基于沪铜期货的套期保值比率与效率比较的实证分析

本文以沪铜期货的多头套期保值为研究对象,分别利用OLS模型、ECM模型和GARCH模型对一月期铜和三月期铜的套期保值比例及保值效果进行了分析.发现OLS模型对一月期铜的套期保值效果要优于其他模型的保值效果,而ECM模型和GARCH模型在三月期铜的套期保值方面显示的效果更好.这说明在一般情况下,具有动态特征的计量模型适合于较长的期货合约,其套期保值效果更好.     

沪深300ETF套期保值效果的比较研究

文章采用OLS、ECM、CCC-BGARCH以及DCC-BGARCH模型分别计算了两支300ETF的最优套期保值比率,并分别比较了两支300ETF的套期保值效果,结果发现：动态多元GARCH类模型的效果明显好于OLS和ECM模型;无论采用哪种模型,华泰柏瑞沪深300ETF的套期保值效果都要好于嘉实沪深300ETF;由于华泰柏瑞沪深300ETF的高流动性和相对完善的套利机制,使得其适合较大方差变化的DCC-BGARCH模型;而嘉实沪深300ETF采用CCC-BGARCH模型的套期保值效果更好,这可能是因为嘉实沪深300ETF和沪深300股指期货间的关联性波动较小,相关系数更接近于常数的缘故。     

估计期货的最优套期保值比率——基于我国锌期货的实证研究

本文在运用OLS方法计算套期保值比率的基础上引入协整检验和ECM模型,以达到更好地估计最优套期保值比率的目的。     

估计期货的最优套期保值比率——基于我国锌期货的实证研究

本文在运用OLS方法计算套期保值比率的基础上引入协整检验和ECM模型,以达到更好地估计最优套期保值比率的目的。     

中国期货市场套期保值绩效实证研究

为了研究中国期货市场的套期保值绩效，本文利用确定套期保值比率的OLS、B-VAR、ECHM和EC—GARCH四个模型和套期保值绩效的衡量指标，对中国期货的小麦、大豆、铜和铝的套期保值比率和绩效进行了实证研究，使用1998～2004年中国期货与现货价格的周数据来进行单位根和协整检验等计量分析。研究显示，金属期货品种的套期保值比率和绩效比农产品期货品种的套期保值比率和绩效都要高。考虑了协整关系的ECHM和EC—GARCH模型的套期保值比率和绩效比没有考虑协整关系的OLS和B—VAR模型高，样本区间外的套期保值绩效优于样本区间内的绩效。本文认为采用ECMH和EC—GARCH模型进行套朔保值是最佳的策略。     

恒生指数和沪深300股指期货套期保值效果对比研究

本文利用OLS、ECM、ECM-GARCH模型对沪深300股指期货和恒生指数期货的最优套期保值率进行了估算,并在风险最小化框架下对它们的套期保值效果进行了对比研究。结果发现:无论是哪种股指期货,不考虑期现货间存在的协整关系会使估算的最优套期保值率偏高,影响套期保值效果;其次是虽然在样本内外,沪深300股指期货的套期保值效果比恒生指数期货的好,但是沪深300股指期货套期保值效果的稳定性比恒生指数差。此时,ECM-GARCH和OLS模型分别为样本内外投资者利用沪深300指数期货进行套期保值时的最佳选择;对于恒生指数股指期货,最优模型是ECM。     

我国期货市场套期保值有效性实证研究——以白糖期货为例

本文以白糖期货为例,分别采用OLS模型、B-VAR模型和ECM模型,从组合投资方差最小化的视角实证研究我国期货市场套期保值有效性问题,同时利用样本内和样本外数据对不同套期保值比率下的套期保值有效性进行比较分析。结果显示:与不进行套期保值相比,参与套期保值能够显著降低组合资产收益风险,转移现货市场价格波动风险;无论样本内还是样本外,利用基于协整关系的ECM模型估计得到的套保比率进行套期保值效果都是最好的。     

我国期货市场套期保值有效性实证研究——以白糖期货为例

本文以白糖期货为例,分别采用OLS模型、B-VAR模型和ECM模型,从组合投资方差最小化的视角实证研究我国期货市场套期保值有效性问题,同时利用样本内和样本外数据对不同套期保值比率下的套期保值有效性进行比较分析.结果显示:与不进行套期保值相比,参与套期保值能够显著降低组合资产收益风险,转移现货市场价格波动风险;无论样本内还是样本外,利用基于协整关系的ECM模型估计得到的套保比率进行套期保值效果都是最好的.     

