而需求预测则是园区规划超前意识的重要依据。目前。国内外对物流园区需求预测方法的研究和实践基本上还处于发展阶段．至今尚未形成完整科学、操作性强的方法体系，现有的需求预测大体上是借鉴史通运输规划的模型．进行研究的过程中灰色模型预测有局限性。其预测结果与真实值之间存在一定误差，因而可以考虑利用Markov链提出改进方案。