Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach

This study analyzes the dynamic connectedness between the ESG stock index, the renewable energy stock index, the green bond stock index, the sustainability stock index, and the carbon emission futures by employing a novel method: the DCC-GARCH-based dynamic connectedness approach. Given the strong volatility spillover among these indexes, we adopt the DCC-GARCH t-copula model to calculate these indexes' hedging ratios and portfolio weights. Our findings show that the carbon emission futures are the volatility transmitter, and the green bond is the volatility receiver. The total dynamic connectedness is affected by international political, economic, and other events. Furthermore, for stock market volatility investors, taking the long position in carbon emission futures and the short position in renewable energy stock can achieve the highest hedging effect.     

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。     

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。     

A regime-switching real-time copula GARCH model for optimal futures hedging

A regime-switching real-time copula GARCH (RSRTCG) model is suggested for optimal futures hedging. The specification of RSRTCG is to model the margins of asset returns with state-dependent real-time GARCH and the dependence structure of asset returns with regime switching copula functions. RSRTCG is faster in adjusting to the new level of volatility under different market regimes which is a regime-switching multivariate generalization of the state-independent univariate real-time GARCH. RSRTCG is applied to cross hedge the price risk of S&P 500 sector indices with crude oil futures. The empirical results show that RSRTCG possesses superior hedging performance compared to its nested non-real-time or state-independent copula GARCH models based on the criterion of percentage variance reduction, utility gain, model confidence set, model combination strategy, risk-adjusted return and reward-to-semivariance ratio.     

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.     

Combining the Effects of OLS and Spread on Futures Hedging: Evidence from the Taiwan Stock Index

Abstract:

This study proposes a dynamic hedge ratio, the combined ordinary least squares spread (COLSS), which combines the hedge ratio of ordinary least squares and the value of spread. Using this dynamic ratio for hedging with futures contracts, one can replace spot risk with spread risk. The COLSS captures not only the long-run equilibrium between spot and futures returns, but also the short-run deviation from equilibrium. The spread is forecast by one-period lagged stock market factors and high-order moments that are estimated by an options model. In the in-sample and out-of-sample tests, the COLSS strategy achieves significant risk reduction and outperforms the alternative models by a large utility improvement.     

Jump-Dependent Model for Optimal Index Futures Hedging in Five Major Asian Stock Markets

This article develops a jump-dependent model to capture the dependences between spot and futures returns and their jumps simultaneously, named JD model. We examine hedging performance of the presenting JD model for the futures contracts of Hong Kong, Japan, Korea, Singapore, and Taiwan. The results have shown that the JD model has better out-of-sample performance than the OLS for Korea, Singapore, and Taiwan. Since these three markets have higher jump dependence between spot and futures, we consider that jump dependence plays an important role in hedging performance. The higher jump dependence means spot and futures markets move more closely when unusual news reveals itself and thus futures could hedge the spot more effectively when extreme unusual news arrives.     

Hedging with Chinese metal futures

This paper evaluates different hedging strategies for aluminum and copper futures contracts traded at Shanghai Futures Exchange. In addition to usual candidates such as the traditional regression hedge ratio and the hedging strategy constructed from bivariate fractionally integrated generalized autoregressive conditional heteroskedasticity (BFIGARCH) model, two advanced specifications are proposed to account for impacts of the basis on market volatility and co-movements between spot and futures returns. Empirical results suggest that the basis has asymmetric effects and optimal hedging strategy constructed from the asymmetric BFIGARCH model tends to produce the best in-sample and out-of-sample hedging performance.     

Hedging effectiveness of the Athens stock index futures contracts

This paper examines the hedging effectiveness of the FTSE/ATHEX-20 and FTSE/ATHEX Mid-40 stock index futures contracts in the relatively new and fairly unresearched futures market of Greece. Both in-sample and out-of-sample hedging performances using weekly and daily data are examined, considering both constant and time-varying hedge ratios. Results indicate that time-varying hedging strategies provide incremental risk-reduction benefits in-sample, but under-perform simple constant hedging strategies out-of-sample. Moreover, futures contracts serve effectively their risk management role and compare favourably with results in other international stock index futures markets. Estimation of investor utility functions and corresponding optimal utility maximising hedge ratios yields similar results, in terms of model selection. For the FTSE/ATHEX Mid-40 contracts we identify the existence of speculative components, which lead to utility-maximising hedge ratios, that are different to the minimum variance hedge ratio solutions.     

Swap variance hedging and efficiency: The role of high moments

In this article, we propose a new theoretical approach for developing hedging strategies based on swap variance (SwV). SwV is a generalized risk measure equivalent to a polynomial combination of all moments of a return distribution. Using the S&P 500 index and West Texas Intermediate (WTI) crude oil spot and futures price data, as well as simulations by varying the distribution of asset returns, we investigate the dynamic differences between hedge ratios and portfolio performances based on SwV (with high moments) and variance (without high moments). We find that, on average, the minimizing-SwV hedging suggests more short futures contracts than minimizing-variance hedging; however, when market conditions deteriorate, the minimizing-SwV hedging suggests fewer short positions in futures. The superior posthedge performances of the mean-SwV hedged portfolios over the mean-variance hedged portfolios in highly volatile or extremely calm markets confirm the efficiency of the mean-SwV hedging strategy.     