黄金期货最优套期保值策略实证研究

随着我国黄金期货市场的发展,越来越多的黄金投资者通过黄金期货进行套期保值来规避由于黄金价格波动引起损失的风险。本文运用黄金期货套期保值绩效作为套期保值有效性的评价指标,对OLS模型、ECM模型、BGARCH模型和ECM-BGARCH模型以及黄金期货一个月期、二个月期和三个月期的套期保值有效性进行横向和纵向的对比研究,以期为黄金投资者提升套期保值有效性,减少由于黄金价格波动而造成的损失提供思路。     

沪深300股指期货套期保值模型选择与绩效评价

摘要：基于不同套期保值模型,本文对沪深300股指期货的套期保值效应进行了实证分析,并通过“风险最小化”原则和“效用最大化”原则分别比较不同模型的套期保值绩效。结果发现,在“风险最小化”原则下,无论是对于样本内还是样本外数据,对角ECM．BGARCH（1,1）模型的套期保值绩效都为最优;在“效用最大化”原则下,无论风险系数水平如何,样本内DCC．GARCH模型的套期保值绩效最优,样本外标量ECM—BGARCH（1,1）模型的套期保值绩效最优。     

Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection

During the recent European sovereign debt crisis, returns on EMU government bond portfolios experienced substantial volatility clustering, leptokurtosis and skewed returns as well as correlation spikes. Asset managers invested in European government bonds had to derive new hedging strategies to deal with changing return properties and higher levels of uncertainty. In this environment, conditional time series approaches such as GARCH models might be better suited to achieve a superior hedging performance relative to unconditional hedging approaches such as OLS. The aim of this study is to test innovative hedging strategies for EMU bond portfolios for non-crisis and crisis periods. We analyze single and composite hedges with the German Bund and the Italian BTP futures contracts and evaluate the hedging effectiveness in an out-of-sample setting. The empirical analysis includes OLS, constant conditional correlation (CCC), and dynamic conditional correlation (DCC) multivariate GARCH models. We also introduce a Bayesian composite hedging strategy, attempting to combine the strengths of OLS and GARCH models, thereby endogenizing the dilemma of selecting the best estimation model. Our empirical results demonstrate that the Bayesian composite hedging strategy achieves the highest hedging effectiveness and compares particularly favorable to OLS during the recent sovereign debt crisis. However, capturing these benefits requires low transactions cost and efficiently functioning futures markets.     

STOCK INDEX FUTURES HEDGING: HEDGE RATIO ESTIMATION, DURATION EFFECTS, EXPIRATION EFFECTS AND HEDGE RATIO STABILITY

This paper examines hedging effectiveness for the FTSE-100 Stock Index futures contract from 1984 to 1992. It investigates the appropriate econometric technique to use in estimating minimum variance hedge ratios by undertaking estimations using OLS, an ECM and GARCH. Simple OLS outperforms more complex econometric techniques. Additionally, the paper examines the impact ofhedge duration and time to expiration on estimated hedge ratios and hedge ratio stability over time. It is shown that hedge ratios and hedging effectiveness increase with hedge duration, hedge ratios approach unity as expiration approaches and while hedge ratios vary over time they are stationary.     

Short-run deviations and time-varying hedge ratios: Evidence from agricultural futures markets

This paper investigates the hedging effectiveness of time-varying hedge ratios in the agricultural commodities futures markets using four different versions of the GARCH models. The GARCH models applied are the standard bivariate GARCH, the bivariate BEKK GARCH, the bivariate GARCH-X and the bivariate BEKK GARCH-X. Futures data for corn, coffee, wheat, sugar, soybeans, live cattle and hogs are applied. Comparison of the hedging effectiveness is done for the within sample period (1980–2004), and two out-of-sample periods (2002–2004 and 2003–2004). Results indicate superior performance of the portfolios based on the GARCH-X model estimated hedge ratio during all periods.     

