A Stochastic Simulation Approach to Model Selection for Stochastic Volatility Models

Stochastic volatility models have been widely appreciated in empirical finance such as option pricing, risk management, etc. Recent advances of Markov chain Monte Carlo (MCMC) techniques made it possible to fit all kinds of stochastic volatility models of increasing complexity within Bayesian framework. In this article, we propose a new Bayesian model selection procedure based on Bayes factor and a classical thermodynamic integration technique named path sampling to select an appropriate stochastic volatility model. The performance of the developed procedure is illustrated with an application to the daily pound/dollar exchange rates data set.     

Estimation of Jump Tails

We propose a new and flexible nonparametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple‐to‐implement set of estimating equations associated with the compensator for the jump measure, or its intensity, that only utilizes the weak assumption of regular variation in the jump tails, along with in‐fill asymptotic arguments for directly estimating the “large” jumps. The procedure assumes that the large‐sized jumps are identically distributed, but otherwise allows for very general dynamic dependencies in jump occurrences, and, importantly, does not restrict the behavior of the “small” jumps or the continuous part of the process and the temporal variation in the stochastic volatility. On implementing the new estimation procedure with actual high‐frequency data for the S&P 500 aggregate market portfolio, we find strong evidence for richer and more complex dynamic dependencies in the jump tails than hitherto entertained in the literature.     

动态认知视阈下的英语使动构式义

关于构式义,"动词多义论"强行地给词汇增添了许多意义,不能揭示语言生成的认知规律;构式多义观"则是人为地区分出核心义及其延伸义,主观认定这些意义之间的家族相似性.而从"动态认知"的视角考察使动构式的意义可以得出更为合理的结果:一方面,使动构式中的动词都有其基义,它在各语境中兑现为具体的反映义.另一方面,使动构式通过由动词和介词结构组合而成的复合谓语,由认知的运作导致使动义的产生.使动构式义的动态认知观对其他论元构式的语义分析和阐释有很好的借鉴意义.     

Tests for structural breaks in memory parameters of long-memory heterogeneous autoregressive models

Tests for structural breaks in the coefficients of the long-memory heterogeneous autoregressive (HAR) models are developed. The tests are based on the partial sum process of the normalized efficient score vector. The tests have the nice property of identifying the parameters of the daily, weekly, and monthly regressors in which breaks occur. Limiting null distributions of the proposed tests are proven to be derived from standard Brownian bridges. A finite sample Monte-Carlo experiment shows reasonable size and power properties of the proposed tests. The proposed method is illustrated by a real data analysis.     

股票市场价值函数实证研究

价值函数是前景理论的核心组成部分,用以刻画决策者对于收益和损失的主观感受.以前对前景理论的实证研究基本上通过心理学实验来进行,而且是针对决策者个体进行的.本文以股票市场整体为对象,采用EGARCH模型提取到达市场上的信息流作为财富改变的代理变量,利用两阶段幂函数型作为价值函数的表现形式,对十个国家股票市场上综合指数的日收益率数据进行了实证研究.实证结果发现各国股票市场上价值函数均呈现反S形状的,与多数心理实验中个体决策者表现价值函数呈S形状迥然有别.     

Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure

ABSTRACT

We introduce a class of large Bayesian vector autoregressions (BVARs) that allows for non-Gaussian, heteroscedastic, and serially dependent innovations. To make estimation computationally tractable, we exploit a certain Kronecker structure of the likelihood implied by this class of models. We propose a unified approach for estimating these models using Markov chain Monte Carlo (MCMC) methods. In an application that involves 20 macroeconomic variables, we find that these BVARs with more flexible covariance structures outperform the standard variant with independent, homoscedastic Gaussian innovations in both in-sample model-fit and out-of-sample forecast performance.     

House price volatility in China: Demand versus supply

This paper studies the transmission mechanisms that underlie China's house price fluctuations using a dynamic stochastic general equilibrium (DSGE) model. The model is estimated with Bayesian methods, which accounts well for business cycle properties of the housing market. Results show that shocks to housing productivity and the government land supply to housing developers are the primary contributors to house price volatility, accounting for 37% of house price volatility in the short run and 32% in the long run. The importance of housing valuation shocks and shocks to migration only increases in models without the supply side of the housing market.     

认股权证定价实证研究

认股权证在性质上也是一种期权,但并不是一种单纯的期权,其定价要比普通期权复杂。本文首先分析了影响认股权证价格的因素,并在一系列假设条件下,利用Black-Scholes公式,推导出认股权证定价公式;其次,采用了我国宝钢股票及其发行的认股权证的收盘价格资料,计算了公司权益的波动率,利用已推导的公式对认股权证理论进行了实证分析;最后同其实际市场价格进行了比较,为认股权证的投资决策提供了参考依据。