多币种兑人民币汇率的协同波动溢出——基于IC-EGARCH模型的实证研究

建立基于独立成分的IC-EGARCH模型对美元、欧元、港币及日元兑人民币汇率市场的杠杆效应进行刻画以及协同波动溢出进行分析,结果显示:以上四个市场都有显著的杠杆效应,对其中任一市场而言,其他三个市场对其都有正向或负向的波动溢出且影响权重各不相同.另外,通过与传统的多元波动率模型BEKK和DCC-MVGARCH对比发现,IC-EGARCH不仅弥补了其模型稳定性差、假设条件不符合实际的缺陷还能显著减少模型的参数估计个数以及通过独立成分体现影响权重.     

汇率波动对对外投资上市企业价值影响研究

全球经济金融的融合、人民币汇率浮动机制的实施以及人民币升值压力的加剧,势必会给中国对外直接投资企业带来越来越大的影响。以从事直接对外投资的沪深上市公司为样本,通过对传统的Jorion模型进行拓展,研究人民币兑美元、欧元、日元的汇率波动对这些企业价值的影响。结果显示,人民币兑美元、欧元、日元的汇率对企业价值影响最为显著的是人民币兑日元汇率;人民币兑美元升值造成了大部分企业价值的贬损;人民币兑欧元升值给企业价值带来的显著影响呈现出正向、负向共存的特点;而人民币兑日元贬值则给大多数企业价值带来了显著的正向影响。     

人民币即期汇率与NDF汇率关系的实证分析

以人民币即期汇率与NDF汇率为例研究境内市场与境外市场的信息传递。主要利用GARCH模型描述人民币即期汇率与NDF的变动并检验人民币即期汇率与NDF之间的均值溢出效应和波动溢出效应。得到的主要结论为,人民币NDF市场对人民币即期汇率市场有均值溢出效应,人民币即期汇率和NDF之间有双向波动溢出效应。这表明信息流由境外市场传导至境内市场,人民币即期汇率市场受到境外市场因素的影响,境外人民币NDF市场是境内即期市场的先导。     

人民币NDF与即期汇率的动态关联性研究

文章以2005年7月25日~2006年6月13日间人民币NDF和即期汇率为研究对象,以MA(1)-GARCH(1,1)模型分析人民币NDF市场和即期市场间均值和波动的溢出效应。分析结果表明,两个市场的波动没有相互溢出效应,即期市场对人民币NDF市场没有报酬溢出效应,而人民币NDF市场对即期市场具有报酬溢出效应。可见,我国汇制改革后,境外因素已开始影响人民币即期市场。     

人民币离岸市场与在岸市场互动机制的实证分析

此次金融危机爆发后,人民币国际化受到了国内外众多关注。本文基于ARMA-GARCH模型,探讨了人民币离岸在岸之间的互动效应。分析结果显示,在CNH市场建立之前,CNY市场和NDF市场的远期汇率之间的联系不显著;CNH市场建立之后,CNY市场、NDF市场和CNH市场之间在绝大多数期限的远期汇率之间均存在溢出效应,NDF市场的溢出效应和价格引导能力最强,其次是CNY市场,最后是CNH市场。由于规模所限,CNH作为新兴的人民币离岸市场,其汇率波动对于CNY市场汇率波动的溢出效应不是十分明显,CNY市场的汇率波动对于CNH市场有较强的溢出效应,即在岸的CNY市场人民币汇率对CNH市场人民币汇率存在较强的价格引导能力。     

引力模型下汇率波动对贸易流量的影响——基于中美、中日贸易的实证研究

在贸易引力模型下引入汇率波动性因素对中美、中日贸易总量进行实证研究,验证了贸易引力模型的成立,并发现:人民币兑美元汇率波动显著抑制中美贸易总量;人民币兑日元汇率波动对中日贸易总量无显著影响。考虑到中日间贸易较大部分采用美元结算,因此将人民币兑美元汇率与日元兑美元汇率波动引入中日贸易框架,发现人民币兑美元汇率与日元对美元汇率波动均显著地抑制中日贸易总量。结论说明,在国际贸易中汇率波动给交易主体带来经济风险,抑制国际贸易的发展,各国应注重维持汇率的稳定以促进经济贸易的健康发展。     

基于GARCH模型对人民币汇率波动的实证研究

本文建立了人民币汇率波动的GARCH族模型,实证检验了汇率制度改革以来人民币汇率波动的特征。结果显示,2005年7月21日至今,人民币的汇率收益具有显著的左厚尾特征;汇率的波动并不服从正态分布,具有集聚性;并且人民币的波动具有记忆性,随时间变化不会衰减;通过TGARCH模型的实证结果显示,人民币的汇率波动存在一定的杠杆效应,人民币汇率还不具备浮动汇率的特征。根据分析,本文认为杠杆效应的存在源自于汇率升值的单向预期,给出以下建议：通过有节奏的汇率市场化改革,以及改善国际收支双顺差,减少对升值的单向预期;央行对汇率的波动适当控制;培育人民币汇率衍生市场,增加进出口贸易企业规避汇率风险的金融产品;增加对附加值高的出口企业非汇率贸易政策支持。     