Optimal hedge ratio and hedging effectiveness of stock index futures: evidence from India

In a free capital mobile world with increased volatility, the need for an optimal hedge ratio and its effectiveness is warranted to design a better hedging strategy with future contracts. This study analyses four competing time series econometric models with daily data on NSE Stock Index Futures and S&P CNX Nifty Index. The effectiveness of the optimal hedge ratios is examined through the mean returns and the average variance reduction between the hedged and the unhedged positions for 1-, 5-, 10- and 20-day horizons. The results clearly show that the time-varying hedge ratio derived from the multivariate GARCH model has higher mean return and higher average variance reduction across hedged and unhedged positions. Even though not outperforming the GARCH model, the simple OLS-based strategy performs well at shorter time horizons. The potential use of this multivariate GARCH model cannot be sublined because of its estimation complexities. However, from a cost of computation point of view, one can equally consider the simple OLS strategy that performs well at the shorter time horizons.     

Model risk of the implied GARCH-normal model

Model risk causes significant losses in financial derivative pricing and hedging. Investors may undertake relatively risky investments due to insufficient hedging or overpaying implied by flawed models. The GARCH model with normal innovations (GARCH-normal) has been adopted to depict the dynamics of the returns in many applications. The implied GARCH-normal model is the one minimizing the mean square error between the market option values and the GARCH-normal option prices. In this study, we investigate the model risk of the implied GARCH-normal model fitted to conditional leptokurtic returns, an important feature of financial data. The risk-neutral GARCH model with conditional leptokurtic innovations is derived by the extended Girsanov principle. The option prices and hedging positions of the conditional leptokurtic GARCH models are obtained by extending the dynamic semiparametric approach of Huang and Guo [Statist. Sin., 2009, 19, 1037–1054]. In the simulation study we find significant model risk of the implied GARCH-normal model in pricing and hedging barrier and lookback options when the underlying dynamics follow a GARCH-t model.     

Hedging with Two Futures Contracts: Simplicity Pays

We propose to use two futures contracts in hedging an agricultural commodity commitment to solve either the standard delta hedge or the roll‐over issue. Most current literature on dual‐hedge strategies is based on a structured model to reduce roll‐over risk and is somehow difficult to apply for agricultural futures contracts. Instead, we propose to apply a regression based model and a naive rules of thumb for dual‐hedges which are applicable for agricultural commodities. The naive dual strategy stems from the fact that in a large sample of agricultural commodities, De Ville, Dhaene and Sercu (2008) find that GARCH‐based hedges do not perform as well as OLS‐based ones and that we can avoid estimation error with such a simple rule. Our semi‐naive hedge ratios are driven from two conditions: omitting exposure to spot price and minimising the variance of the unexpected basis effects on the portfolio values. We find that, generally, (i) rebalancing helps; (ii) the two‐contract hedging rules do better than the one‐contract counterparts, even for standard delta hedges without rolling‐over; (iii) simplicity pays: the naive rules are the best one–for corn and wheat within the two‐contract group, the semi‐naive rule systematically beats the others and GARCH performs worse than OLS for either one‐contract or two‐contract hedges and for soybeans the traditional naive rule performs nearly as well as OLS. These conclusions are based on the tests on unconditional variance ( Diebold and Mariano, 1995 ) and those on conditional risk ( Giacomini and White, 2006 ).     

Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets

The dynamic minimum variance hedge ratios (MVHRs) have been commonly estimated using the Bivariate GARCH model that overlooks the basis effect on the time-varying variance–covariance of spot and futures returns. This paper proposes an alternative specification of the BGARCH model in which the effect is incorporated for estimating MVHRs. Empirical investigation in commodity markets suggests that the basis effect is asymmetric, i.e., the positive basis has greater impact than the negative basis on the variance and covariance structure. Both in-sample and out-of-sample comparisons of the MVHR performance reveal that the model with the asymmetric effect provides greater risk reduction than the conventional models, illustrating importance of the asymmetric effect when modeling the joint dynamics of spot and futures returns and hence estimating hedging strategies.