欧盟碳市场与能源市场的相依结构研究——基于多元Copula-Kernel模型

自欧盟碳市场建立以来,对于这一新兴的人为建立的虚拟商品(碳排放权)金融市场的研究不断深入。基于对第二、第三交易阶段欧盟碳期货与能源期货价格及日收益率数据进行多元Copula-Kernel模型拟合的基础上,研究碳资产与能源资产之间的波动传导效应和相依结构,这对于评价碳市场运作效率有重要意义。研究结果表明,能源期货的日收益率与碳期货日收益率存在弱正相关性,相依系数0.18,且上下尾对称分布,相关系数为0.30,两市场之间存在弱传导效应。研究结果还表明,欧盟碳市场与能源市场之间的影响关系在金融危机后逐步恢复,碳市场也逐渐走向成熟和有效。     

基于小波分析的中美大豆期货价格周期波动关联性研究

本文运用小波分析法对大连商品期货交易所(DCE)和芝加哥商品交易所(CBOT)大豆期货价格序列以及收益率序列进行分解与重构,分析了两个市场的波动周期,并结合VAR和多元GARCH-BEKK模型,从价格溢出和波动溢出两个角度研究了不同尺度下国内外期货价格之间的动态关系,结果表明:国内外大豆各细节层期货价格收益率之间存在显著的价格溢出与波动溢出效应,且主要是CBOT向DCE的价格溢出与波动溢出传导.     

股指期货与现货市场溢出效应及动态关系研究——基于中、美、日、香港等市场的实证分析

本文运用BEKK-MGARCH-VAR和DCC-MGARCH模型分别实证分析了中国、美国、日本及香港等地股指期货与现货市场收益率均值和波动的溢出效应以及两市相关系数的动态(时变)特征,研究发现:四个国家(地区)股指期货与现货市场收益率间均存在双向均值溢出效应;四个国家(地区)股指期货与现货市场间均存在双向波动溢出效应;新兴经济体的指数期货与现货市场间的动态相关系数波动较小,而发达国家指数期货与现货市场间的动态相关系数波动较为明显。最后,对当前中国政策当局规范股指期货市场,警惕期现两市之间的波动传导效应,以确保股指期货和现货两市的稳定提出政策建议。     

我国期货价格风险管理研究——基于VaR方法与GARCH-t模型的视角

本文利用我国商品期货及金融期货2010年9月份合约数据采用VaR方法对其收益率序列的波动性进行了检验。研究结果发现:首先,应用GARCH-t模型的方法对期货商品的价格风险进行管理具有显著的有效性和适用性,特别是在95%的置信水平下对收益率波动性的拟合效果最佳,同时该方法对期货商品正收益率的拟合效果比负收益率更好。其次,我国股指期货正式推出后,收益率波动性较模拟交易时期显著变小,表明改进后的交易制度及政府监管等措施可能限制了市场上的过度投机行为。最后,农副产品期货的风险暴露程度比股指、金属和能源化工等期货品种要小。     

我国股指期货市场与股票市场溢出效应研究

运用基于结构向量自回归模型的溢出指数,检验我国沪深300股指期货与沪深300指数收益率间静态和动态的波动溢出效应和信息溢出效应。结果表明,在股指期货市场未限制交易前,我国沪深300股指期货收益率波动对沪深300指数收益率波动具有显著正向净溢出效应,沪深300股指期货成交量对沪深300指数收益率波动也具有显著正向净溢出效应;在股票市场剧烈波动时,波动溢出效应和信息溢出效应均会增加,沪深300股指期货成交量的增加会放大股指期货对现货的波动溢出效应。因此,在我国股票市场持续不稳定波动的背景下,对股指期货成交量和波动进行合理的管制,可降低期货市场对股票市场的波动溢出效应,进而有效防范资本市场风险。     