人民币/美元日汇率收益模型的建立

人民币汇率制度改革以后,人民币汇率的波动特点也发生了变化。本文对人民币/美元的日汇率收益序列进行实证研究,建立相应的GARCH模型并对未来值进行预测。结果表明GARCH-t(1,1)模型能够很好的刻画人民币/美元的日汇率收益序列的统计特征,而且对未来的短期预测具有可行性。     

人民币升值预期与国际油价关系的实证研究

文章在回顾国内外研究国际油价与汇率关系的基础上,运用溢出效应模型、协整检验、VEC模型对人民币汇率形成机制改革之后国际油价与人民币升值预期的关系进行了实证分析。结果发现:国际油价与人民币升值预期之间具有长期均衡关系,但仅仅存在国际油价对人民币升值预期的单向传导作用,溢出效应方面也只有国际油价对人民币无本金交割远期交易汇率的单向收益溢出效应与波动溢出效应。从短期看,国际油价上涨会削弱人民币升值预期,而从长期看则会增强人民币升值预期。     

人民币汇率波动与证券市场价格波动相关性的实证分析

文章尝试运用单位根、协整模型和向量自回归模型,对人民币汇率波动与证券市场价格波动的相关性进行实证分析。分析结果显示,无论从长期运行关系还是短期波动状况,人民币兑美元汇率与上证指数、A股指数之间存在显著的相关关系,而与B股指数之间则不存在显著的相关关系,而人民币兑欧元、日元汇率与上证指数、A股指数之间则不存在显著的相关关系。     

Invoice currency choice,nonlinearities and exchange rate pass-through

ABSTRACT

Estimating time-varying thresholds as a proxy for exporter’s predicted exchange rates, this study proposes a new approach to analyse possible asymmetric behaviour of exchange rate pass-through (ERPT) or pricing-to-market (PTM) in Japanese exports between yen appreciation and depreciation periods. Constructing the industry-specific nominal effective exchange rate on a contract (invoice) currency basis, we perform the multivariate threshold near-vector autoregressive (near-MTVAR) estimation and reveal a strong tendency of symmetric ERPT in the short-run, between yen appreciation and depreciation periods. From the 2000s, however, Japanese machinery exporters increased the degree of PTM even in the long-run, while other industries raised the degree of long-run ERPT, reflecting the difference of product differentiation across industries. This evidence has significant implications for the recent unresponsiveness of the Japanese trade balance to the large depreciation of the yen.     

汇率非线性因素在部分亚洲货币汇率中的特征——检验购买力平价论的新方法

当真实汇率运动实际上是非线性过程,而假设它为线性时,那么检验购买力评价理论的标准单位根检验通常是低效力的。文章运用带有单位根的门限自回归模型模拟了包括中国在内的6个亚洲主要新兴市场国家货币兑美元的真实汇率,发现它们都具有较强的非线性,说明了传统的线性方法不再具备模拟真实汇率的能力,且除人民币以外的其他5种货币的真实汇率都表现出了平稳非线性特征,在异动时期具有均值回归的趋势。周期性的金融危机是导致中国以外的其他5个国家货币的真实汇率出现异动的主要因素。人民币真实汇率的非线性行为则表现出了与其他国家不同的特点,导致它出现异动的主要因素为人民币对内和对外价格的相互背离,人民币真实汇率没有表现出向均值调整的趋势,甚至在异动时期呈现了向均值偏离的趋势。     

BAYESIAN ANALYSIS OF GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY AND STOCHASTIC VOLATILITY: MODELING LEVERAGE,JUMPS AND HEAVY‐TAILS FOR FINANCIAL TIME SERIES*

This paper develops a Bayesian model comparison of two broad major classes of varying volatility model, the generalized autoregressive conditional heteroskedasticity and stochastic volatility models, on financial time series. The leverage effect, jumps and heavy‐tailed errors are incorporated into the two models. For estimation, the efficient Markov chain Monte Carlo methods are developed and the model comparisons are examined based on the marginal likelihood. The empirical analyses are illustrated using the daily return data of US stock indices, individual securities and exchange rates of UK sterling and Japanese yen against the US dollar. The estimation results indicate that the stochastic volatility model with leverage and Student‐t errors yield the best performance among the competing models.     

A small forward-looking inter-country model (Belarus, Russia and Ukraine)

The paper describes an inter-country model developed on the New Keynesian Phillips curve principle for the economies of Belarus, Russia and Ukraine. Technically the modelling idea has been grounded within the concept of the infinite dimensional vector autoregressive models by Chudik and Pesaran [Chudik A., Pesara M.H., 2007. Infinite-dimensional VAR's and factor models. IZA; DP No. 3206]. The main developments are such that the model is 1) interdependent rather than vector autoregressive, 2) estimated by the generalised method of moments and 3) forward-looking. The primary linkage of the country models is provided through the real effective exchange rates of particular countries, while the secondary linkages are through the Chudik and Pesaran cross-sectional augmentations. A series of Monte Carlo experiments confirms that the small cross-dimension of the model and a possible dominance of one country in the panel (Russia) should not distort the results in a significant way. A series of stochastic simulation experiments made with and without the assumption of observational equivalence principle shows a possible spread of the Dutch Disease from Russia to other countries in the model.     

