气候变化对经济金融系统性冲击的物理风险研究

中国作为全球最大的发展中国家,其综合实力伴随着经济、科技的快速发展而不断增强。但我国的极端气候事件趋多趋强,气候风险水平呈上升趋势,影响我国经济社会的发展。金融作为经济运行的核心,在宏观经济中有着举足轻重的作用。为了研究气候变化与经济金融稳定之间的关系,本文对极端气候事件损失体系和区域经济金融稳定性综合体系进行指数合成并构建面板模型探讨气候变化中气温和降水量因素的变动和极端气候事件对区域金融稳定的影响,得出气候变化的物理风险通过极端气候事件对经济发展和金融稳定有负面影响,并根据实证结果提出完善绿色金融市场和优化信息披露制度的政策建议。     

Measuring financial risks with copulas

This paper is concerned with the statistical modeling of the dependence structure of multivariate financial data using the concept of copulas. We select some special copulas and identify the type of dependency captured by each one. We fit copulas to daily returns and simulate from the fitted models. We compare the effect of the choice of copula on risk measures and assess the variability of one-step-ahead predictions of portfolio losses. We analyze extreme scenarios and fit extreme value copulas to the block maxima and minima from daily returns. The stress scenarios constructed are compared to those obtained using models from the extreme value theory. We illustrate the usefulness of the copula approach using two stock market indexes.     

WTO financial services commitments: Determinants and impact on financial stability

The paper investigates the factors that have influenced WTO members to take on their chosen level of liberalization commitments in the framework of liberalization of trade in financial services and the impact of such commitments on financial sector stability. The most important factors are economic growth, current account, trends in banking sector development, policy restrictiveness, and peer-group effects. The econometric evidence suggests that more liberal commitments may be associated with greater vulnerability to currency and banking crises—most likely a short-term effect, which should be mitigated with time through increased market efficiency and better resource allocation.     

Risk management under extreme events

This article presents two applications of extreme value theory (EVT) to financial markets: computation of value at risk (VaR) and cross-section dependence of extreme returns (i.e., tail dependence). We use a sample comprised of the United States, Europe, Asia, and Latin America. Our main findings are the following. First, on average, EVT gives the most accurate estimate of VaR. Second, tail dependence of paired returns decreases substantially when both heteroscedasticity and serial correlation are filtered out by a multivariate GARCH model. Both findings are in agreement with previous research in this area for other financial markets.     

EXTREME VALUE THEORY IN FINANCE: A SURVEY

Extreme value theory is concerned with the study of the asymptotic distribution of extreme events, that is to say events which are rare in frequency and huge in magnitude with respect to the majority of observations. Statistical methods derived from it have been employed increasingly in finance, especially for risk measurement. This paper surveys some of those main applications, namely for testing different distributional assumptions for the data, for Value‐at‐Risk and Expected Shortfall calculations, for asset allocation under safety‐first type constraints, and for the study of contagion and dependence across markets under conditions of stress.     

Extreme risk spillovers between crude palm oil prices and exchange rates

This study is the first attempt to examine the extreme risk spillovers between Malaysian crude palm oil (CPO) and foreign exchange currencies of the three largest CPO importers: India, the European Union and China throughout the global financial crisis. Using daily data of three currencies, CPO spot and futures from 2000 to 2018, our results show: First, before the crisis, the unexpected change in foreign exchange rates is the primary driver of risk spillover to the CPO market. Second, during the crisis, the extreme movement of CPO spot returns is dominant in the Malaysian exchange rates relative to the euro. Third, after the crisis, the spillover flows from the CPO market to the foreign exchange market. Overall, our findings show the importance of CPO pricing dynamics in mitigating foreign exchange risk over the crisis period. This paper contributes to the extant literature by recognizing the effect of risk spillover on the targeted foreign exchange rate for portfolio allocation.     

DETERMINANTS OF SOVEREIGN BONDS RATINGS: A ROBUSTNESS ANALYSIS

Several studies have attempted to deduce the determinants of sovereign bond ratings. In this study, Extreme Bounds Analysis is applied to approximately 30 factors proposed by the literature in order to assess their robustness with a focus on the relative importance that economic and political variables receive in the shaping of the ratings. We find that policies that constrain the public sector are among the most robust. Variables such as rule of law, openness to economic flows, central bank independence, and market friendly policies are found to be more robustly correlated with the ratings than foreign reserves, fiscal deficit, sovereign bond yields, and economic growth.     

Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms

This paper investigates behaviour of stock price synchronicity to oil shocks across quantiles for Chinese oil firms. The spillover effects of the oil market on a firm are segregated into firm-specific and market-wide information. First, our results report a higher level of synchronicity by dynamic conditional correlations than by R-square since the former better captures dynamic linear dependence. Second, we find strong evidence of size effect. In particular, stock price synchronicity is generally higher in large-cap firms than in small-cap ones. Oil shocks affect synchronicity in the upper quantiles differently based on firm size. Third, we also find that synchronicity responds to oil shocks significantly in extreme low quantiles, implying that shocks in the oil market are transmitted to Chinese oil firms via firm-specific information. Finally, we determine that oil shocks have little or no immediate impact on stock price synchronicity; instead, cumulative lagged effect is evident. This evidence highlights the lagging effect of spillover of oil shocks on Chinese oil firms.     

A robust VaR model under different time periods and weighting schemes

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable.

股市暴涨暴跌的界定及比较——以中国、美国、英国、日本股市为例

本文运用经验分布函数对中、美、英、日四国股市的暴涨暴跌进行了界定,并对四国股市暴涨暴跌的表现进行了比较分析。相比其它三国,中国股市在过去15年间成长性最强,暴涨暴跌的幅度最大,表现出较强的"政策驱动型"特征。美、英、日股市的暴涨暴跌呈现出明显的"市场和事件驱动型"特征。英国和美国股市波动呈现出较强的同步性,但日本股市波动较为独特。政策建议上,各国应通力合作,以应对全球系统性风险对股市的影响;中国政府应加强股市的市场化建设,同时谨慎开放资本市场。