我国股指期货市场非对称性波动与下行风险研究

我国正处于经济转型升级的重要时期,资本市场改革的不断深化导致金融产品的风险增大,波动行为也具有一定特殊性。因此,加深对我国股指期货波动特征及风险的认识、加快完善股指期货市场体系尤为重要。运用成分GARCH模型对我国沪深300股指期货市场收益率波动的非对称性进行检验,并通过下行风险资本资产定价模型对下行风险进行测量。结果表明:沪深300股指期货收益率波动存在非对称性,即负面冲击会增加收益率波动,而正面冲击会降低收益率波动;沪深300股指期货的下行风险可解释部分收益率的变化,投资者会因为承担下行风险而获得额外的风险补偿;沪深300股指期货协偏度为负说明其收益率与市场波动率负相关,从而投资者会要求更高的预期收益率。因此,由于投资者对风险的厌恶,沪深300股指期货的收益率非对称性波动、高下行风险和负协偏度使其应具有更高的预期收益率。     

地缘冲突风险、大宗商品金融化与农产品期货价格波动

全球范围内地缘格局的调整对我国农产品期货价格波动产生深远影响，从而给我国粮食安全带来诸多不确定性。为此借助TVP-VAR模型，基于2013年1月至2022年7月的数据，实证检验了地缘冲突风险对我国农产品期货价格冲击的时变特征，并探析了大宗商品金融化在其中的传递效应。研究表明：样本期间内，国际地缘冲突风险会降低国内农产品期货收益率，而国内面临的地缘冲突风险则提升了国内农产品期货收益率。基于大宗商品金融化传递效应的解析表明，大宗商品金融化对农产品期货收益率具有正向冲击，国际地缘冲突风险在中长期抑制了大宗商品金融化，叠加投资者悲观情绪导致国内农产品期货收益率下降；国内面临的地缘冲突风险则提升了大宗商品金融化，在供需基本面失衡状态下引发国内农产品期货收益率上升。在地缘冲突加剧的背景下，研究结果为利用农产品期货进行套期保值，确保粮食安全提供了经验证据。     

传统能源及碳交易价格与新能源股价——基于VAR和CAPM-GARCH模型的分析

文章构建VAR模型和CAPM-GARCH模型,分析检验了2010年7月初至2013年底期间传统能源和碳排放权交易价格对国内新能源上市公司股价波动的影响及新能源股票收益率的波动特点,研究发现:国内煤价对新能源公司股价有显著的正向影响,而国际油价的影响不显著;碳排放权交易价格也是引起新能源投资价值从而上市公司股价变动的重要因素;新能源公司股价指数对高科技股价指数并不敏感,反映出国内新能源上市公司科技含量不足,资本市场关注更多的是新能源的概念而非技术优势;国内新能源股票整体的系统风险在1.125~1.131之间,利好消息比利空消息能引起新能源股票收益率更大的波动。     

百科:股指期货

Share Price Index Futures,英文简称SPIF,全称是股票价格指数期货,也可称为股价指数期货、期指,是指以股价指数为标的物的标准化期货合约,双方约定在未来的某个特定日期,可以按照事先确定的股价指数的大小,进行标的指数的买卖。目前我国的股指期货是以沪深300指数作为标的物的期货品种,在2010年4月由中国金融期货交易所推出。沪深300股票指数由中证指数公司编制的沪深300指数于     

中国与国际大豆期货市场波动溢出效应分析

文章采用多元GARCH(MGARCH)模型,研究中国、美国和日本大豆期货市场的相关性和波动溢出效应。结果表明:在样本研究期间,大连、芝加哥和东京大豆期货交易市场之间存在正相关,大连大豆期货市场与芝加哥大豆期货的相关性要小于东京谷物交易所大豆期货与芝加哥大豆期货的相关性;大连、芝加哥和东京大豆期货交易所存在双向的波动溢出效应;在三个市场中,大连大豆期货的新息冲击和自身波动溢出值最小,但在统计上不显著,可能与目前大连期货市场受管制和相对封闭等因素有关;三个大豆期货市场市场均不存在波动持续性。     

Correlations and volatility spillovers across commodity and stock markets: Linking energies,food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets.     

Hedging and diversification across commodity assets

ABSTRACT

We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.     

Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

The effectiveness of index futures hedging in emerging markets during the crisis period of 2008-2010: Evidence from South Africa

This article provides an assessment of the comparative effectiveness of four econometric methods in estimating the optimal hedge ratio in an emerging equity market, particularly the South African equity and futures markets. The article bases the effectiveness of hedging on volatility reduction and minimization of the coefficient of variation of hedged returns as well as risk-aversion-based utility maximization. The empirical analysis shows that the vector error-correction method and multivariate generalized autoregressive conditional heteroscedasticity methods are most effective over relatively long horizon, weekly and monthly hedging periods.     

纽约黄金期货价格波动对我国期货市场收益率的影响研究

随着我国期货市场的迅速发展,商品期货逐步显示出金融属性。本文运用自回归分布滞后模型结合GARCH族模型对纽约黄金期货价格波动与我国上海期货交易所沪铜、沪铝、沪锌、天然橡胶、燃料油期货价格波动之间的动态关系展开研究,以考察宏观经济运行对我国期货市场的影响。     

Market volatility and the dynamic hedging of multi-commodity price risk

Commodity cash and futures prices experienced a severe boom-and-bust cycle between 2006 and 2009. Increases in commodity price volatility have raised concerns about the usefulness of commodity futures and options as risk management tools. Dynamic hedging strategies have the potential to improve risk management when conditional (co)variances depart significantly from their unconditional, long-run counterparts and may be useful to decision-makers despite their greater complexity and higher transaction costs. We propose a Nonparametric Copula-based Generalized Autoregressive Conditional Heteroscedastic (NPC-GARCH) approach to estimate time-varying hedge ratios, and evaluate the benefits of dynamic hedging during four sub-periods between 2000 and 2011 using a stylized Texas cattle feedlot management problem. The NPC-GARCH approach allows for a flexible, nonlinear and asymmetric dependence structure between cash and futures prices for different commodities. We find that NPC-GARCH dynamic hedging performs better than either static, GARCH-Dynamic Conditional Correlation (DCC) or GARCH-Baba, Engle, Kraft and Kroner (BEKK) hedging in terms of lower tail risk (expected shortfall), but that there is no significant difference between hedging approaches in terms of portfolio variance reduction.     

Which types of commodity price information are more useful for predicting US stock market volatility?

This study aims to investigate which types of commodity price information are more useful for predicting US stock market realized volatility (RV) in a data-rich word. The standard predictive regression framework and monthly RV data are used to explore the RV predictability of commodity futures for the next-month RV on S&P 500 spot index. We utilize principal component analysis (PCA) and factor analysis (FA) to extract the common factors for each type and all types of commodity futures. Our results indicate that the futures volatility information of grains and softs has a significant predictive ability in forecasting the RV of the S&P 500. In addition, the FA method can yield better forecasts than the PCA and average methods in most cases. Further analysis shows that the volatility information of grains and softs exhibits higher informativeness during recessions and pre-crises. Finally, the forecasts of the five combination methods and different out-of-sample periods confirm our results are robust.     

Testing commodity futures market efficiency under time-varying risk premiums and heteroscedastic prices

We propose a novel test to measure market efficiency while estimating the time-varying risk premiums of commodity futures, given that the prices are heteroscedastic. The risk premium is estimated using a state-space model with a Kalman filter modified for heteroscedasticity. Using 79 commodity futures traded on 16 exchanges during the period 2000–2014 and a Monte Carlo simulation, we demonstrate that the proposal produces robust results compared with conventional approaches. The global financial crisis has improved the efficiency and affected the trading volumes of commodity futures, but it has had no effect on the average or the volatility of risk premiums.     

NEGATIVE CORRELATION BETWEEN STOCK AND FUTURES RETURNS: AN UNEXPLOITED HEDGING OPPORTUNITY?

The negative correlation between equity and commodity futures returns is widely perceived by investors as an unexploited hedging opportunity. A Lucas (1982) asset‐pricing model is adapted to analyse the fundamentals driving equity and commodity futures returns. Using the model we argue that such a negative correlation could arise as an equilibrium relationship which reflects traders' perceptions about the shocks driving the fundamentals such as energy and consumables, and does not necessarily indicate any hedging opportunity.