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。     

The use and abuse of the hedging effectiveness measure

Ederington (1979) proposed an effectiveness measure for futures hedging. Since then, this measure has been widely adopted in the literature to compare different hedge ratios against the OLS (ordinary least squares) hedge ratio. This note attempts to demonstrate this application is inappropriate. Ederington hedging effectiveness is only useful for measuring the risk reduction effect of the OLS hedge ratio. It does not apply to other hedge ratios and therefore should not serve as a criterion to compare different hedge strategies against the OLS strategy. A strict application of this measure almost always leads to an incorrect conclusion stating that the OLS hedge ratio is the best hedging strategy.     

Dynamic hedging with futures: a copula-based GARCH model with high-frequency data

Modeling the joint distribution of spot and futures returns is crucial for establishing optimal hedging strategies. This paper proposes a new class of dynamic copula-GARCH models that exploits information from high-frequency data for hedge ratio estimation. The copula theory facilitates constructing a flexible distribution; the inclusion of realized volatility measures constructed from high-frequency data enables copula forecasts to swiftly adapt to changing markets. By using data concerning equity index returns, the estimation results show that the inclusion of realized measures of volatility and correlation greatly enhances the explanatory power in the modeling. Moreover, the out-of-sample forecasting results show that the hedged portfolios constructed from the proposed model are superior to those constructed from the prevailing models in reducing the (estimated) conditional hedged portfolio variance. Finally, the economic gains from exploiting high-frequency data for estimating the hedge ratios are examined. It is found that hedgers obtain additional benefits by including high-frequency data in their hedging decisions; more risk-averse hedgers generate greater benefits.     

Determination of Optimal Hedging Strategy for Index Futures: Evidence from Turkey

This paper aims to determine optimal hedge strategy for the Istanbul Stock Exchange (ISE)-30 stock index futures in Turkey by comparing hedging performance of constant and time-varying hedge ratios under mean-variance utility criteria. We employ standard regression and bivariate GARCH frameworks to estimate constant and time-varying hedge ratios respectively. The Turkish case is particularly challenging since Turkey has one of the most volatile stock markets among emerging economies and the turnover ratio as a measure of liquidity is very high for the market. These facts can be considered to highlight the great risk and, therefore, the extra need for hedging in the Istanbul Stock Exchange (ISE). The empirical results from the study reveal that the dynamic hedge strategy outperforms the static and the traditional strategies.     

Dynamic Hedging Effectiveness in South Korean Index Futures and the Impact of the Asian Financial Crisis

This paper focuses on the impact of the 1997 Asian financial market crisis upon hedging effectiveness within the KOSPI 200 stock index and index futures markets. The paper utilizes the inter-temporal relationship between the two markets to examine the characteristics of several minimum variance hedge ratios. It also examines the performances of alternative hedging strategies for dynamic portfolio management in the presence of cointegrated time-varying risks. The results show a decline in the persistence of conditional volatility within market prices after the crisis. This decline leads to the relative performance of utilizing constant hedge ratios to increase, though not significantly so to guarantee a superior performance over more sophisticated time-varying hedge ratio strategies.     

Dissecting hedge funds' strategies

This paper dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds' return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds' investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds' performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market.     

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。     

Hedging long-term exposures with multiple short-term futures contracts

This article analyzes the problem facing an agent who has along-term commodity supply commitment and who wishes to hedgethat commitment using short-maturity commodity futures contracts.As time evolves, the agent has to roll the hedge as old futurescontracts mature and new futures contracts are listed. Thisgives rise to hedge errors. The optimal hedging strategy ischaracterized in a world where contracts of several differentmaturities coexist. The strategy is independent both of theagent's risk aversion and, under certain conditions, of beliefsabout expected returns from holding futures contracts. The methodologyis compared with approaches based on dynamic models of the termstructure. It is tested on data from the oil futures market.     

Size effect,methodological issues and ‘risk-to-default’: evidence from the UK stock market

The hedging effectiveness of dynamic strategies is compared with static (traditional) ones using futures contracts for the five leading currencies. The traditional hedging model assumes time invariance in the joint distribution of spot and futures price changes thus leading to a constant optimal hedge ratio (OHR). However, if this time-invariance assumption is violated, time-varying OHRs are appropriate for hedging purposes. A bivariate GARCH model is employed to estimate the joint distribution of spot and futures currency returns and the sequence of dynamic (time-varying) OHRs is constructed based upon the estimated parameters of the conditional covariance matrix. The empirical evidence strongly supports time-varying OHRs but the dynamic model provides superior out-of-sample hedging performance, compared to the static model, only for the Canadian dollar.     

Limits to arbitrage and hedging: Evidence from commodity markets

We build an equilibrium model of commodity markets in which speculators are capital constrained, and commodity producers have hedging demands for commodity futures. Increases in producers' hedging demand or speculators' capital constraints increase hedging costs via price-pressure on futures. These in turn affect producers' equilibrium hedging and supply decision inducing a link between a financial friction in the futures market and the commodity spot prices. Consistent with the model, measures of producers' propensity to hedge forecasts futures returns and spot prices in oil and gas market data from 1979 to 2010. The component of the commodity futures risk premium associated with producer hedging demand rises when speculative activity reduces. We conclude that limits to financial arbitrage generate limits to hedging by producers, and affect equilibrium commodity supply and prices.