AGGREGATION,HETEROGENEOUS AUTOREGRESSION AND VOLATILITY OF DAILY INTERNATIONAL TOURIST ARRIVALS AND EXCHANGE RATES*

Tourism is a major source of service receipts for many countries, including Taiwan. The two leading tourism countries for Taiwan are Japan and the USA, which are sources of short‐ and long‐haul tourism, respectively. As a strong domestic currency can have adverse effects on international tourist arrivals through the price effect, daily data from 1 January 1990 to 31 December 2008 are used to model the world price, exchange rates, and tourist arrivals from the world, the USA and Japan to Taiwan, and their associated volatility. Inclusion of the exchange rate and its volatility captures approximate daily and weekly price and price volatility effects on world, US and Japanese tourist arrivals to Taiwan. The heterogeneous autoregressive model is used to approximate the slowly decaying correlations associated with the long‐memory properties in daily and weekly exchange rates and international tourist arrivals, to test whether alternative short‐ and long‐run estimates of conditional volatility are sensitive to the long‐memory in the conditional mean, to examine asymmetry and leverage in volatility, and to examine the effects of temporal and spatial aggregation. The approximate price and price volatility effects tend to be different, with the exchange rate typically having the expected negative impact on tourist arrivals to Taiwan, whereas exchange rate volatility can have positive or negative effects on tourist arrivals to Taiwan. For policy purposes, the empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings as they are generally not independent of the level of aggregation used.     

The inadequacy of linear autoregressive model for real exchange rates: empirical evidence from Asian economies

Utilizing the formal linearity test of Luukkonen, Saikkonen and Teräsvirta (Biometrika, 75, 491-499, 1998) as diagnostic tool, the empirical finding suggests that the linear autoregressive (AR) model is inadequate in describing the real exchange rates behaviour of 11 Asian economies. It is noted that the conventional battery of diagnostic tests is capable of identifying the inadequacy of the linear model in only three of these series. Moreover, the linearity nature of this behaviour has been formally rejected in favour of the non-linear smooth transition autoregressive (STAR) model. The finding of non-linearity in the data generating process of these real exchange rates warrants that the use of linear framework in empirical modelling and statistical testing procedures in the field of exchange rates may lead to an inappropriate policy conclusions.     

Autoregressive conditional durations: An application to the Surinamese dollar versus the US dollar exchange rate

The parallel market nominal exchange rate of the United States dollar vis-à-vis the Surinamese dollar (USD/SRD) exhibited periods of severe volatility which were often followed by episodes of stability, usually at a cost of sharp depreciations. This study seeks to model this exchange rate using autoregressive conditional duration models. These models are suitable for modelling events occurring with irregular intervals. Exchange rates in developing countries have distinct features compared to exchange rates in countries with well-established and accessible financial markets. A key feature is that for these developing countries, exchange rates only occasionally experience jumps. Our findings suggest that past exchange rate changes appear to be a significant driver of future exchange rate jumps. Furthermore, our results show that money, international reserves, and commodity prices can explain jumps in the market USD/SRD exchange rate.     

Volatility and Spillover Effects of Yen Interventions

We consider the effects of interventions by the Bank of Japan's (BoJ) on the intraday volatility of the US dollar/Japanese yen (USD/JPY) exchange rates and their spillovers to volatility of the euro/JPY exchange rates. We use 15‐minute data during the period 2000–2004 and employ multivariate generalized autoregressive conditional heteroskedasticity (GARCH) modeling and quartile plots of intraday volatility to analyze the intraday effects of the BoJ interventions on exchange rate volatility. The results indicate that the BoJ interventions decrease daily volatility of the USD/JPY exchange rate but increase the volatility of the euro/JPY series. On intervention days, the intraday volatility has different patterns to those on non‐intervention days.     

Calibration of implied volatility for the exchange rate for the Chinese Yuan from its derivatives

Revised implied volatility curves and surfaces for the Chinese Yuan (CNY) exchange rate are obtained from market quotations for CNY non-deliverable options by solving an inverse problem of foreign exchange option pricing, which is calculated using a regularization approach in an optimal control framework. To take account of the market expectation for the CNY exchange rate, a stochastic adjusted factor is applied that follows a Vasicek model with parameters fitted from market quotations for CNY non-deliverable forwards. A well-posed numerical scheme is implemented.     

Remittances and the Dutch Disease: Evidence from the Republic of Moldova

This paper analyzes the linkage between exports, real effective exchange rates, and workers’ remittances in the Republic of Moldova based on impulse response functions through a vector autoregressive model. We find that an inflow of remittances leads to an appreciation of real exchange rate and a decline of exports, but the magnitude is small. Another finding is that the exchange rate appreciation does not affect remittance transfers for the first three-quarters.